RESEARCH Open Access

Bypassing primary care facilities health-seeking behavior of middle age and olderadults in ChinaChangle Li12 Zhuo Chen23 and M Mahmud Khan2

Abstract

Background With economic development aging of the population improved insurance coverage and theabsence of a formal referral system bypassing primary healthcare facilities appear to have become more commonChinese patients tend to visit the secondary or tertiary healthcare facilities directly leading to overcrowding at thehigher-level facilities This study attempts to analyze the factors associated with bypassing primary care facilitiesamong patients of age 45 years or older in China

Methods Random effects logistic models were used to examine bypassing of primary health facilities among rural-urban patients Data from 2011 to 2015 waves of the China Health and Retirement Longitudinal Study were used

Results Two in five older patients in China bypass primary health centers (PHC) to access care from higher-tierfacilities Urban patients were nearly twice as likely as rural patients to bypass PHC Regardless of rural-urban residenceour analysis found that a longer travel time to primary facilities compared to higher-tier facilities increases thelikelihood of bypassing Patients with higher educational attainment were more likely to bypass PHCs In rural areaspatients who reported their health as poor or those who experienced a recent hospitalization had a higher probabilityof bypassing PHC In urban areas older adults (age 65 years or older) were more likely to bypass PHC than the youngergroup Patients with chronic conditions like diabetes also had a higher probability of bypassing

Conclusions The findings indicate the importance of strengthening the PHCs in China to improve the efficiency andeffectiveness of the health system Significantly lower out-of-pocket costs at the PHC compared to costs at the highertiers had little or no impact on increasing the likelihood of utilizing the PHCs Improving service quality providingcomprehensive person-centered care focusing on family health care needs and providing critical preventive serviceswill help increase utilization of PHCs as well as the effectiveness and efficiency of the health system

Keywords Health-seeking behavior Bypassing Primary care Older adults China

copy The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 40 International Licensewhich permits use sharing adaptation distribution and reproduction in any medium or format as long as you giveappropriate credit to the original author(s) and the source provide a link to the Creative Commons licence and indicate ifchanges were made The images or other third party material in this article are included in the articles Creative Commonslicence unless indicated otherwise in a credit line to the material If material is not included in the articles Creative Commonslicence and your intended use is not permitted by statutory regulation or exceeds the permitted use you will need to obtainpermission directly from the copyright holder To view a copy of this licence visit httpcreativecommonsorglicensesby40The Creative Commons Public Domain Dedication waiver (httpcreativecommonsorgpublicdomainzero10) applies to thedata made available in this article unless otherwise stated in a credit line to the data

Correspondence MahmudKhanugaedu2Department of Health Policy and Management College of Public HealthUniversity of Georgia 100 Foster Rd Wright Hall 116 Athens GA 30602 USAFull list of author information is available at the end of the article

Li et al BMC Health Services Research (2021) 21895 httpsdoiorg101186s12913-021-06908-0

BackgroundHealth system of China established a three-tier health-care delivery structure in both rural and urban areassince 1950s The essential features of this system haveremained quite stable even today with a network con-necting healthcare providers at county township andvillage levels in rural areas and at municipal districtand community levels in urban areas [1] Despite struc-tural stability the 1978 economic liberalization signifi-cantly affected the functioning of the health facilities atall levels The multi-level referral system is now virtuallyabsent [2 3] With the rapid demographic transition andaging of the population the prevalence of chronic dis-eases and disabilities has increased [4] Many local levelprimary centers (PHCs) are not ready to offer chronicdisease management [5] Another significant change wasthe adoption of a universal health insurance scheme thathas provided coverage to 95 of the population since2011 [6] With rapid economic development aging ofthe population improved insurance coverage and lackof formal referral structure bypassing PHCs to seek carefrom secondary and tertiary healthcare facilities (STFs)have increased leading to overcrowding at the higher-tier facilities [7]Since the 2009 health reforms in China significant in-

vestments were made to strengthen primary care infra-structure [7 8] Many PHCs were constructed andorupgraded [9] In 2019 there were approximately 9300community health centers and 26000 community healthclinics in urban areas and 36000 township health cen-ters and 622000 village clinics in rural areas Today al-most every community has at least one PHC [10] Inaddition to encourage utilization of PHCs basic medicalinsurance schemes reimburse a higher proportion ofcosts to patients for seeking care from the PHCs ratherthan from STFs [11] The zero-profit drug policy as partof the national essential drug system (NSDS) was intro-duced in PHCs in 2009 Under the NSDS the PHCsmust sell drugs at cost without any mark-up [12 13]Despite these financial incentives in favor of PHCs thereappears to be no decline in the propensity to bypassPHCs [8]Bypassing the PHCs can adversely affect health system

performance and contributes to higher medical expendi-tures [14] People who bypass PHCs report spending ap-proximately two times more on healthcare than thosewho do not bypass PHCs [15 16] Although bypassingof PHCs has become widespread there is limited evi-dence on reasons and consequences of bypassing inChina Most studies on bypassing conducted in selectedcountries in Asia Africa and the Americas definedbypassing as incidents where people travel to another fa-cility to obtain care rather than using the nearby localfacility [17ndash23] Few other studies have defined

bypassing as skipping the PHCs to obtain care fromSTFs [24ndash26] without explicitly considering the distanceto facilities from patientsrsquo residencesIn the literature several factors are found to be im-

portant in explaining the bypassing phenomenon Im-portant demographic and socioeconomic factors includeage gender marital status educational attainment in-come health insurance status and health conditionsSanders et al [27] Shah [28] and Yao and Agadjanian[23] found that older patients are more likely to bypasslocal providers However Liu et al [29] Escarce andKapur [30] and Tai et al [31] reported the opposite forpatients in the USA Liu et al [29] found that patientswho have some college education are less likely to by-pass but Akin and Hutchinson [17] and Damrongplasitand Wangdi [25] observed the opposite Similarly Liuet al [29] and Perera and Weerasinghe [32] found apositive association between being married and bypass-ing but Damrongplasit and Wangdi concluded to thecontrary [25] In the USA like the Chinese health sys-tem most insurance plans allow patients to seek carefrom upper-level providers or facilities without formalreferralsEffects of gender socioeconomic status and health

conditions on bypassing tendency were similar acrossseveral studies Rao and Sheffel [26] and Akin andHutchinson [17] found that females are more likely thanmales to bypass local providers Rao and Sheffel [26] andYao and Agadjanian [23] reported a higher likelihood ofbypassing with increasing income or wealth Radcliffet al [33] found that uninsured patients have a lowertendency to bypass and Akin and Hutchinson [17] andTai et al [31] found that bypassing local facilities in-creases with increasing severity of medical conditionsSanders et al [27] on the other hand reported thatbypassing is more common among patients with betteroverall self-rated healthProvider characteristics associated with bypassing

include size of the practice availability of technologyservice quality and mix cost and ownership Escarceand Kapur [30] found that patients are less likely tobypass large local providers with extensive techno-logical capabilities Perceived poor quality of localhealthcare providers increases bypassing (Paul andRumsey [21] Kruk et al [18] Liu Bellamy et al [20]and Sanders et al [22]) Leonard et al [34] reportedthat patients in Tanzania bypass health providers thatoveruse injections or overprescribe drugs Patientswith relatively low income may bypass local providersto seek care from less expensive providers [16] Rohand Moon [35] and Escarce and Kapur [30] observedthat patients in rural USA are more likely to bypasslocal public-sector providers to access care from pri-vate providers

Li et al BMC Health Services Research (2021) 21895 Page 2 of 12

Patients are less likely to bypass local health care pro-viders when the distance to alternative providers is rela-tively high (Tai et al [31] Escarce and Kapur [30] andLeonard et al [34]) Varkevisser and van der Geest [36]reported that distance is an important factor in thechoice of hospitals ie patients are less likely to bypassthe nearest hospital when travel time to the next-nearesthospital increasesUnderstanding the reasons for bypassing PHCs will

help design government policies on how to make thePHCs more effective at the local level Despite the im-portance of the topic only a few studies have analyzedthis phenomenon using large longitudinal datasets Thisstudy is an attempt to understand the factors affectingthe propensity to bypass PHCs in China despite thecost-advantages created by policy makers to encouragethe utilization of PHCs

MethodsTheoretical and empirical modelsPatients have options in terms of health facilities theycan use For this analysis the current study defines theoptions as either seeking care from the ldquoprimary carecenterrdquo in the locality (PHC) or choosing an alternativeldquosecondary or tertiary facilityrdquo (STF) Patients in theorywill choose a facility-type that provides them a higherlevel of utility (u) ie if ui(PHC) lt ui(STF) patient i islikely to seek care from secondary or tertiary health fa-cilities The literature suggests that the utility u() associ-ated with the use of a health facility type may depend onseveral factors including patient characteristics illnesstype facility characteristics costs associated with seekingcare health system design Since the choice has been de-fined as a dichotomous outcome this study can developthe model by considering the likelihood of not selectingPHC [p(~PHC)] Therefore the generalized model ofbypassing PHCs can be written as

p PHCeth THORN frac14 f ZCT RjXeth THORN

where X is a vector of individual characteristics (agegender income) Z is facility-specific characteristics (egfacility size technology availability perceived quality) Cis the out-of-pocket expenses associated with thefacility-types T is travel distances and R representsother factors (eg physician recommendations on choiceof facilities)Given patient characteristics choosing a health facility

will require comparing the relevant factors between thelocal facility and other potentially accessible facilities InChina utilization of PHCs will be less expensive thanobtaining care from upper-level facilities and insurancecoverage lowers the cost of using PHCs even furtherTherefore insurance status may be used as one of the

proxy variables of financial incentives to access PHCsHigher-tier facilities by definition provide more com-prehensive healthcare services using better equipmentand technology Therefore higher severity and relativelycomplex medical conditions may benefit from accessingcare from higher-tier facilities One important factor thataffects the choice of facilities is their relative distances Ifthe closest STF is located relatively far away from acommunity patients may elect to use PHC keepingother factors constant For empirical estimation the ra-tio of the distances to PHC and STFs may be used torepresent the relative degrees of accessibility of the facil-ities This ratio is expected to be less than 10 but thehigher the ratio the greater should be the likelihood ofbypassingFor the analysis of bypassing behavior the probability

of not using PHC [p(~PHC)] the first step was to carry-out simple descriptive analysis to understand the differ-ences between patients who bypass PHCs (bypassers)and those who do not (non-bypassers) Pearsonrsquos chi-square test was used to analyze the categorical inde-pendent variables For the multivariate analysis it is as-sumed that there is an unobserved latent variable yitaffecting the decision to bypass

yit frac14 X0itαthorn Z

0itβthorn C

0itγ thorn T

0itθ thorn μi thorn εit i

frac14 1hellip n t frac14 1hellipTi

Where the vectors X0itZ

0it C

0it and T

0it represent indi-

vidual patient-specific PHC specific relative costs andrelative distances associated with PHC and other sec-ondary and tertiary health care facilities for individual iat time t α β γ and θ are the estimated coefficients ofcovariates μi is the unobserved and individual-specificheterogeneity and εit is a time-varying error term Thereis a binary variable yit = [~PHC] where

yit frac14 PHCfrac12 frac14 1 if yit gt 0 and 0 otherwise

where yit = 1 indicates that the individual did not usePHC ie bypassed the primary level of careThe probability that yit = 1 ie P(~PHC) can be writ-

ten as

P PHCeth THORN frac14 P yit frac14 1eth jX 0itZ

0itC

0it T

0it α β γ θ μiTHORN

frac14 P yit gt 0 X

0it Z

0itC

0itT

0it α β γ θ μiTHORN

frac14 P X0itαthorn Z

0itβthorn C

0itγ thorn T

0itθ thorn μi thorn εit gt 0

X0itZ

0itC

0it T

0it α β γ θ μiTHORN

frac14 P minusεit lt X0itαthorn Z

0itβthorn C

0itγ thorn T

0itθ thorn μi

X0itZ

0itC

0it T

0it α β γ θ μiTHORN

frac14 F μi thorn X0itαthorn Z

0itβthorn C

0itγ thorn T

0itθ

It assumes that the error term εit follows a logistic dis-tribution as expressed below

Li et al BMC Health Services Research (2021) 21895 Page 3 of 12

P PHCeth THORN frac14 P yit frac14 1eth j X 0itZ

0it C

0it T

0it α β γ θ μi

frac14 eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

1thorn eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

P yit frac14 0eth j X 0it Z

0it C

0it T

0it α β γ θ μi

frac14 1

1thorn eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

Furthermore the present study assumes that μi is notrelated to the covariates Correlation between μi and thecovariates would indicate a fixed-effects model [37]

Data sourceThe China Health and Retirement Longitudinal Study(CHARLS) conducted by the National School of Devel-opment of Peking University is the data set used for thisanalysis The sample of CHARLS was drawn from 450villages or urban communities of 150 counties or equiva-lent urban districts in 28 provinces A multistage strati-fied sampling with probability proportional to size wasused for the survey More details on the sampling anddata collection process are available in Zhao et al [38]The CHARLS is nationally representative and collectsdata from persons of age 45 years or older and theirspouses The CHARLS respondents are reinterviewedevery 2 years with the first wave in 2011 covering17705 persons and two follow-ups in 2013 and 2015with 18605 persons and 21095 persons respectivelyThe CHARLS questionnaires include questions onhousehold characteristics demographic backgroundhealth status and physical functioning health careutilization insurance status work retirement and pen-sion income expenditure asset ownership housingcharacteristics etc From the datasets only the individ-uals who sought outpatient care during the previous 4weeks before the date of interview were selected Thefinal sample consisted of a total of 10061 individuals inall three waves combined

MeasuresRural and urban definitionsIn the CHARLS each adult was asked ldquoWhat is the typeof your addressrdquo and ldquoIs it a rural village or urban com-munityrdquo All respondents were classified as either ruralor urban residents based on their responses

Dependent variableThe PHCs in China provide generalist clinical care andbasic public health services through community healthcenters and clinics in the urban areas and township hos-pitals and village clinics in the rural areas [13 39] Inthis study bypassing PHCs has been defined as skippingany primary care facilities to obtain care from the

secondary or tertiary level Responses to the followingsurvey questions were used to identify the incidence ofldquobypassingrdquo (1) Which healthcare provider did you visitmost recently during the past 4 weeks 1 General hos-pital 2 Specialized hospital 3 Chinese medicine hos-pital 4 Community healthcare center 5 Townshiphospital 6 Community health clinic 7 Village clinicPrivate clinic and 8 Other and (2) Did the providervisit you at home 1 Yes and 2 No If a respondent an-swered Question (1) by selecting any of General hospitalSpecialized hospital or Chinese medicine hospital andreported ldquoNordquo on Question (2) the patient is consideredto have had a ldquobypassingrdquo of the PHC The respondentswho reported using ldquoOtherrdquo providers in Question (1) orldquoYesrdquo to Question (2) were dropped from this studysample

Independent variablesIndependent variables were chosen based on theoreticalconsiderations and literature review The survey col-lected data on travel time to the facility for each of thepatients Therefore those who obtained care from PHCsreported travel time to the PHCs while those who vis-ited the upper-level facilities (STFs) reported travel timeto those facilities Reported travel times to facility-types(PHCs or STFs) were used to predict the travel times toPHCs and STFs for all patients living in a communitybut did not visit the facility-type The average travel timeto PHCs for patients living in a community for examplewas used to approximate the travel time of those livingin the same community but did not use the PHCs Thesame method was used to predict the travel time fromhome to an STF for patients in each community Rela-tive travel time was defined as the ratio of travel time toa PHC to travel time to an STFChina has two basic medical insurance schemes

Urban Employee Basic Medical Insurance and Urbanand Rural Resident Basic Medical Insurance (the medicalinsurance of integrating Urban Resident Basic MedicalInsurance and New Rural Cooperative Medical Schemeofficially in 2016) Insurance status affects out-of-pocketexpenses of patients differentially for seeking care fromPHCs and STFs Another critical factor affecting bypass-ing is patientsrsquo medical conditions especially the pres-ence of chronic conditions This analysis included anextensive list of chronic conditions including hyperten-sion dyslipidemia diabetes cancer chronic lung dis-eases liver disease heart diseases stroke emotionalnervous or psychiatric problems Definitions of the vari-ables are given in Table 1

Data analysisThis analysis is based on a sample of 10061 respon-dents who sought outpatient care during the 4 weeks

Li et al BMC Health Services Research (2021) 21895 Page 4 of 12

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015

Variable Description

Dependent variable

Bypassing 1 if a patient bypasses primary health center (PHC) to seek care from a higher-tier facility (secondary or tertiary facilities)0 otherwise

Independent variable

Age (years)

45ndash54 1 if the individual is aged 45ndash54 years 0 otherwise

55ndash64 1 if the individual is aged 55ndash64 years 0 otherwise

ge 65 1 if the individual is aged ge65 years 0 otherwise

Male 1 if the individual is male 0 for female

Educational attainment

Illiterate 1 if the individual is illiterate 0 otherwise

Elementary school 1 if the individual attended elementary school 0 otherwise

Middle school 1 if the individual graduated from middle school 0 otherwise

High school 1 if the individual graduated from high school 0 otherwise

Above three-years ofcollege

1 if the individual had above three-years of college 0 otherwise

Married 1 if the individual is married 0 otherwise

Household income

Low income 1 if the individualrsquos household income is in the first quartile 0 otherwise

Lower middle income 1 if the individualrsquos household income is in second quartile 0 otherwise

Upper middle income 1 if the individualrsquos household income is in the third quartile 0 otherwise

High income 1 if the individualrsquos household income is in the highest quartile 0 otherwise

Medical insurance

UEMI 1 if the individual is enrolled in Urban Employee Medical Insurance 0 otherwise

URMI 1 if the individual is enrolled in Urban Resident Medical Insurance 0 otherwise

NRCMI 1 if the individual is enrolled in New Rural Cooperative Medical Insurance 0 otherwise

Other Insurance 1 if the individual is enrolled in Government Medical Insurance Urban and Rural has either Resident Medical InsurancePrivate Medical Insurance Medical Aid or Other medical insurance 0 otherwise

No Insurance 1 if the individual does not have medical insurance 0 otherwise

Health status

Poor 1 if the individual reports health status to be poor 0 otherwise

Fair 1 if the individual reports health status to be fair 0 otherwise

Good 1 if the individual reports health status to be good or better 0 otherwise

Specific chronic conditions

Hypertension 1 if the individual has hypertension 0 otherwise

Dyslipidemia 1 if the individual has dyslipidemia 0 otherwise

Diabetes 1 if the individual has diabetes or high blood sugar 0 otherwise

Chronic lung diseases 1 if the individual has chronic lung diseases 0 otherwise

Heart diseases 1 if the individual has heart diseases 0 otherwise

Kidney disease 1 if the individual has kidney disease 0 otherwise

Stomach diseases 1 if the individual has stomach or other digestive diseases 0 otherwise

Arthritis orrheumatism

1 if the individual has arthritis or rheumatism 0 otherwise

Other major chronic 1 if the individual has cancer or malignant tumor liver disease stroke emotional nervous or psychiatric problems

Li et al BMC Health Services Research (2021) 21895 Page 5 of 12

prior to the survey date Since follow-up visits maybias the results this study has estimated the modelsseparately for all visits (first visit and revisits) and thefirst visits The sample size for first visits for an epi-sode of illness was 4720 If the primary care providersin the first visits refer patients to specialists the sub-sequent visits may reflect physician recommendationsrather than patientsrsquo decision-making In other wordsat least some of the revisits may not be consideredbypassing of the PHCsLogistic regression models were employed to analyze

factors affecting propensity to bypass PHCs stratified byrural-urban residence Since access to health facilitiesdiffers significantly between rural and urban areas thestratification is important to avoid potential bias createdby rural-urban differences (see Table A1 of Additionalfile 1) The annex table also identifies a number of rele-vant variables for inclusion in the regression models Inmost panel studies the preferred empirical model wouldbe either the fixed-effects or the random-effects logisticmodel [37] and empirical results should guide the choicebetween the model-typesWhen estimating the patient fixed effects model

whenever patients bypass (or do not bypass) PHC in twowaves or all three waves by definition variations overtime becomes zero and the empirical model will dropthe cases In the full sample of the fixed effects logisticmodels 6620 out of 7672 rural patients and 2185 out of2389 urban patients were dropped because of lack ofinter-temporal variation The random-effects model usesall the available observations and allows estimation ofparameters and standard errors [40] This study usedHausmanrsquos specification test for the random effects lo-gistic regression models to test the orthogonality of therandom effects and the regressors [41] The Hausmantest suggests that the random-effects model is preferredover the fixed-effects model

ResultsAmong those who used outpatient services the percentof patients bypassing PHCs were 340 in Wave 1394 in Wave 2 and 418 in Wave 3 indicating an in-creasing trend of bypassing over the years In rural areasthe percent bypassing PHCs were 270 in Wave 1330 in Wave 2 and 346 in Wave 3 In contrast thepropensity to bypass PHCs remained almost static inurban areas over the years ndash 624 in Wave 1 611 inWave 2 and 601 in Wave 3 Urban patients werenearly twice as likely as rural patients to bypass PHCsThe results remained similar when only the first visitswere considered ie excluding the follow-up outpatientvisits Table A1 of Additional file 1 compares patientcharacteristics by bypassing behavior (patients bypassingPHCs vs those not bypassing) The results indicate thatbypassers differed from non-bypassers in terms of theirresidence educational attainment household incomemedical insurance coverage specific chronic conditionsand the incidence of hospitalizationThe odds ratios of the random effects logistic regres-

sion analysis are reported in Table 2 The results implythat rural patients aged 65 years or older were less likelyto bypass PHCs than patients in the age group 45ndash54years (OR = 064 p lt 0001) In contrast patients aged65 years or older show a higher probability of bypassingin urban areas (OR = 147 p = 0036) The probability ofbypassing PHCs increases with higher educational at-tainment in both rural and urban areas Compared toilliterate patients individuals who attended elementaryschool show increased odds of bypassing by 22 in ruralareas (OR = 122 p lt 0012) and completion of morethan 3 years of college increased the odds by 236 inurban areas (OR = 336 p lt 0001) Urban patients in thelower-middle income category were less likely to bypassPHCs than those with high income (OR = 056 p =0010) A similar trend was observed for patients in the

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015 (Continued)

Variable Description

diseases memory-related disease or asthma 0 otherwise

Functional limitations

None 1 if the individual can eat toilet dress batheshower get inout of bed and walk without difficulty 0 otherwise

Mild 1 if the individual has one or two difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Moderate 1 if the individual has three or four difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Severe 1 if the individual has five to six difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Hospitalization 1 if the individual reports hospitalization in the past 12 months 0 otherwise

Relative travel time The ratio of travel time to a primary care facility to travel time to a secondary or tertiary level facility for individuals inthe community

Li et al BMC Health Services Research (2021) 21895 Page 6 of 12

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 092 (078 107) 0273 112 (081 154) 0506

ge 65 064 (053 077) lt 0001 147 (103 211) 0036

Male 111 (096 127) 0161 102 (078 135) 0871

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 122 (104 143) 0012 130 (087 194) 0195

Middle school 157 (127 193) lt 0001 197 (127 305) 0002

High school 187 (138 254) lt 0001 282 (173 459) lt 0001

gt three-years of college 176 (051 610) 0373 336 (177 637) lt 0001

Married 109 (089 133) 0397 105 (072 154) 0798

Household income

Low income 084 (069 102) 0081 084 (058 120) 0332

Lower middle income 087 (072 105) 0156 056 (036 087) 0010

Upper middle income 095 (079 115) 0602 069 (050 094) 0018

High income 100 Ref 100 Ref

Medical insurance

UEMI 301 (173 522) lt 0001 152 (087 267) 0140

URMI 149 (072 306) 0283 162 (087 300) 0125

NRCMI 092 (068 124) 0576 047 (026 085) 0012

Other Insurance 110 (060 200) 0775 103 (059 178) 0929

No Insurance 100 Ref 100 Ref

Health status

Poor 134 (116 154) lt 0001 128 (094 173) 0113

Fair 100 Ref

Good 122 (099 151) 0063 098 (068 141) 0900

Specific chronic conditions

Hypertension 095 (081 111) 0492 082 (061 111) 0195

Dyslipidemia 124 (099 156) 0061 101 (071 143) 0959

Diabetes 113 (086 148) 0374 176 (115 270) 0009

Chronic lung diseases 087 (071 105) 0155 098 (065 147) 0906

Heart diseases 140 (115 170) 0001 124 (087 176) 0228

Kidney disease 081 (064 102) 0073 070 (044 112) 0138

Stomach diseases 088 (077 102) 0087 093 (068 128) 0662

Arthritis or rheumatism 083 (072 095) 0006 089 (066 120) 0442

Other major chronic diseases 088 (073 106) 0192 064 (044 091) 0015

Functional limitations

None 100 Ref 100 Ref

Mild 093 (079 110) 0401 106 (073 154) 0745

Moderate 102 (076 135) 0907 119 (057 246) 0643

Severe 144 (095 217) 0085 154 (055 432) 0408

Li et al BMC Health Services Research (2021) 21895 Page 7 of 12

upper-middle income category (OR = 069 p = 0018)Rural patients enrolled in Urban Employee Basic Med-ical Insurance had three times the odds (OR = 301 p lt0001) of bypassing PHCs than the uninsured Comparedwith the uninsured patients urban patients enrolled inNew Rural Cooperative Medical Scheme had a lowerodds of bypassing (OR = 047 p = 0012)Rural patients with poor health were more likely to by-

pass PHCs than those who reported their health beinglsquofairrsquo (OR = 134 p lt 0001) Patients with heart diseasesin rural areas and urban patients with diabetes had ahigher odds of bypassing PHCs (OR = 140 p = 0001OR = 176 p = 0009) and the opposite was true for ruralpatients with arthritis or rheumatism and patients withother major chronic conditions in urban areas (OR =083 p = 0006 OR = 064 p = 0015) Patients who expe-rienced hospitalization in the past 12 months had ahigher odds of bypassing in both the rural and urbanareas (OR = 208 p lt 0001 OR = 215 p lt 0001) Rela-tive travel time was positively associated with patientsbypassing PHCs in rural and urban areas (OR = 115 p lt0001 OR = 128 p lt 0001)Table 3 presents factors affecting bypassing PHCs

when only the first contact outpatient visits are used inthe estimation The results are similar to the estimatesobtained when all visits including the revisits were usedin the analysis

DiscussionThe nationally representative survey indicates that theproportion of outpatients bypassing PHCs increased overthe years in China Urban patients were nearly twice aslikely to bypass PHCs than rural patients This is not un-expected due to the easy access and availability of manySTFs in urban areas Travel distance and travel-relatedcosts are likely to be lower for the urban population [3642] Rural patients often must rely on PHCs in the areadue to the difficulty of accessing alternative health careproviders Especially for rural residents obtaining carefrom upper-level facilities may become quite expensivedue to higher out-of-pocket expenses and longer traveltimes [43]About two in five older adults in China bypassed

PHCs to obtain care from upper-level providers (STFs)

This is despite significantly lower out-of-pocket costs forservices and drugs at PHCs than at the STFs Thereforefinancial incentives have not been adequate to discour-age bypassing of PHCs in China The results imply thatpropensity to bypass PHCs is unlikely to decline signifi-cantly if the financial incentives in favor of PHCs aremade even stronger Given that the bypassing tendencyis related to age ruralurban location present of chronicconditions etc it points to supply-side concerns prob-ably related to availability and quality of service-mix of-fered at the PHCsThe random-effects logistic regression model identi-

fied several factors affecting bypassing of PHCs for ruraland urban residents separately The estimates suggestthat factors affecting the first visits are very similar tofactors affecting all outpatient visits (both new andfollow-up visits) implying that physician recommenda-tions were not important in influencing the choice offacility-types Regardless of rural-urban residence a rela-tive increase in travel time (ratio of travel times to PHCand STF) increased the probability of bypassing PHCsThe result is consistent with the findings in the litera-ture ie increased travel time lowers the utilization ofhealth care facilities [33 44ndash50] Without a formal refer-ral system in urban areas where health resources aremuch richer and STFs are more concentrated than thosein rural areas in China urban patients are more likely tobypass PHCs because of easy accessibility and availabilityof medical care services they needPatients with higher educational attainment show a

higher probability of bypassing PHCs Educational at-tainment is an indicator of socioeconomic status (SES)as well as knowledge about the relative quality of ser-vices facilities offer Middle-aged and older adults withhigher level of income are also more likely to bypassPHCs This probably indicates perception of lower qual-ity of services at the PHCs compared to the STFs Withan increase in income and educational attainment pa-tients become more sensitive to service quality and lesssensitive to cost savings that can be achieved by utilizingPHCsIn rural areas self-reported poor health status in-

creased the likelihood of bypassing PHCs Again thispossibly reflects a lack of confidence in the quality of

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 208 (177 245) lt 0001 215 (153 302) lt 0001

Relative travel time 115 (113 117) lt 0001 128 (118 139) lt 0001

Constant 025 (017 038) lt 0001 063 (030 130) 0207

Observations 7672 2389

Li et al BMC Health Services Research (2021) 21895 Page 8 of 12

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 108 (085 139) 0488 102 (069 150) 0932

ge 65 091 (068 121) 0509 171 (107 273) 0024

Male 103 (084 129) 0727 100 (071 140) 0998

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 121 (095 155) 0120 169 (100 285) 0050

Middle school 162 (117 224) 0004 216 (121 385) 0009

High school 189 (116 306) 0010 252 (134 476) 0004

gt three-years of college 556 (097 3181) 0054 294 (126 686) 0013

Married 107 (078 147) 0681 102 (063 165) 0936

Household income

Low income 104 (077 140) 0808 101 (064 160) 0959

Lower middle income 102 (076 136) 0921 063 (036 111) 0110

Upper middle income 111 (083 148) 0498 073 (049 109) 0129

High income 100 Ref 100 Ref

Medical insurance

UEMI 153 (062 375) 0354 155 (076 316) 0227

URMI 284 (090 896) 0075 140 (065 302) 0387

NRCMI 086 (054 136) 0517 058 (028 119) 0136

Other Insurance 110 (033 217) 0726 086 (044 168) 0664

No Insurance 084 Ref 100 Ref

Health status

Poor 159 (125 202) lt 0001 103 (069 156) 0872

Fair 100 Ref

Good 134 (099 181) 0056 099 (065 151) 0972

Specific chronic conditions

Hypertension 102 (079 131) 0897 093 (063 137) 0705

Dyslipidemia 163 (112 237) 0010 094 (060 147) 0778

Diabetes 093 (057 150) 0758 196 (100 383) 0049

Chronic lung diseases 096 (070 131) 0790 104 (061 180) 0876

Heart diseases 120 (086 168) 0291 140 (087 225) 0172

Kidney disease 059 (039 089) 0013 067 (036 125) 0210

Stomach diseases 088 (070 111) 0281 102 (070 150) 0911

Arthritis or rheumatism 079 (064 098) 0035 096 (067 137) 0807

Other major chronic diseases 088 (064 120) 0413 063 (037 105) 0075

Functional limitations

None 100 Ref 100 Ref

Mild 106 (080 141) 0662 107 (065 177) 0783

Moderate 147 (092 234) 0107 169 (049 587) 0410

Severe 191 (082 446) 0133 152 (031 744) 0603

Li et al BMC Health Services Research (2021) 21895 Page 9 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

Patients are less likely to bypass local health care pro-viders when the distance to alternative providers is rela-tively high (Tai et al [31] Escarce and Kapur [30] andLeonard et al [34]) Varkevisser and van der Geest [36]reported that distance is an important factor in thechoice of hospitals ie patients are less likely to bypassthe nearest hospital when travel time to the next-nearesthospital increasesUnderstanding the reasons for bypassing PHCs will

help design government policies on how to make thePHCs more effective at the local level Despite the im-portance of the topic only a few studies have analyzedthis phenomenon using large longitudinal datasets Thisstudy is an attempt to understand the factors affectingthe propensity to bypass PHCs in China despite thecost-advantages created by policy makers to encouragethe utilization of PHCs

MethodsTheoretical and empirical modelsPatients have options in terms of health facilities theycan use For this analysis the current study defines theoptions as either seeking care from the ldquoprimary carecenterrdquo in the locality (PHC) or choosing an alternativeldquosecondary or tertiary facilityrdquo (STF) Patients in theorywill choose a facility-type that provides them a higherlevel of utility (u) ie if ui(PHC) lt ui(STF) patient i islikely to seek care from secondary or tertiary health fa-cilities The literature suggests that the utility u() associ-ated with the use of a health facility type may depend onseveral factors including patient characteristics illnesstype facility characteristics costs associated with seekingcare health system design Since the choice has been de-fined as a dichotomous outcome this study can developthe model by considering the likelihood of not selectingPHC [p(~PHC)] Therefore the generalized model ofbypassing PHCs can be written as

p PHCeth THORN frac14 f ZCT RjXeth THORN

where X is a vector of individual characteristics (agegender income) Z is facility-specific characteristics (egfacility size technology availability perceived quality) Cis the out-of-pocket expenses associated with thefacility-types T is travel distances and R representsother factors (eg physician recommendations on choiceof facilities)Given patient characteristics choosing a health facility

will require comparing the relevant factors between thelocal facility and other potentially accessible facilities InChina utilization of PHCs will be less expensive thanobtaining care from upper-level facilities and insurancecoverage lowers the cost of using PHCs even furtherTherefore insurance status may be used as one of the

proxy variables of financial incentives to access PHCsHigher-tier facilities by definition provide more com-prehensive healthcare services using better equipmentand technology Therefore higher severity and relativelycomplex medical conditions may benefit from accessingcare from higher-tier facilities One important factor thataffects the choice of facilities is their relative distances Ifthe closest STF is located relatively far away from acommunity patients may elect to use PHC keepingother factors constant For empirical estimation the ra-tio of the distances to PHC and STFs may be used torepresent the relative degrees of accessibility of the facil-ities This ratio is expected to be less than 10 but thehigher the ratio the greater should be the likelihood ofbypassingFor the analysis of bypassing behavior the probability

of not using PHC [p(~PHC)] the first step was to carry-out simple descriptive analysis to understand the differ-ences between patients who bypass PHCs (bypassers)and those who do not (non-bypassers) Pearsonrsquos chi-square test was used to analyze the categorical inde-pendent variables For the multivariate analysis it is as-sumed that there is an unobserved latent variable yitaffecting the decision to bypass

yit frac14 X0itαthorn Z

0itβthorn C

0itγ thorn T

0itθ thorn μi thorn εit i

frac14 1hellip n t frac14 1hellipTi

Where the vectors X0itZ

0it C

0it and T

0it represent indi-

vidual patient-specific PHC specific relative costs andrelative distances associated with PHC and other sec-ondary and tertiary health care facilities for individual iat time t α β γ and θ are the estimated coefficients ofcovariates μi is the unobserved and individual-specificheterogeneity and εit is a time-varying error term Thereis a binary variable yit = [~PHC] where

yit frac14 PHCfrac12 frac14 1 if yit gt 0 and 0 otherwise

where yit = 1 indicates that the individual did not usePHC ie bypassed the primary level of careThe probability that yit = 1 ie P(~PHC) can be writ-

ten as

P PHCeth THORN frac14 P yit frac14 1eth jX 0itZ

0itC

0it T

0it α β γ θ μiTHORN

frac14 P yit gt 0 X

0it Z

0itC

0itT

0it α β γ θ μiTHORN

frac14 P X0itαthorn Z

0itβthorn C

0itγ thorn T

0itθ thorn μi thorn εit gt 0

X0itZ

0itC

0it T

0it α β γ θ μiTHORN

frac14 P minusεit lt X0itαthorn Z

0itβthorn C

0itγ thorn T

0itθ thorn μi

X0itZ

0itC

0it T

0it α β γ θ μiTHORN

frac14 F μi thorn X0itαthorn Z

0itβthorn C

0itγ thorn T

0itθ

It assumes that the error term εit follows a logistic dis-tribution as expressed below

Li et al BMC Health Services Research (2021) 21895 Page 3 of 12

P PHCeth THORN frac14 P yit frac14 1eth j X 0itZ

0it C

0it T

0it α β γ θ μi

frac14 eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

1thorn eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

P yit frac14 0eth j X 0it Z

0it C

0it T

0it α β γ θ μi

frac14 1

1thorn eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

Furthermore the present study assumes that μi is notrelated to the covariates Correlation between μi and thecovariates would indicate a fixed-effects model [37]

Data sourceThe China Health and Retirement Longitudinal Study(CHARLS) conducted by the National School of Devel-opment of Peking University is the data set used for thisanalysis The sample of CHARLS was drawn from 450villages or urban communities of 150 counties or equiva-lent urban districts in 28 provinces A multistage strati-fied sampling with probability proportional to size wasused for the survey More details on the sampling anddata collection process are available in Zhao et al [38]The CHARLS is nationally representative and collectsdata from persons of age 45 years or older and theirspouses The CHARLS respondents are reinterviewedevery 2 years with the first wave in 2011 covering17705 persons and two follow-ups in 2013 and 2015with 18605 persons and 21095 persons respectivelyThe CHARLS questionnaires include questions onhousehold characteristics demographic backgroundhealth status and physical functioning health careutilization insurance status work retirement and pen-sion income expenditure asset ownership housingcharacteristics etc From the datasets only the individ-uals who sought outpatient care during the previous 4weeks before the date of interview were selected Thefinal sample consisted of a total of 10061 individuals inall three waves combined

MeasuresRural and urban definitionsIn the CHARLS each adult was asked ldquoWhat is the typeof your addressrdquo and ldquoIs it a rural village or urban com-munityrdquo All respondents were classified as either ruralor urban residents based on their responses

Dependent variableThe PHCs in China provide generalist clinical care andbasic public health services through community healthcenters and clinics in the urban areas and township hos-pitals and village clinics in the rural areas [13 39] Inthis study bypassing PHCs has been defined as skippingany primary care facilities to obtain care from the

secondary or tertiary level Responses to the followingsurvey questions were used to identify the incidence ofldquobypassingrdquo (1) Which healthcare provider did you visitmost recently during the past 4 weeks 1 General hos-pital 2 Specialized hospital 3 Chinese medicine hos-pital 4 Community healthcare center 5 Townshiphospital 6 Community health clinic 7 Village clinicPrivate clinic and 8 Other and (2) Did the providervisit you at home 1 Yes and 2 No If a respondent an-swered Question (1) by selecting any of General hospitalSpecialized hospital or Chinese medicine hospital andreported ldquoNordquo on Question (2) the patient is consideredto have had a ldquobypassingrdquo of the PHC The respondentswho reported using ldquoOtherrdquo providers in Question (1) orldquoYesrdquo to Question (2) were dropped from this studysample

Independent variablesIndependent variables were chosen based on theoreticalconsiderations and literature review The survey col-lected data on travel time to the facility for each of thepatients Therefore those who obtained care from PHCsreported travel time to the PHCs while those who vis-ited the upper-level facilities (STFs) reported travel timeto those facilities Reported travel times to facility-types(PHCs or STFs) were used to predict the travel times toPHCs and STFs for all patients living in a communitybut did not visit the facility-type The average travel timeto PHCs for patients living in a community for examplewas used to approximate the travel time of those livingin the same community but did not use the PHCs Thesame method was used to predict the travel time fromhome to an STF for patients in each community Rela-tive travel time was defined as the ratio of travel time toa PHC to travel time to an STFChina has two basic medical insurance schemes

Urban Employee Basic Medical Insurance and Urbanand Rural Resident Basic Medical Insurance (the medicalinsurance of integrating Urban Resident Basic MedicalInsurance and New Rural Cooperative Medical Schemeofficially in 2016) Insurance status affects out-of-pocketexpenses of patients differentially for seeking care fromPHCs and STFs Another critical factor affecting bypass-ing is patientsrsquo medical conditions especially the pres-ence of chronic conditions This analysis included anextensive list of chronic conditions including hyperten-sion dyslipidemia diabetes cancer chronic lung dis-eases liver disease heart diseases stroke emotionalnervous or psychiatric problems Definitions of the vari-ables are given in Table 1

Data analysisThis analysis is based on a sample of 10061 respon-dents who sought outpatient care during the 4 weeks

Li et al BMC Health Services Research (2021) 21895 Page 4 of 12

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015

Variable Description

Dependent variable

Bypassing 1 if a patient bypasses primary health center (PHC) to seek care from a higher-tier facility (secondary or tertiary facilities)0 otherwise

Independent variable

Age (years)

45ndash54 1 if the individual is aged 45ndash54 years 0 otherwise

55ndash64 1 if the individual is aged 55ndash64 years 0 otherwise

ge 65 1 if the individual is aged ge65 years 0 otherwise

Male 1 if the individual is male 0 for female

Educational attainment

Illiterate 1 if the individual is illiterate 0 otherwise

Elementary school 1 if the individual attended elementary school 0 otherwise

Middle school 1 if the individual graduated from middle school 0 otherwise

High school 1 if the individual graduated from high school 0 otherwise

Above three-years ofcollege

1 if the individual had above three-years of college 0 otherwise

Married 1 if the individual is married 0 otherwise

Household income

Low income 1 if the individualrsquos household income is in the first quartile 0 otherwise

Lower middle income 1 if the individualrsquos household income is in second quartile 0 otherwise

Upper middle income 1 if the individualrsquos household income is in the third quartile 0 otherwise

High income 1 if the individualrsquos household income is in the highest quartile 0 otherwise

Medical insurance

UEMI 1 if the individual is enrolled in Urban Employee Medical Insurance 0 otherwise

URMI 1 if the individual is enrolled in Urban Resident Medical Insurance 0 otherwise

NRCMI 1 if the individual is enrolled in New Rural Cooperative Medical Insurance 0 otherwise

Other Insurance 1 if the individual is enrolled in Government Medical Insurance Urban and Rural has either Resident Medical InsurancePrivate Medical Insurance Medical Aid or Other medical insurance 0 otherwise

No Insurance 1 if the individual does not have medical insurance 0 otherwise

Health status

Poor 1 if the individual reports health status to be poor 0 otherwise

Fair 1 if the individual reports health status to be fair 0 otherwise

Good 1 if the individual reports health status to be good or better 0 otherwise

Specific chronic conditions

Hypertension 1 if the individual has hypertension 0 otherwise

Dyslipidemia 1 if the individual has dyslipidemia 0 otherwise

Diabetes 1 if the individual has diabetes or high blood sugar 0 otherwise

Chronic lung diseases 1 if the individual has chronic lung diseases 0 otherwise

Heart diseases 1 if the individual has heart diseases 0 otherwise

Kidney disease 1 if the individual has kidney disease 0 otherwise

Stomach diseases 1 if the individual has stomach or other digestive diseases 0 otherwise

Arthritis orrheumatism

1 if the individual has arthritis or rheumatism 0 otherwise

Other major chronic 1 if the individual has cancer or malignant tumor liver disease stroke emotional nervous or psychiatric problems

Li et al BMC Health Services Research (2021) 21895 Page 5 of 12

prior to the survey date Since follow-up visits maybias the results this study has estimated the modelsseparately for all visits (first visit and revisits) and thefirst visits The sample size for first visits for an epi-sode of illness was 4720 If the primary care providersin the first visits refer patients to specialists the sub-sequent visits may reflect physician recommendationsrather than patientsrsquo decision-making In other wordsat least some of the revisits may not be consideredbypassing of the PHCsLogistic regression models were employed to analyze

factors affecting propensity to bypass PHCs stratified byrural-urban residence Since access to health facilitiesdiffers significantly between rural and urban areas thestratification is important to avoid potential bias createdby rural-urban differences (see Table A1 of Additionalfile 1) The annex table also identifies a number of rele-vant variables for inclusion in the regression models Inmost panel studies the preferred empirical model wouldbe either the fixed-effects or the random-effects logisticmodel [37] and empirical results should guide the choicebetween the model-typesWhen estimating the patient fixed effects model

whenever patients bypass (or do not bypass) PHC in twowaves or all three waves by definition variations overtime becomes zero and the empirical model will dropthe cases In the full sample of the fixed effects logisticmodels 6620 out of 7672 rural patients and 2185 out of2389 urban patients were dropped because of lack ofinter-temporal variation The random-effects model usesall the available observations and allows estimation ofparameters and standard errors [40] This study usedHausmanrsquos specification test for the random effects lo-gistic regression models to test the orthogonality of therandom effects and the regressors [41] The Hausmantest suggests that the random-effects model is preferredover the fixed-effects model

ResultsAmong those who used outpatient services the percentof patients bypassing PHCs were 340 in Wave 1394 in Wave 2 and 418 in Wave 3 indicating an in-creasing trend of bypassing over the years In rural areasthe percent bypassing PHCs were 270 in Wave 1330 in Wave 2 and 346 in Wave 3 In contrast thepropensity to bypass PHCs remained almost static inurban areas over the years ndash 624 in Wave 1 611 inWave 2 and 601 in Wave 3 Urban patients werenearly twice as likely as rural patients to bypass PHCsThe results remained similar when only the first visitswere considered ie excluding the follow-up outpatientvisits Table A1 of Additional file 1 compares patientcharacteristics by bypassing behavior (patients bypassingPHCs vs those not bypassing) The results indicate thatbypassers differed from non-bypassers in terms of theirresidence educational attainment household incomemedical insurance coverage specific chronic conditionsand the incidence of hospitalizationThe odds ratios of the random effects logistic regres-

sion analysis are reported in Table 2 The results implythat rural patients aged 65 years or older were less likelyto bypass PHCs than patients in the age group 45ndash54years (OR = 064 p lt 0001) In contrast patients aged65 years or older show a higher probability of bypassingin urban areas (OR = 147 p = 0036) The probability ofbypassing PHCs increases with higher educational at-tainment in both rural and urban areas Compared toilliterate patients individuals who attended elementaryschool show increased odds of bypassing by 22 in ruralareas (OR = 122 p lt 0012) and completion of morethan 3 years of college increased the odds by 236 inurban areas (OR = 336 p lt 0001) Urban patients in thelower-middle income category were less likely to bypassPHCs than those with high income (OR = 056 p =0010) A similar trend was observed for patients in the

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015 (Continued)

Variable Description

diseases memory-related disease or asthma 0 otherwise

Functional limitations

None 1 if the individual can eat toilet dress batheshower get inout of bed and walk without difficulty 0 otherwise

Mild 1 if the individual has one or two difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Moderate 1 if the individual has three or four difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Severe 1 if the individual has five to six difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Hospitalization 1 if the individual reports hospitalization in the past 12 months 0 otherwise

Relative travel time The ratio of travel time to a primary care facility to travel time to a secondary or tertiary level facility for individuals inthe community

Li et al BMC Health Services Research (2021) 21895 Page 6 of 12

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 092 (078 107) 0273 112 (081 154) 0506

ge 65 064 (053 077) lt 0001 147 (103 211) 0036

Male 111 (096 127) 0161 102 (078 135) 0871

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 122 (104 143) 0012 130 (087 194) 0195

Middle school 157 (127 193) lt 0001 197 (127 305) 0002

High school 187 (138 254) lt 0001 282 (173 459) lt 0001

gt three-years of college 176 (051 610) 0373 336 (177 637) lt 0001

Married 109 (089 133) 0397 105 (072 154) 0798

Household income

Low income 084 (069 102) 0081 084 (058 120) 0332

Lower middle income 087 (072 105) 0156 056 (036 087) 0010

Upper middle income 095 (079 115) 0602 069 (050 094) 0018

High income 100 Ref 100 Ref

Medical insurance

UEMI 301 (173 522) lt 0001 152 (087 267) 0140

URMI 149 (072 306) 0283 162 (087 300) 0125

NRCMI 092 (068 124) 0576 047 (026 085) 0012

Other Insurance 110 (060 200) 0775 103 (059 178) 0929

No Insurance 100 Ref 100 Ref

Health status

Poor 134 (116 154) lt 0001 128 (094 173) 0113

Fair 100 Ref

Good 122 (099 151) 0063 098 (068 141) 0900

Specific chronic conditions

Hypertension 095 (081 111) 0492 082 (061 111) 0195

Dyslipidemia 124 (099 156) 0061 101 (071 143) 0959

Diabetes 113 (086 148) 0374 176 (115 270) 0009

Chronic lung diseases 087 (071 105) 0155 098 (065 147) 0906

Heart diseases 140 (115 170) 0001 124 (087 176) 0228

Kidney disease 081 (064 102) 0073 070 (044 112) 0138

Stomach diseases 088 (077 102) 0087 093 (068 128) 0662

Arthritis or rheumatism 083 (072 095) 0006 089 (066 120) 0442

Other major chronic diseases 088 (073 106) 0192 064 (044 091) 0015

Functional limitations

None 100 Ref 100 Ref

Mild 093 (079 110) 0401 106 (073 154) 0745

Moderate 102 (076 135) 0907 119 (057 246) 0643

Severe 144 (095 217) 0085 154 (055 432) 0408

Li et al BMC Health Services Research (2021) 21895 Page 7 of 12

upper-middle income category (OR = 069 p = 0018)Rural patients enrolled in Urban Employee Basic Med-ical Insurance had three times the odds (OR = 301 p lt0001) of bypassing PHCs than the uninsured Comparedwith the uninsured patients urban patients enrolled inNew Rural Cooperative Medical Scheme had a lowerodds of bypassing (OR = 047 p = 0012)Rural patients with poor health were more likely to by-

pass PHCs than those who reported their health beinglsquofairrsquo (OR = 134 p lt 0001) Patients with heart diseasesin rural areas and urban patients with diabetes had ahigher odds of bypassing PHCs (OR = 140 p = 0001OR = 176 p = 0009) and the opposite was true for ruralpatients with arthritis or rheumatism and patients withother major chronic conditions in urban areas (OR =083 p = 0006 OR = 064 p = 0015) Patients who expe-rienced hospitalization in the past 12 months had ahigher odds of bypassing in both the rural and urbanareas (OR = 208 p lt 0001 OR = 215 p lt 0001) Rela-tive travel time was positively associated with patientsbypassing PHCs in rural and urban areas (OR = 115 p lt0001 OR = 128 p lt 0001)Table 3 presents factors affecting bypassing PHCs

when only the first contact outpatient visits are used inthe estimation The results are similar to the estimatesobtained when all visits including the revisits were usedin the analysis

DiscussionThe nationally representative survey indicates that theproportion of outpatients bypassing PHCs increased overthe years in China Urban patients were nearly twice aslikely to bypass PHCs than rural patients This is not un-expected due to the easy access and availability of manySTFs in urban areas Travel distance and travel-relatedcosts are likely to be lower for the urban population [3642] Rural patients often must rely on PHCs in the areadue to the difficulty of accessing alternative health careproviders Especially for rural residents obtaining carefrom upper-level facilities may become quite expensivedue to higher out-of-pocket expenses and longer traveltimes [43]About two in five older adults in China bypassed

PHCs to obtain care from upper-level providers (STFs)

This is despite significantly lower out-of-pocket costs forservices and drugs at PHCs than at the STFs Thereforefinancial incentives have not been adequate to discour-age bypassing of PHCs in China The results imply thatpropensity to bypass PHCs is unlikely to decline signifi-cantly if the financial incentives in favor of PHCs aremade even stronger Given that the bypassing tendencyis related to age ruralurban location present of chronicconditions etc it points to supply-side concerns prob-ably related to availability and quality of service-mix of-fered at the PHCsThe random-effects logistic regression model identi-

fied several factors affecting bypassing of PHCs for ruraland urban residents separately The estimates suggestthat factors affecting the first visits are very similar tofactors affecting all outpatient visits (both new andfollow-up visits) implying that physician recommenda-tions were not important in influencing the choice offacility-types Regardless of rural-urban residence a rela-tive increase in travel time (ratio of travel times to PHCand STF) increased the probability of bypassing PHCsThe result is consistent with the findings in the litera-ture ie increased travel time lowers the utilization ofhealth care facilities [33 44ndash50] Without a formal refer-ral system in urban areas where health resources aremuch richer and STFs are more concentrated than thosein rural areas in China urban patients are more likely tobypass PHCs because of easy accessibility and availabilityof medical care services they needPatients with higher educational attainment show a

higher probability of bypassing PHCs Educational at-tainment is an indicator of socioeconomic status (SES)as well as knowledge about the relative quality of ser-vices facilities offer Middle-aged and older adults withhigher level of income are also more likely to bypassPHCs This probably indicates perception of lower qual-ity of services at the PHCs compared to the STFs Withan increase in income and educational attainment pa-tients become more sensitive to service quality and lesssensitive to cost savings that can be achieved by utilizingPHCsIn rural areas self-reported poor health status in-

creased the likelihood of bypassing PHCs Again thispossibly reflects a lack of confidence in the quality of

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 208 (177 245) lt 0001 215 (153 302) lt 0001

Relative travel time 115 (113 117) lt 0001 128 (118 139) lt 0001

Constant 025 (017 038) lt 0001 063 (030 130) 0207

Observations 7672 2389

Li et al BMC Health Services Research (2021) 21895 Page 8 of 12

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 108 (085 139) 0488 102 (069 150) 0932

ge 65 091 (068 121) 0509 171 (107 273) 0024

Male 103 (084 129) 0727 100 (071 140) 0998

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 121 (095 155) 0120 169 (100 285) 0050

Middle school 162 (117 224) 0004 216 (121 385) 0009

High school 189 (116 306) 0010 252 (134 476) 0004

gt three-years of college 556 (097 3181) 0054 294 (126 686) 0013

Married 107 (078 147) 0681 102 (063 165) 0936

Household income

Low income 104 (077 140) 0808 101 (064 160) 0959

Lower middle income 102 (076 136) 0921 063 (036 111) 0110

Upper middle income 111 (083 148) 0498 073 (049 109) 0129

High income 100 Ref 100 Ref

Medical insurance

UEMI 153 (062 375) 0354 155 (076 316) 0227

URMI 284 (090 896) 0075 140 (065 302) 0387

NRCMI 086 (054 136) 0517 058 (028 119) 0136

Other Insurance 110 (033 217) 0726 086 (044 168) 0664

No Insurance 084 Ref 100 Ref

Health status

Poor 159 (125 202) lt 0001 103 (069 156) 0872

Fair 100 Ref

Good 134 (099 181) 0056 099 (065 151) 0972

Specific chronic conditions

Hypertension 102 (079 131) 0897 093 (063 137) 0705

Dyslipidemia 163 (112 237) 0010 094 (060 147) 0778

Diabetes 093 (057 150) 0758 196 (100 383) 0049

Chronic lung diseases 096 (070 131) 0790 104 (061 180) 0876

Heart diseases 120 (086 168) 0291 140 (087 225) 0172

Kidney disease 059 (039 089) 0013 067 (036 125) 0210

Stomach diseases 088 (070 111) 0281 102 (070 150) 0911

Arthritis or rheumatism 079 (064 098) 0035 096 (067 137) 0807

Other major chronic diseases 088 (064 120) 0413 063 (037 105) 0075

Functional limitations

None 100 Ref 100 Ref

Mild 106 (080 141) 0662 107 (065 177) 0783

Moderate 147 (092 234) 0107 169 (049 587) 0410

Severe 191 (082 446) 0133 152 (031 744) 0603

Li et al BMC Health Services Research (2021) 21895 Page 9 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

P PHCeth THORN frac14 P yit frac14 1eth j X 0itZ

0it C

0it T

0it α β γ θ μi

frac14 eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

1thorn eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

P yit frac14 0eth j X 0it Z

0it C

0it T

0it α β γ θ μi

frac14 1

1thorn eμithornX0itαthornZ

0itβthornC

0itγthornT

0itθ

Furthermore the present study assumes that μi is notrelated to the covariates Correlation between μi and thecovariates would indicate a fixed-effects model [37]

Data sourceThe China Health and Retirement Longitudinal Study(CHARLS) conducted by the National School of Devel-opment of Peking University is the data set used for thisanalysis The sample of CHARLS was drawn from 450villages or urban communities of 150 counties or equiva-lent urban districts in 28 provinces A multistage strati-fied sampling with probability proportional to size wasused for the survey More details on the sampling anddata collection process are available in Zhao et al [38]The CHARLS is nationally representative and collectsdata from persons of age 45 years or older and theirspouses The CHARLS respondents are reinterviewedevery 2 years with the first wave in 2011 covering17705 persons and two follow-ups in 2013 and 2015with 18605 persons and 21095 persons respectivelyThe CHARLS questionnaires include questions onhousehold characteristics demographic backgroundhealth status and physical functioning health careutilization insurance status work retirement and pen-sion income expenditure asset ownership housingcharacteristics etc From the datasets only the individ-uals who sought outpatient care during the previous 4weeks before the date of interview were selected Thefinal sample consisted of a total of 10061 individuals inall three waves combined

MeasuresRural and urban definitionsIn the CHARLS each adult was asked ldquoWhat is the typeof your addressrdquo and ldquoIs it a rural village or urban com-munityrdquo All respondents were classified as either ruralor urban residents based on their responses

Dependent variableThe PHCs in China provide generalist clinical care andbasic public health services through community healthcenters and clinics in the urban areas and township hos-pitals and village clinics in the rural areas [13 39] Inthis study bypassing PHCs has been defined as skippingany primary care facilities to obtain care from the

secondary or tertiary level Responses to the followingsurvey questions were used to identify the incidence ofldquobypassingrdquo (1) Which healthcare provider did you visitmost recently during the past 4 weeks 1 General hos-pital 2 Specialized hospital 3 Chinese medicine hos-pital 4 Community healthcare center 5 Townshiphospital 6 Community health clinic 7 Village clinicPrivate clinic and 8 Other and (2) Did the providervisit you at home 1 Yes and 2 No If a respondent an-swered Question (1) by selecting any of General hospitalSpecialized hospital or Chinese medicine hospital andreported ldquoNordquo on Question (2) the patient is consideredto have had a ldquobypassingrdquo of the PHC The respondentswho reported using ldquoOtherrdquo providers in Question (1) orldquoYesrdquo to Question (2) were dropped from this studysample

Independent variablesIndependent variables were chosen based on theoreticalconsiderations and literature review The survey col-lected data on travel time to the facility for each of thepatients Therefore those who obtained care from PHCsreported travel time to the PHCs while those who vis-ited the upper-level facilities (STFs) reported travel timeto those facilities Reported travel times to facility-types(PHCs or STFs) were used to predict the travel times toPHCs and STFs for all patients living in a communitybut did not visit the facility-type The average travel timeto PHCs for patients living in a community for examplewas used to approximate the travel time of those livingin the same community but did not use the PHCs Thesame method was used to predict the travel time fromhome to an STF for patients in each community Rela-tive travel time was defined as the ratio of travel time toa PHC to travel time to an STFChina has two basic medical insurance schemes

Urban Employee Basic Medical Insurance and Urbanand Rural Resident Basic Medical Insurance (the medicalinsurance of integrating Urban Resident Basic MedicalInsurance and New Rural Cooperative Medical Schemeofficially in 2016) Insurance status affects out-of-pocketexpenses of patients differentially for seeking care fromPHCs and STFs Another critical factor affecting bypass-ing is patientsrsquo medical conditions especially the pres-ence of chronic conditions This analysis included anextensive list of chronic conditions including hyperten-sion dyslipidemia diabetes cancer chronic lung dis-eases liver disease heart diseases stroke emotionalnervous or psychiatric problems Definitions of the vari-ables are given in Table 1

Data analysisThis analysis is based on a sample of 10061 respon-dents who sought outpatient care during the 4 weeks

Li et al BMC Health Services Research (2021) 21895 Page 4 of 12

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015

Variable Description

Dependent variable

Bypassing 1 if a patient bypasses primary health center (PHC) to seek care from a higher-tier facility (secondary or tertiary facilities)0 otherwise

Independent variable

Age (years)

45ndash54 1 if the individual is aged 45ndash54 years 0 otherwise

55ndash64 1 if the individual is aged 55ndash64 years 0 otherwise

ge 65 1 if the individual is aged ge65 years 0 otherwise

Male 1 if the individual is male 0 for female

Educational attainment

Illiterate 1 if the individual is illiterate 0 otherwise

Elementary school 1 if the individual attended elementary school 0 otherwise

Middle school 1 if the individual graduated from middle school 0 otherwise

High school 1 if the individual graduated from high school 0 otherwise

Above three-years ofcollege

1 if the individual had above three-years of college 0 otherwise

Married 1 if the individual is married 0 otherwise

Household income

Low income 1 if the individualrsquos household income is in the first quartile 0 otherwise

Lower middle income 1 if the individualrsquos household income is in second quartile 0 otherwise

Upper middle income 1 if the individualrsquos household income is in the third quartile 0 otherwise

High income 1 if the individualrsquos household income is in the highest quartile 0 otherwise

Medical insurance

UEMI 1 if the individual is enrolled in Urban Employee Medical Insurance 0 otherwise

URMI 1 if the individual is enrolled in Urban Resident Medical Insurance 0 otherwise

NRCMI 1 if the individual is enrolled in New Rural Cooperative Medical Insurance 0 otherwise

Other Insurance 1 if the individual is enrolled in Government Medical Insurance Urban and Rural has either Resident Medical InsurancePrivate Medical Insurance Medical Aid or Other medical insurance 0 otherwise

No Insurance 1 if the individual does not have medical insurance 0 otherwise

Health status

Poor 1 if the individual reports health status to be poor 0 otherwise

Fair 1 if the individual reports health status to be fair 0 otherwise

Good 1 if the individual reports health status to be good or better 0 otherwise

Specific chronic conditions

Hypertension 1 if the individual has hypertension 0 otherwise

Dyslipidemia 1 if the individual has dyslipidemia 0 otherwise

Diabetes 1 if the individual has diabetes or high blood sugar 0 otherwise

Chronic lung diseases 1 if the individual has chronic lung diseases 0 otherwise

Heart diseases 1 if the individual has heart diseases 0 otherwise

Kidney disease 1 if the individual has kidney disease 0 otherwise

Stomach diseases 1 if the individual has stomach or other digestive diseases 0 otherwise

Arthritis orrheumatism

1 if the individual has arthritis or rheumatism 0 otherwise

Other major chronic 1 if the individual has cancer or malignant tumor liver disease stroke emotional nervous or psychiatric problems

Li et al BMC Health Services Research (2021) 21895 Page 5 of 12

prior to the survey date Since follow-up visits maybias the results this study has estimated the modelsseparately for all visits (first visit and revisits) and thefirst visits The sample size for first visits for an epi-sode of illness was 4720 If the primary care providersin the first visits refer patients to specialists the sub-sequent visits may reflect physician recommendationsrather than patientsrsquo decision-making In other wordsat least some of the revisits may not be consideredbypassing of the PHCsLogistic regression models were employed to analyze

factors affecting propensity to bypass PHCs stratified byrural-urban residence Since access to health facilitiesdiffers significantly between rural and urban areas thestratification is important to avoid potential bias createdby rural-urban differences (see Table A1 of Additionalfile 1) The annex table also identifies a number of rele-vant variables for inclusion in the regression models Inmost panel studies the preferred empirical model wouldbe either the fixed-effects or the random-effects logisticmodel [37] and empirical results should guide the choicebetween the model-typesWhen estimating the patient fixed effects model

whenever patients bypass (or do not bypass) PHC in twowaves or all three waves by definition variations overtime becomes zero and the empirical model will dropthe cases In the full sample of the fixed effects logisticmodels 6620 out of 7672 rural patients and 2185 out of2389 urban patients were dropped because of lack ofinter-temporal variation The random-effects model usesall the available observations and allows estimation ofparameters and standard errors [40] This study usedHausmanrsquos specification test for the random effects lo-gistic regression models to test the orthogonality of therandom effects and the regressors [41] The Hausmantest suggests that the random-effects model is preferredover the fixed-effects model

ResultsAmong those who used outpatient services the percentof patients bypassing PHCs were 340 in Wave 1394 in Wave 2 and 418 in Wave 3 indicating an in-creasing trend of bypassing over the years In rural areasthe percent bypassing PHCs were 270 in Wave 1330 in Wave 2 and 346 in Wave 3 In contrast thepropensity to bypass PHCs remained almost static inurban areas over the years ndash 624 in Wave 1 611 inWave 2 and 601 in Wave 3 Urban patients werenearly twice as likely as rural patients to bypass PHCsThe results remained similar when only the first visitswere considered ie excluding the follow-up outpatientvisits Table A1 of Additional file 1 compares patientcharacteristics by bypassing behavior (patients bypassingPHCs vs those not bypassing) The results indicate thatbypassers differed from non-bypassers in terms of theirresidence educational attainment household incomemedical insurance coverage specific chronic conditionsand the incidence of hospitalizationThe odds ratios of the random effects logistic regres-

sion analysis are reported in Table 2 The results implythat rural patients aged 65 years or older were less likelyto bypass PHCs than patients in the age group 45ndash54years (OR = 064 p lt 0001) In contrast patients aged65 years or older show a higher probability of bypassingin urban areas (OR = 147 p = 0036) The probability ofbypassing PHCs increases with higher educational at-tainment in both rural and urban areas Compared toilliterate patients individuals who attended elementaryschool show increased odds of bypassing by 22 in ruralareas (OR = 122 p lt 0012) and completion of morethan 3 years of college increased the odds by 236 inurban areas (OR = 336 p lt 0001) Urban patients in thelower-middle income category were less likely to bypassPHCs than those with high income (OR = 056 p =0010) A similar trend was observed for patients in the

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015 (Continued)

Variable Description

diseases memory-related disease or asthma 0 otherwise

Functional limitations

None 1 if the individual can eat toilet dress batheshower get inout of bed and walk without difficulty 0 otherwise

Mild 1 if the individual has one or two difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Moderate 1 if the individual has three or four difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Severe 1 if the individual has five to six difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Hospitalization 1 if the individual reports hospitalization in the past 12 months 0 otherwise

Relative travel time The ratio of travel time to a primary care facility to travel time to a secondary or tertiary level facility for individuals inthe community

Li et al BMC Health Services Research (2021) 21895 Page 6 of 12

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 092 (078 107) 0273 112 (081 154) 0506

ge 65 064 (053 077) lt 0001 147 (103 211) 0036

Male 111 (096 127) 0161 102 (078 135) 0871

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 122 (104 143) 0012 130 (087 194) 0195

Middle school 157 (127 193) lt 0001 197 (127 305) 0002

High school 187 (138 254) lt 0001 282 (173 459) lt 0001

gt three-years of college 176 (051 610) 0373 336 (177 637) lt 0001

Married 109 (089 133) 0397 105 (072 154) 0798

Household income

Low income 084 (069 102) 0081 084 (058 120) 0332

Lower middle income 087 (072 105) 0156 056 (036 087) 0010

Upper middle income 095 (079 115) 0602 069 (050 094) 0018

High income 100 Ref 100 Ref

Medical insurance

UEMI 301 (173 522) lt 0001 152 (087 267) 0140

URMI 149 (072 306) 0283 162 (087 300) 0125

NRCMI 092 (068 124) 0576 047 (026 085) 0012

Other Insurance 110 (060 200) 0775 103 (059 178) 0929

No Insurance 100 Ref 100 Ref

Health status

Poor 134 (116 154) lt 0001 128 (094 173) 0113

Fair 100 Ref

Good 122 (099 151) 0063 098 (068 141) 0900

Specific chronic conditions

Hypertension 095 (081 111) 0492 082 (061 111) 0195

Dyslipidemia 124 (099 156) 0061 101 (071 143) 0959

Diabetes 113 (086 148) 0374 176 (115 270) 0009

Chronic lung diseases 087 (071 105) 0155 098 (065 147) 0906

Heart diseases 140 (115 170) 0001 124 (087 176) 0228

Kidney disease 081 (064 102) 0073 070 (044 112) 0138

Stomach diseases 088 (077 102) 0087 093 (068 128) 0662

Arthritis or rheumatism 083 (072 095) 0006 089 (066 120) 0442

Other major chronic diseases 088 (073 106) 0192 064 (044 091) 0015

Functional limitations

None 100 Ref 100 Ref

Mild 093 (079 110) 0401 106 (073 154) 0745

Moderate 102 (076 135) 0907 119 (057 246) 0643

Severe 144 (095 217) 0085 154 (055 432) 0408

Li et al BMC Health Services Research (2021) 21895 Page 7 of 12

upper-middle income category (OR = 069 p = 0018)Rural patients enrolled in Urban Employee Basic Med-ical Insurance had three times the odds (OR = 301 p lt0001) of bypassing PHCs than the uninsured Comparedwith the uninsured patients urban patients enrolled inNew Rural Cooperative Medical Scheme had a lowerodds of bypassing (OR = 047 p = 0012)Rural patients with poor health were more likely to by-

pass PHCs than those who reported their health beinglsquofairrsquo (OR = 134 p lt 0001) Patients with heart diseasesin rural areas and urban patients with diabetes had ahigher odds of bypassing PHCs (OR = 140 p = 0001OR = 176 p = 0009) and the opposite was true for ruralpatients with arthritis or rheumatism and patients withother major chronic conditions in urban areas (OR =083 p = 0006 OR = 064 p = 0015) Patients who expe-rienced hospitalization in the past 12 months had ahigher odds of bypassing in both the rural and urbanareas (OR = 208 p lt 0001 OR = 215 p lt 0001) Rela-tive travel time was positively associated with patientsbypassing PHCs in rural and urban areas (OR = 115 p lt0001 OR = 128 p lt 0001)Table 3 presents factors affecting bypassing PHCs

when only the first contact outpatient visits are used inthe estimation The results are similar to the estimatesobtained when all visits including the revisits were usedin the analysis

DiscussionThe nationally representative survey indicates that theproportion of outpatients bypassing PHCs increased overthe years in China Urban patients were nearly twice aslikely to bypass PHCs than rural patients This is not un-expected due to the easy access and availability of manySTFs in urban areas Travel distance and travel-relatedcosts are likely to be lower for the urban population [3642] Rural patients often must rely on PHCs in the areadue to the difficulty of accessing alternative health careproviders Especially for rural residents obtaining carefrom upper-level facilities may become quite expensivedue to higher out-of-pocket expenses and longer traveltimes [43]About two in five older adults in China bypassed

PHCs to obtain care from upper-level providers (STFs)

This is despite significantly lower out-of-pocket costs forservices and drugs at PHCs than at the STFs Thereforefinancial incentives have not been adequate to discour-age bypassing of PHCs in China The results imply thatpropensity to bypass PHCs is unlikely to decline signifi-cantly if the financial incentives in favor of PHCs aremade even stronger Given that the bypassing tendencyis related to age ruralurban location present of chronicconditions etc it points to supply-side concerns prob-ably related to availability and quality of service-mix of-fered at the PHCsThe random-effects logistic regression model identi-

fied several factors affecting bypassing of PHCs for ruraland urban residents separately The estimates suggestthat factors affecting the first visits are very similar tofactors affecting all outpatient visits (both new andfollow-up visits) implying that physician recommenda-tions were not important in influencing the choice offacility-types Regardless of rural-urban residence a rela-tive increase in travel time (ratio of travel times to PHCand STF) increased the probability of bypassing PHCsThe result is consistent with the findings in the litera-ture ie increased travel time lowers the utilization ofhealth care facilities [33 44ndash50] Without a formal refer-ral system in urban areas where health resources aremuch richer and STFs are more concentrated than thosein rural areas in China urban patients are more likely tobypass PHCs because of easy accessibility and availabilityof medical care services they needPatients with higher educational attainment show a

higher probability of bypassing PHCs Educational at-tainment is an indicator of socioeconomic status (SES)as well as knowledge about the relative quality of ser-vices facilities offer Middle-aged and older adults withhigher level of income are also more likely to bypassPHCs This probably indicates perception of lower qual-ity of services at the PHCs compared to the STFs Withan increase in income and educational attainment pa-tients become more sensitive to service quality and lesssensitive to cost savings that can be achieved by utilizingPHCsIn rural areas self-reported poor health status in-

creased the likelihood of bypassing PHCs Again thispossibly reflects a lack of confidence in the quality of

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 208 (177 245) lt 0001 215 (153 302) lt 0001

Relative travel time 115 (113 117) lt 0001 128 (118 139) lt 0001

Constant 025 (017 038) lt 0001 063 (030 130) 0207

Observations 7672 2389

Li et al BMC Health Services Research (2021) 21895 Page 8 of 12

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 108 (085 139) 0488 102 (069 150) 0932

ge 65 091 (068 121) 0509 171 (107 273) 0024

Male 103 (084 129) 0727 100 (071 140) 0998

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 121 (095 155) 0120 169 (100 285) 0050

Middle school 162 (117 224) 0004 216 (121 385) 0009

High school 189 (116 306) 0010 252 (134 476) 0004

gt three-years of college 556 (097 3181) 0054 294 (126 686) 0013

Married 107 (078 147) 0681 102 (063 165) 0936

Household income

Low income 104 (077 140) 0808 101 (064 160) 0959

Lower middle income 102 (076 136) 0921 063 (036 111) 0110

Upper middle income 111 (083 148) 0498 073 (049 109) 0129

High income 100 Ref 100 Ref

Medical insurance

UEMI 153 (062 375) 0354 155 (076 316) 0227

URMI 284 (090 896) 0075 140 (065 302) 0387

NRCMI 086 (054 136) 0517 058 (028 119) 0136

Other Insurance 110 (033 217) 0726 086 (044 168) 0664

No Insurance 084 Ref 100 Ref

Health status

Poor 159 (125 202) lt 0001 103 (069 156) 0872

Fair 100 Ref

Good 134 (099 181) 0056 099 (065 151) 0972

Specific chronic conditions

Hypertension 102 (079 131) 0897 093 (063 137) 0705

Dyslipidemia 163 (112 237) 0010 094 (060 147) 0778

Diabetes 093 (057 150) 0758 196 (100 383) 0049

Chronic lung diseases 096 (070 131) 0790 104 (061 180) 0876

Heart diseases 120 (086 168) 0291 140 (087 225) 0172

Kidney disease 059 (039 089) 0013 067 (036 125) 0210

Stomach diseases 088 (070 111) 0281 102 (070 150) 0911

Arthritis or rheumatism 079 (064 098) 0035 096 (067 137) 0807

Other major chronic diseases 088 (064 120) 0413 063 (037 105) 0075

Functional limitations

None 100 Ref 100 Ref

Mild 106 (080 141) 0662 107 (065 177) 0783

Moderate 147 (092 234) 0107 169 (049 587) 0410

Severe 191 (082 446) 0133 152 (031 744) 0603

Li et al BMC Health Services Research (2021) 21895 Page 9 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015

Variable Description

Dependent variable

Bypassing 1 if a patient bypasses primary health center (PHC) to seek care from a higher-tier facility (secondary or tertiary facilities)0 otherwise

Independent variable

Age (years)

45ndash54 1 if the individual is aged 45ndash54 years 0 otherwise

55ndash64 1 if the individual is aged 55ndash64 years 0 otherwise

ge 65 1 if the individual is aged ge65 years 0 otherwise

Male 1 if the individual is male 0 for female

Educational attainment

Illiterate 1 if the individual is illiterate 0 otherwise

Elementary school 1 if the individual attended elementary school 0 otherwise

Middle school 1 if the individual graduated from middle school 0 otherwise

High school 1 if the individual graduated from high school 0 otherwise

Above three-years ofcollege

1 if the individual had above three-years of college 0 otherwise

Married 1 if the individual is married 0 otherwise

Household income

Low income 1 if the individualrsquos household income is in the first quartile 0 otherwise

Lower middle income 1 if the individualrsquos household income is in second quartile 0 otherwise

Upper middle income 1 if the individualrsquos household income is in the third quartile 0 otherwise

High income 1 if the individualrsquos household income is in the highest quartile 0 otherwise

Medical insurance

UEMI 1 if the individual is enrolled in Urban Employee Medical Insurance 0 otherwise

URMI 1 if the individual is enrolled in Urban Resident Medical Insurance 0 otherwise

NRCMI 1 if the individual is enrolled in New Rural Cooperative Medical Insurance 0 otherwise

Other Insurance 1 if the individual is enrolled in Government Medical Insurance Urban and Rural has either Resident Medical InsurancePrivate Medical Insurance Medical Aid or Other medical insurance 0 otherwise

No Insurance 1 if the individual does not have medical insurance 0 otherwise

Health status

Poor 1 if the individual reports health status to be poor 0 otherwise

Fair 1 if the individual reports health status to be fair 0 otherwise

Good 1 if the individual reports health status to be good or better 0 otherwise

Specific chronic conditions

Hypertension 1 if the individual has hypertension 0 otherwise

Dyslipidemia 1 if the individual has dyslipidemia 0 otherwise

Diabetes 1 if the individual has diabetes or high blood sugar 0 otherwise

Chronic lung diseases 1 if the individual has chronic lung diseases 0 otherwise

Heart diseases 1 if the individual has heart diseases 0 otherwise

Kidney disease 1 if the individual has kidney disease 0 otherwise

Stomach diseases 1 if the individual has stomach or other digestive diseases 0 otherwise

Arthritis orrheumatism

1 if the individual has arthritis or rheumatism 0 otherwise

Other major chronic 1 if the individual has cancer or malignant tumor liver disease stroke emotional nervous or psychiatric problems

Li et al BMC Health Services Research (2021) 21895 Page 5 of 12

prior to the survey date Since follow-up visits maybias the results this study has estimated the modelsseparately for all visits (first visit and revisits) and thefirst visits The sample size for first visits for an epi-sode of illness was 4720 If the primary care providersin the first visits refer patients to specialists the sub-sequent visits may reflect physician recommendationsrather than patientsrsquo decision-making In other wordsat least some of the revisits may not be consideredbypassing of the PHCsLogistic regression models were employed to analyze

factors affecting propensity to bypass PHCs stratified byrural-urban residence Since access to health facilitiesdiffers significantly between rural and urban areas thestratification is important to avoid potential bias createdby rural-urban differences (see Table A1 of Additionalfile 1) The annex table also identifies a number of rele-vant variables for inclusion in the regression models Inmost panel studies the preferred empirical model wouldbe either the fixed-effects or the random-effects logisticmodel [37] and empirical results should guide the choicebetween the model-typesWhen estimating the patient fixed effects model

whenever patients bypass (or do not bypass) PHC in twowaves or all three waves by definition variations overtime becomes zero and the empirical model will dropthe cases In the full sample of the fixed effects logisticmodels 6620 out of 7672 rural patients and 2185 out of2389 urban patients were dropped because of lack ofinter-temporal variation The random-effects model usesall the available observations and allows estimation ofparameters and standard errors [40] This study usedHausmanrsquos specification test for the random effects lo-gistic regression models to test the orthogonality of therandom effects and the regressors [41] The Hausmantest suggests that the random-effects model is preferredover the fixed-effects model

ResultsAmong those who used outpatient services the percentof patients bypassing PHCs were 340 in Wave 1394 in Wave 2 and 418 in Wave 3 indicating an in-creasing trend of bypassing over the years In rural areasthe percent bypassing PHCs were 270 in Wave 1330 in Wave 2 and 346 in Wave 3 In contrast thepropensity to bypass PHCs remained almost static inurban areas over the years ndash 624 in Wave 1 611 inWave 2 and 601 in Wave 3 Urban patients werenearly twice as likely as rural patients to bypass PHCsThe results remained similar when only the first visitswere considered ie excluding the follow-up outpatientvisits Table A1 of Additional file 1 compares patientcharacteristics by bypassing behavior (patients bypassingPHCs vs those not bypassing) The results indicate thatbypassers differed from non-bypassers in terms of theirresidence educational attainment household incomemedical insurance coverage specific chronic conditionsand the incidence of hospitalizationThe odds ratios of the random effects logistic regres-

sion analysis are reported in Table 2 The results implythat rural patients aged 65 years or older were less likelyto bypass PHCs than patients in the age group 45ndash54years (OR = 064 p lt 0001) In contrast patients aged65 years or older show a higher probability of bypassingin urban areas (OR = 147 p = 0036) The probability ofbypassing PHCs increases with higher educational at-tainment in both rural and urban areas Compared toilliterate patients individuals who attended elementaryschool show increased odds of bypassing by 22 in ruralareas (OR = 122 p lt 0012) and completion of morethan 3 years of college increased the odds by 236 inurban areas (OR = 336 p lt 0001) Urban patients in thelower-middle income category were less likely to bypassPHCs than those with high income (OR = 056 p =0010) A similar trend was observed for patients in the

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015 (Continued)

Variable Description

diseases memory-related disease or asthma 0 otherwise

Functional limitations

None 1 if the individual can eat toilet dress batheshower get inout of bed and walk without difficulty 0 otherwise

Mild 1 if the individual has one or two difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Moderate 1 if the individual has three or four difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Severe 1 if the individual has five to six difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Hospitalization 1 if the individual reports hospitalization in the past 12 months 0 otherwise

Relative travel time The ratio of travel time to a primary care facility to travel time to a secondary or tertiary level facility for individuals inthe community

Li et al BMC Health Services Research (2021) 21895 Page 6 of 12

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 092 (078 107) 0273 112 (081 154) 0506

ge 65 064 (053 077) lt 0001 147 (103 211) 0036

Male 111 (096 127) 0161 102 (078 135) 0871

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 122 (104 143) 0012 130 (087 194) 0195

Middle school 157 (127 193) lt 0001 197 (127 305) 0002

High school 187 (138 254) lt 0001 282 (173 459) lt 0001

gt three-years of college 176 (051 610) 0373 336 (177 637) lt 0001

Married 109 (089 133) 0397 105 (072 154) 0798

Household income

Low income 084 (069 102) 0081 084 (058 120) 0332

Lower middle income 087 (072 105) 0156 056 (036 087) 0010

Upper middle income 095 (079 115) 0602 069 (050 094) 0018

High income 100 Ref 100 Ref

Medical insurance

UEMI 301 (173 522) lt 0001 152 (087 267) 0140

URMI 149 (072 306) 0283 162 (087 300) 0125

NRCMI 092 (068 124) 0576 047 (026 085) 0012

Other Insurance 110 (060 200) 0775 103 (059 178) 0929

No Insurance 100 Ref 100 Ref

Health status

Poor 134 (116 154) lt 0001 128 (094 173) 0113

Fair 100 Ref

Good 122 (099 151) 0063 098 (068 141) 0900

Specific chronic conditions

Hypertension 095 (081 111) 0492 082 (061 111) 0195

Dyslipidemia 124 (099 156) 0061 101 (071 143) 0959

Diabetes 113 (086 148) 0374 176 (115 270) 0009

Chronic lung diseases 087 (071 105) 0155 098 (065 147) 0906

Heart diseases 140 (115 170) 0001 124 (087 176) 0228

Kidney disease 081 (064 102) 0073 070 (044 112) 0138

Stomach diseases 088 (077 102) 0087 093 (068 128) 0662

Arthritis or rheumatism 083 (072 095) 0006 089 (066 120) 0442

Other major chronic diseases 088 (073 106) 0192 064 (044 091) 0015

Functional limitations

None 100 Ref 100 Ref

Mild 093 (079 110) 0401 106 (073 154) 0745

Moderate 102 (076 135) 0907 119 (057 246) 0643

Severe 144 (095 217) 0085 154 (055 432) 0408

Li et al BMC Health Services Research (2021) 21895 Page 7 of 12

upper-middle income category (OR = 069 p = 0018)Rural patients enrolled in Urban Employee Basic Med-ical Insurance had three times the odds (OR = 301 p lt0001) of bypassing PHCs than the uninsured Comparedwith the uninsured patients urban patients enrolled inNew Rural Cooperative Medical Scheme had a lowerodds of bypassing (OR = 047 p = 0012)Rural patients with poor health were more likely to by-

pass PHCs than those who reported their health beinglsquofairrsquo (OR = 134 p lt 0001) Patients with heart diseasesin rural areas and urban patients with diabetes had ahigher odds of bypassing PHCs (OR = 140 p = 0001OR = 176 p = 0009) and the opposite was true for ruralpatients with arthritis or rheumatism and patients withother major chronic conditions in urban areas (OR =083 p = 0006 OR = 064 p = 0015) Patients who expe-rienced hospitalization in the past 12 months had ahigher odds of bypassing in both the rural and urbanareas (OR = 208 p lt 0001 OR = 215 p lt 0001) Rela-tive travel time was positively associated with patientsbypassing PHCs in rural and urban areas (OR = 115 p lt0001 OR = 128 p lt 0001)Table 3 presents factors affecting bypassing PHCs

when only the first contact outpatient visits are used inthe estimation The results are similar to the estimatesobtained when all visits including the revisits were usedin the analysis

DiscussionThe nationally representative survey indicates that theproportion of outpatients bypassing PHCs increased overthe years in China Urban patients were nearly twice aslikely to bypass PHCs than rural patients This is not un-expected due to the easy access and availability of manySTFs in urban areas Travel distance and travel-relatedcosts are likely to be lower for the urban population [3642] Rural patients often must rely on PHCs in the areadue to the difficulty of accessing alternative health careproviders Especially for rural residents obtaining carefrom upper-level facilities may become quite expensivedue to higher out-of-pocket expenses and longer traveltimes [43]About two in five older adults in China bypassed

PHCs to obtain care from upper-level providers (STFs)

This is despite significantly lower out-of-pocket costs forservices and drugs at PHCs than at the STFs Thereforefinancial incentives have not been adequate to discour-age bypassing of PHCs in China The results imply thatpropensity to bypass PHCs is unlikely to decline signifi-cantly if the financial incentives in favor of PHCs aremade even stronger Given that the bypassing tendencyis related to age ruralurban location present of chronicconditions etc it points to supply-side concerns prob-ably related to availability and quality of service-mix of-fered at the PHCsThe random-effects logistic regression model identi-

fied several factors affecting bypassing of PHCs for ruraland urban residents separately The estimates suggestthat factors affecting the first visits are very similar tofactors affecting all outpatient visits (both new andfollow-up visits) implying that physician recommenda-tions were not important in influencing the choice offacility-types Regardless of rural-urban residence a rela-tive increase in travel time (ratio of travel times to PHCand STF) increased the probability of bypassing PHCsThe result is consistent with the findings in the litera-ture ie increased travel time lowers the utilization ofhealth care facilities [33 44ndash50] Without a formal refer-ral system in urban areas where health resources aremuch richer and STFs are more concentrated than thosein rural areas in China urban patients are more likely tobypass PHCs because of easy accessibility and availabilityof medical care services they needPatients with higher educational attainment show a

higher probability of bypassing PHCs Educational at-tainment is an indicator of socioeconomic status (SES)as well as knowledge about the relative quality of ser-vices facilities offer Middle-aged and older adults withhigher level of income are also more likely to bypassPHCs This probably indicates perception of lower qual-ity of services at the PHCs compared to the STFs Withan increase in income and educational attainment pa-tients become more sensitive to service quality and lesssensitive to cost savings that can be achieved by utilizingPHCsIn rural areas self-reported poor health status in-

creased the likelihood of bypassing PHCs Again thispossibly reflects a lack of confidence in the quality of

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 208 (177 245) lt 0001 215 (153 302) lt 0001

Relative travel time 115 (113 117) lt 0001 128 (118 139) lt 0001

Constant 025 (017 038) lt 0001 063 (030 130) 0207

Observations 7672 2389

Li et al BMC Health Services Research (2021) 21895 Page 8 of 12

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 108 (085 139) 0488 102 (069 150) 0932

ge 65 091 (068 121) 0509 171 (107 273) 0024

Male 103 (084 129) 0727 100 (071 140) 0998

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 121 (095 155) 0120 169 (100 285) 0050

Middle school 162 (117 224) 0004 216 (121 385) 0009

High school 189 (116 306) 0010 252 (134 476) 0004

gt three-years of college 556 (097 3181) 0054 294 (126 686) 0013

Married 107 (078 147) 0681 102 (063 165) 0936

Household income

Low income 104 (077 140) 0808 101 (064 160) 0959

Lower middle income 102 (076 136) 0921 063 (036 111) 0110

Upper middle income 111 (083 148) 0498 073 (049 109) 0129

High income 100 Ref 100 Ref

Medical insurance

UEMI 153 (062 375) 0354 155 (076 316) 0227

URMI 284 (090 896) 0075 140 (065 302) 0387

NRCMI 086 (054 136) 0517 058 (028 119) 0136

Other Insurance 110 (033 217) 0726 086 (044 168) 0664

No Insurance 084 Ref 100 Ref

Health status

Poor 159 (125 202) lt 0001 103 (069 156) 0872

Fair 100 Ref

Good 134 (099 181) 0056 099 (065 151) 0972

Specific chronic conditions

Hypertension 102 (079 131) 0897 093 (063 137) 0705

Dyslipidemia 163 (112 237) 0010 094 (060 147) 0778

Diabetes 093 (057 150) 0758 196 (100 383) 0049

Chronic lung diseases 096 (070 131) 0790 104 (061 180) 0876

Heart diseases 120 (086 168) 0291 140 (087 225) 0172

Kidney disease 059 (039 089) 0013 067 (036 125) 0210

Stomach diseases 088 (070 111) 0281 102 (070 150) 0911

Arthritis or rheumatism 079 (064 098) 0035 096 (067 137) 0807

Other major chronic diseases 088 (064 120) 0413 063 (037 105) 0075

Functional limitations

None 100 Ref 100 Ref

Mild 106 (080 141) 0662 107 (065 177) 0783

Moderate 147 (092 234) 0107 169 (049 587) 0410

Severe 191 (082 446) 0133 152 (031 744) 0603

Li et al BMC Health Services Research (2021) 21895 Page 9 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

prior to the survey date Since follow-up visits maybias the results this study has estimated the modelsseparately for all visits (first visit and revisits) and thefirst visits The sample size for first visits for an epi-sode of illness was 4720 If the primary care providersin the first visits refer patients to specialists the sub-sequent visits may reflect physician recommendationsrather than patientsrsquo decision-making In other wordsat least some of the revisits may not be consideredbypassing of the PHCsLogistic regression models were employed to analyze

factors affecting propensity to bypass PHCs stratified byrural-urban residence Since access to health facilitiesdiffers significantly between rural and urban areas thestratification is important to avoid potential bias createdby rural-urban differences (see Table A1 of Additionalfile 1) The annex table also identifies a number of rele-vant variables for inclusion in the regression models Inmost panel studies the preferred empirical model wouldbe either the fixed-effects or the random-effects logisticmodel [37] and empirical results should guide the choicebetween the model-typesWhen estimating the patient fixed effects model

whenever patients bypass (or do not bypass) PHC in twowaves or all three waves by definition variations overtime becomes zero and the empirical model will dropthe cases In the full sample of the fixed effects logisticmodels 6620 out of 7672 rural patients and 2185 out of2389 urban patients were dropped because of lack ofinter-temporal variation The random-effects model usesall the available observations and allows estimation ofparameters and standard errors [40] This study usedHausmanrsquos specification test for the random effects lo-gistic regression models to test the orthogonality of therandom effects and the regressors [41] The Hausmantest suggests that the random-effects model is preferredover the fixed-effects model

ResultsAmong those who used outpatient services the percentof patients bypassing PHCs were 340 in Wave 1394 in Wave 2 and 418 in Wave 3 indicating an in-creasing trend of bypassing over the years In rural areasthe percent bypassing PHCs were 270 in Wave 1330 in Wave 2 and 346 in Wave 3 In contrast thepropensity to bypass PHCs remained almost static inurban areas over the years ndash 624 in Wave 1 611 inWave 2 and 601 in Wave 3 Urban patients werenearly twice as likely as rural patients to bypass PHCsThe results remained similar when only the first visitswere considered ie excluding the follow-up outpatientvisits Table A1 of Additional file 1 compares patientcharacteristics by bypassing behavior (patients bypassingPHCs vs those not bypassing) The results indicate thatbypassers differed from non-bypassers in terms of theirresidence educational attainment household incomemedical insurance coverage specific chronic conditionsand the incidence of hospitalizationThe odds ratios of the random effects logistic regres-

sion analysis are reported in Table 2 The results implythat rural patients aged 65 years or older were less likelyto bypass PHCs than patients in the age group 45ndash54years (OR = 064 p lt 0001) In contrast patients aged65 years or older show a higher probability of bypassingin urban areas (OR = 147 p = 0036) The probability ofbypassing PHCs increases with higher educational at-tainment in both rural and urban areas Compared toilliterate patients individuals who attended elementaryschool show increased odds of bypassing by 22 in ruralareas (OR = 122 p lt 0012) and completion of morethan 3 years of college increased the odds by 236 inurban areas (OR = 336 p lt 0001) Urban patients in thelower-middle income category were less likely to bypassPHCs than those with high income (OR = 056 p =0010) A similar trend was observed for patients in the

Table 1 Definitions of variables Analysis of Bypassing Primary Health Centers the China Health and Aging Longitudinal Study2011ndash2015 (Continued)

Variable Description

diseases memory-related disease or asthma 0 otherwise

Functional limitations

None 1 if the individual can eat toilet dress batheshower get inout of bed and walk without difficulty 0 otherwise

Mild 1 if the individual has one or two difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Moderate 1 if the individual has three or four difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Severe 1 if the individual has five to six difficulties in eating toileting dressing bathingshowering getting inout of bed orwalking 0 otherwise

Hospitalization 1 if the individual reports hospitalization in the past 12 months 0 otherwise

Relative travel time The ratio of travel time to a primary care facility to travel time to a secondary or tertiary level facility for individuals inthe community

Li et al BMC Health Services Research (2021) 21895 Page 6 of 12

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 092 (078 107) 0273 112 (081 154) 0506

ge 65 064 (053 077) lt 0001 147 (103 211) 0036

Male 111 (096 127) 0161 102 (078 135) 0871

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 122 (104 143) 0012 130 (087 194) 0195

Middle school 157 (127 193) lt 0001 197 (127 305) 0002

High school 187 (138 254) lt 0001 282 (173 459) lt 0001

gt three-years of college 176 (051 610) 0373 336 (177 637) lt 0001

Married 109 (089 133) 0397 105 (072 154) 0798

Household income

Low income 084 (069 102) 0081 084 (058 120) 0332

Lower middle income 087 (072 105) 0156 056 (036 087) 0010

Upper middle income 095 (079 115) 0602 069 (050 094) 0018

High income 100 Ref 100 Ref

Medical insurance

UEMI 301 (173 522) lt 0001 152 (087 267) 0140

URMI 149 (072 306) 0283 162 (087 300) 0125

NRCMI 092 (068 124) 0576 047 (026 085) 0012

Other Insurance 110 (060 200) 0775 103 (059 178) 0929

No Insurance 100 Ref 100 Ref

Health status

Poor 134 (116 154) lt 0001 128 (094 173) 0113

Fair 100 Ref

Good 122 (099 151) 0063 098 (068 141) 0900

Specific chronic conditions

Hypertension 095 (081 111) 0492 082 (061 111) 0195

Dyslipidemia 124 (099 156) 0061 101 (071 143) 0959

Diabetes 113 (086 148) 0374 176 (115 270) 0009

Chronic lung diseases 087 (071 105) 0155 098 (065 147) 0906

Heart diseases 140 (115 170) 0001 124 (087 176) 0228

Kidney disease 081 (064 102) 0073 070 (044 112) 0138

Stomach diseases 088 (077 102) 0087 093 (068 128) 0662

Arthritis or rheumatism 083 (072 095) 0006 089 (066 120) 0442

Other major chronic diseases 088 (073 106) 0192 064 (044 091) 0015

Functional limitations

None 100 Ref 100 Ref

Mild 093 (079 110) 0401 106 (073 154) 0745

Moderate 102 (076 135) 0907 119 (057 246) 0643

Severe 144 (095 217) 0085 154 (055 432) 0408

Li et al BMC Health Services Research (2021) 21895 Page 7 of 12

upper-middle income category (OR = 069 p = 0018)Rural patients enrolled in Urban Employee Basic Med-ical Insurance had three times the odds (OR = 301 p lt0001) of bypassing PHCs than the uninsured Comparedwith the uninsured patients urban patients enrolled inNew Rural Cooperative Medical Scheme had a lowerodds of bypassing (OR = 047 p = 0012)Rural patients with poor health were more likely to by-

pass PHCs than those who reported their health beinglsquofairrsquo (OR = 134 p lt 0001) Patients with heart diseasesin rural areas and urban patients with diabetes had ahigher odds of bypassing PHCs (OR = 140 p = 0001OR = 176 p = 0009) and the opposite was true for ruralpatients with arthritis or rheumatism and patients withother major chronic conditions in urban areas (OR =083 p = 0006 OR = 064 p = 0015) Patients who expe-rienced hospitalization in the past 12 months had ahigher odds of bypassing in both the rural and urbanareas (OR = 208 p lt 0001 OR = 215 p lt 0001) Rela-tive travel time was positively associated with patientsbypassing PHCs in rural and urban areas (OR = 115 p lt0001 OR = 128 p lt 0001)Table 3 presents factors affecting bypassing PHCs

when only the first contact outpatient visits are used inthe estimation The results are similar to the estimatesobtained when all visits including the revisits were usedin the analysis

DiscussionThe nationally representative survey indicates that theproportion of outpatients bypassing PHCs increased overthe years in China Urban patients were nearly twice aslikely to bypass PHCs than rural patients This is not un-expected due to the easy access and availability of manySTFs in urban areas Travel distance and travel-relatedcosts are likely to be lower for the urban population [3642] Rural patients often must rely on PHCs in the areadue to the difficulty of accessing alternative health careproviders Especially for rural residents obtaining carefrom upper-level facilities may become quite expensivedue to higher out-of-pocket expenses and longer traveltimes [43]About two in five older adults in China bypassed

PHCs to obtain care from upper-level providers (STFs)

This is despite significantly lower out-of-pocket costs forservices and drugs at PHCs than at the STFs Thereforefinancial incentives have not been adequate to discour-age bypassing of PHCs in China The results imply thatpropensity to bypass PHCs is unlikely to decline signifi-cantly if the financial incentives in favor of PHCs aremade even stronger Given that the bypassing tendencyis related to age ruralurban location present of chronicconditions etc it points to supply-side concerns prob-ably related to availability and quality of service-mix of-fered at the PHCsThe random-effects logistic regression model identi-

fied several factors affecting bypassing of PHCs for ruraland urban residents separately The estimates suggestthat factors affecting the first visits are very similar tofactors affecting all outpatient visits (both new andfollow-up visits) implying that physician recommenda-tions were not important in influencing the choice offacility-types Regardless of rural-urban residence a rela-tive increase in travel time (ratio of travel times to PHCand STF) increased the probability of bypassing PHCsThe result is consistent with the findings in the litera-ture ie increased travel time lowers the utilization ofhealth care facilities [33 44ndash50] Without a formal refer-ral system in urban areas where health resources aremuch richer and STFs are more concentrated than thosein rural areas in China urban patients are more likely tobypass PHCs because of easy accessibility and availabilityof medical care services they needPatients with higher educational attainment show a

higher probability of bypassing PHCs Educational at-tainment is an indicator of socioeconomic status (SES)as well as knowledge about the relative quality of ser-vices facilities offer Middle-aged and older adults withhigher level of income are also more likely to bypassPHCs This probably indicates perception of lower qual-ity of services at the PHCs compared to the STFs Withan increase in income and educational attainment pa-tients become more sensitive to service quality and lesssensitive to cost savings that can be achieved by utilizingPHCsIn rural areas self-reported poor health status in-

creased the likelihood of bypassing PHCs Again thispossibly reflects a lack of confidence in the quality of

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 208 (177 245) lt 0001 215 (153 302) lt 0001

Relative travel time 115 (113 117) lt 0001 128 (118 139) lt 0001

Constant 025 (017 038) lt 0001 063 (030 130) 0207

Observations 7672 2389

Li et al BMC Health Services Research (2021) 21895 Page 8 of 12

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 108 (085 139) 0488 102 (069 150) 0932

ge 65 091 (068 121) 0509 171 (107 273) 0024

Male 103 (084 129) 0727 100 (071 140) 0998

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 121 (095 155) 0120 169 (100 285) 0050

Middle school 162 (117 224) 0004 216 (121 385) 0009

High school 189 (116 306) 0010 252 (134 476) 0004

gt three-years of college 556 (097 3181) 0054 294 (126 686) 0013

Married 107 (078 147) 0681 102 (063 165) 0936

Household income

Low income 104 (077 140) 0808 101 (064 160) 0959

Lower middle income 102 (076 136) 0921 063 (036 111) 0110

Upper middle income 111 (083 148) 0498 073 (049 109) 0129

High income 100 Ref 100 Ref

Medical insurance

UEMI 153 (062 375) 0354 155 (076 316) 0227

URMI 284 (090 896) 0075 140 (065 302) 0387

NRCMI 086 (054 136) 0517 058 (028 119) 0136

Other Insurance 110 (033 217) 0726 086 (044 168) 0664

No Insurance 084 Ref 100 Ref

Health status

Poor 159 (125 202) lt 0001 103 (069 156) 0872

Fair 100 Ref

Good 134 (099 181) 0056 099 (065 151) 0972

Specific chronic conditions

Hypertension 102 (079 131) 0897 093 (063 137) 0705

Dyslipidemia 163 (112 237) 0010 094 (060 147) 0778

Diabetes 093 (057 150) 0758 196 (100 383) 0049

Chronic lung diseases 096 (070 131) 0790 104 (061 180) 0876

Heart diseases 120 (086 168) 0291 140 (087 225) 0172

Kidney disease 059 (039 089) 0013 067 (036 125) 0210

Stomach diseases 088 (070 111) 0281 102 (070 150) 0911

Arthritis or rheumatism 079 (064 098) 0035 096 (067 137) 0807

Other major chronic diseases 088 (064 120) 0413 063 (037 105) 0075

Functional limitations

None 100 Ref 100 Ref

Mild 106 (080 141) 0662 107 (065 177) 0783

Moderate 147 (092 234) 0107 169 (049 587) 0410

Severe 191 (082 446) 0133 152 (031 744) 0603

Li et al BMC Health Services Research (2021) 21895 Page 9 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 092 (078 107) 0273 112 (081 154) 0506

ge 65 064 (053 077) lt 0001 147 (103 211) 0036

Male 111 (096 127) 0161 102 (078 135) 0871

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 122 (104 143) 0012 130 (087 194) 0195

Middle school 157 (127 193) lt 0001 197 (127 305) 0002

High school 187 (138 254) lt 0001 282 (173 459) lt 0001

gt three-years of college 176 (051 610) 0373 336 (177 637) lt 0001

Married 109 (089 133) 0397 105 (072 154) 0798

Household income

Low income 084 (069 102) 0081 084 (058 120) 0332

Lower middle income 087 (072 105) 0156 056 (036 087) 0010

Upper middle income 095 (079 115) 0602 069 (050 094) 0018

High income 100 Ref 100 Ref

Medical insurance

UEMI 301 (173 522) lt 0001 152 (087 267) 0140

URMI 149 (072 306) 0283 162 (087 300) 0125

NRCMI 092 (068 124) 0576 047 (026 085) 0012

Other Insurance 110 (060 200) 0775 103 (059 178) 0929

No Insurance 100 Ref 100 Ref

Health status

Poor 134 (116 154) lt 0001 128 (094 173) 0113

Fair 100 Ref

Good 122 (099 151) 0063 098 (068 141) 0900

Specific chronic conditions

Hypertension 095 (081 111) 0492 082 (061 111) 0195

Dyslipidemia 124 (099 156) 0061 101 (071 143) 0959

Diabetes 113 (086 148) 0374 176 (115 270) 0009

Chronic lung diseases 087 (071 105) 0155 098 (065 147) 0906

Heart diseases 140 (115 170) 0001 124 (087 176) 0228

Kidney disease 081 (064 102) 0073 070 (044 112) 0138

Stomach diseases 088 (077 102) 0087 093 (068 128) 0662

Arthritis or rheumatism 083 (072 095) 0006 089 (066 120) 0442

Other major chronic diseases 088 (073 106) 0192 064 (044 091) 0015

Functional limitations

None 100 Ref 100 Ref

Mild 093 (079 110) 0401 106 (073 154) 0745

Moderate 102 (076 135) 0907 119 (057 246) 0643

Severe 144 (095 217) 0085 154 (055 432) 0408

Li et al BMC Health Services Research (2021) 21895 Page 7 of 12

upper-middle income category (OR = 069 p = 0018)Rural patients enrolled in Urban Employee Basic Med-ical Insurance had three times the odds (OR = 301 p lt0001) of bypassing PHCs than the uninsured Comparedwith the uninsured patients urban patients enrolled inNew Rural Cooperative Medical Scheme had a lowerodds of bypassing (OR = 047 p = 0012)Rural patients with poor health were more likely to by-

pass PHCs than those who reported their health beinglsquofairrsquo (OR = 134 p lt 0001) Patients with heart diseasesin rural areas and urban patients with diabetes had ahigher odds of bypassing PHCs (OR = 140 p = 0001OR = 176 p = 0009) and the opposite was true for ruralpatients with arthritis or rheumatism and patients withother major chronic conditions in urban areas (OR =083 p = 0006 OR = 064 p = 0015) Patients who expe-rienced hospitalization in the past 12 months had ahigher odds of bypassing in both the rural and urbanareas (OR = 208 p lt 0001 OR = 215 p lt 0001) Rela-tive travel time was positively associated with patientsbypassing PHCs in rural and urban areas (OR = 115 p lt0001 OR = 128 p lt 0001)Table 3 presents factors affecting bypassing PHCs

when only the first contact outpatient visits are used inthe estimation The results are similar to the estimatesobtained when all visits including the revisits were usedin the analysis

DiscussionThe nationally representative survey indicates that theproportion of outpatients bypassing PHCs increased overthe years in China Urban patients were nearly twice aslikely to bypass PHCs than rural patients This is not un-expected due to the easy access and availability of manySTFs in urban areas Travel distance and travel-relatedcosts are likely to be lower for the urban population [3642] Rural patients often must rely on PHCs in the areadue to the difficulty of accessing alternative health careproviders Especially for rural residents obtaining carefrom upper-level facilities may become quite expensivedue to higher out-of-pocket expenses and longer traveltimes [43]About two in five older adults in China bypassed

PHCs to obtain care from upper-level providers (STFs)

This is despite significantly lower out-of-pocket costs forservices and drugs at PHCs than at the STFs Thereforefinancial incentives have not been adequate to discour-age bypassing of PHCs in China The results imply thatpropensity to bypass PHCs is unlikely to decline signifi-cantly if the financial incentives in favor of PHCs aremade even stronger Given that the bypassing tendencyis related to age ruralurban location present of chronicconditions etc it points to supply-side concerns prob-ably related to availability and quality of service-mix of-fered at the PHCsThe random-effects logistic regression model identi-

fied several factors affecting bypassing of PHCs for ruraland urban residents separately The estimates suggestthat factors affecting the first visits are very similar tofactors affecting all outpatient visits (both new andfollow-up visits) implying that physician recommenda-tions were not important in influencing the choice offacility-types Regardless of rural-urban residence a rela-tive increase in travel time (ratio of travel times to PHCand STF) increased the probability of bypassing PHCsThe result is consistent with the findings in the litera-ture ie increased travel time lowers the utilization ofhealth care facilities [33 44ndash50] Without a formal refer-ral system in urban areas where health resources aremuch richer and STFs are more concentrated than thosein rural areas in China urban patients are more likely tobypass PHCs because of easy accessibility and availabilityof medical care services they needPatients with higher educational attainment show a

higher probability of bypassing PHCs Educational at-tainment is an indicator of socioeconomic status (SES)as well as knowledge about the relative quality of ser-vices facilities offer Middle-aged and older adults withhigher level of income are also more likely to bypassPHCs This probably indicates perception of lower qual-ity of services at the PHCs compared to the STFs Withan increase in income and educational attainment pa-tients become more sensitive to service quality and lesssensitive to cost savings that can be achieved by utilizingPHCsIn rural areas self-reported poor health status in-

creased the likelihood of bypassing PHCs Again thispossibly reflects a lack of confidence in the quality of

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 208 (177 245) lt 0001 215 (153 302) lt 0001

Relative travel time 115 (113 117) lt 0001 128 (118 139) lt 0001

Constant 025 (017 038) lt 0001 063 (030 130) 0207

Observations 7672 2389

Li et al BMC Health Services Research (2021) 21895 Page 8 of 12

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 108 (085 139) 0488 102 (069 150) 0932

ge 65 091 (068 121) 0509 171 (107 273) 0024

Male 103 (084 129) 0727 100 (071 140) 0998

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 121 (095 155) 0120 169 (100 285) 0050

Middle school 162 (117 224) 0004 216 (121 385) 0009

High school 189 (116 306) 0010 252 (134 476) 0004

gt three-years of college 556 (097 3181) 0054 294 (126 686) 0013

Married 107 (078 147) 0681 102 (063 165) 0936

Household income

Low income 104 (077 140) 0808 101 (064 160) 0959

Lower middle income 102 (076 136) 0921 063 (036 111) 0110

Upper middle income 111 (083 148) 0498 073 (049 109) 0129

High income 100 Ref 100 Ref

Medical insurance

UEMI 153 (062 375) 0354 155 (076 316) 0227

URMI 284 (090 896) 0075 140 (065 302) 0387

NRCMI 086 (054 136) 0517 058 (028 119) 0136

Other Insurance 110 (033 217) 0726 086 (044 168) 0664

No Insurance 084 Ref 100 Ref

Health status

Poor 159 (125 202) lt 0001 103 (069 156) 0872

Fair 100 Ref

Good 134 (099 181) 0056 099 (065 151) 0972

Specific chronic conditions

Hypertension 102 (079 131) 0897 093 (063 137) 0705

Dyslipidemia 163 (112 237) 0010 094 (060 147) 0778

Diabetes 093 (057 150) 0758 196 (100 383) 0049

Chronic lung diseases 096 (070 131) 0790 104 (061 180) 0876

Heart diseases 120 (086 168) 0291 140 (087 225) 0172

Kidney disease 059 (039 089) 0013 067 (036 125) 0210

Stomach diseases 088 (070 111) 0281 102 (070 150) 0911

Arthritis or rheumatism 079 (064 098) 0035 096 (067 137) 0807

Other major chronic diseases 088 (064 120) 0413 063 (037 105) 0075

Functional limitations

None 100 Ref 100 Ref

Mild 106 (080 141) 0662 107 (065 177) 0783

Moderate 147 (092 234) 0107 169 (049 587) 0410

Severe 191 (082 446) 0133 152 (031 744) 0603

Li et al BMC Health Services Research (2021) 21895 Page 9 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

upper-middle income category (OR = 069 p = 0018)Rural patients enrolled in Urban Employee Basic Med-ical Insurance had three times the odds (OR = 301 p lt0001) of bypassing PHCs than the uninsured Comparedwith the uninsured patients urban patients enrolled inNew Rural Cooperative Medical Scheme had a lowerodds of bypassing (OR = 047 p = 0012)Rural patients with poor health were more likely to by-

pass PHCs than those who reported their health beinglsquofairrsquo (OR = 134 p lt 0001) Patients with heart diseasesin rural areas and urban patients with diabetes had ahigher odds of bypassing PHCs (OR = 140 p = 0001OR = 176 p = 0009) and the opposite was true for ruralpatients with arthritis or rheumatism and patients withother major chronic conditions in urban areas (OR =083 p = 0006 OR = 064 p = 0015) Patients who expe-rienced hospitalization in the past 12 months had ahigher odds of bypassing in both the rural and urbanareas (OR = 208 p lt 0001 OR = 215 p lt 0001) Rela-tive travel time was positively associated with patientsbypassing PHCs in rural and urban areas (OR = 115 p lt0001 OR = 128 p lt 0001)Table 3 presents factors affecting bypassing PHCs

when only the first contact outpatient visits are used inthe estimation The results are similar to the estimatesobtained when all visits including the revisits were usedin the analysis

DiscussionThe nationally representative survey indicates that theproportion of outpatients bypassing PHCs increased overthe years in China Urban patients were nearly twice aslikely to bypass PHCs than rural patients This is not un-expected due to the easy access and availability of manySTFs in urban areas Travel distance and travel-relatedcosts are likely to be lower for the urban population [3642] Rural patients often must rely on PHCs in the areadue to the difficulty of accessing alternative health careproviders Especially for rural residents obtaining carefrom upper-level facilities may become quite expensivedue to higher out-of-pocket expenses and longer traveltimes [43]About two in five older adults in China bypassed

PHCs to obtain care from upper-level providers (STFs)

This is despite significantly lower out-of-pocket costs forservices and drugs at PHCs than at the STFs Thereforefinancial incentives have not been adequate to discour-age bypassing of PHCs in China The results imply thatpropensity to bypass PHCs is unlikely to decline signifi-cantly if the financial incentives in favor of PHCs aremade even stronger Given that the bypassing tendencyis related to age ruralurban location present of chronicconditions etc it points to supply-side concerns prob-ably related to availability and quality of service-mix of-fered at the PHCsThe random-effects logistic regression model identi-

fied several factors affecting bypassing of PHCs for ruraland urban residents separately The estimates suggestthat factors affecting the first visits are very similar tofactors affecting all outpatient visits (both new andfollow-up visits) implying that physician recommenda-tions were not important in influencing the choice offacility-types Regardless of rural-urban residence a rela-tive increase in travel time (ratio of travel times to PHCand STF) increased the probability of bypassing PHCsThe result is consistent with the findings in the litera-ture ie increased travel time lowers the utilization ofhealth care facilities [33 44ndash50] Without a formal refer-ral system in urban areas where health resources aremuch richer and STFs are more concentrated than thosein rural areas in China urban patients are more likely tobypass PHCs because of easy accessibility and availabilityof medical care services they needPatients with higher educational attainment show a

higher probability of bypassing PHCs Educational at-tainment is an indicator of socioeconomic status (SES)as well as knowledge about the relative quality of ser-vices facilities offer Middle-aged and older adults withhigher level of income are also more likely to bypassPHCs This probably indicates perception of lower qual-ity of services at the PHCs compared to the STFs Withan increase in income and educational attainment pa-tients become more sensitive to service quality and lesssensitive to cost savings that can be achieved by utilizingPHCsIn rural areas self-reported poor health status in-

creased the likelihood of bypassing PHCs Again thispossibly reflects a lack of confidence in the quality of

Table 2 Random effects logistic regression results bypassing primary health centers the China Health and Aging LongitudinalStudy 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 208 (177 245) lt 0001 215 (153 302) lt 0001

Relative travel time 115 (113 117) lt 0001 128 (118 139) lt 0001

Constant 025 (017 038) lt 0001 063 (030 130) 0207

Observations 7672 2389

Li et al BMC Health Services Research (2021) 21895 Page 8 of 12

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 108 (085 139) 0488 102 (069 150) 0932

ge 65 091 (068 121) 0509 171 (107 273) 0024

Male 103 (084 129) 0727 100 (071 140) 0998

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 121 (095 155) 0120 169 (100 285) 0050

Middle school 162 (117 224) 0004 216 (121 385) 0009

High school 189 (116 306) 0010 252 (134 476) 0004

gt three-years of college 556 (097 3181) 0054 294 (126 686) 0013

Married 107 (078 147) 0681 102 (063 165) 0936

Household income

Low income 104 (077 140) 0808 101 (064 160) 0959

Lower middle income 102 (076 136) 0921 063 (036 111) 0110

Upper middle income 111 (083 148) 0498 073 (049 109) 0129

High income 100 Ref 100 Ref

Medical insurance

UEMI 153 (062 375) 0354 155 (076 316) 0227

URMI 284 (090 896) 0075 140 (065 302) 0387

NRCMI 086 (054 136) 0517 058 (028 119) 0136

Other Insurance 110 (033 217) 0726 086 (044 168) 0664

No Insurance 084 Ref 100 Ref

Health status

Poor 159 (125 202) lt 0001 103 (069 156) 0872

Fair 100 Ref

Good 134 (099 181) 0056 099 (065 151) 0972

Specific chronic conditions

Hypertension 102 (079 131) 0897 093 (063 137) 0705

Dyslipidemia 163 (112 237) 0010 094 (060 147) 0778

Diabetes 093 (057 150) 0758 196 (100 383) 0049

Chronic lung diseases 096 (070 131) 0790 104 (061 180) 0876

Heart diseases 120 (086 168) 0291 140 (087 225) 0172

Kidney disease 059 (039 089) 0013 067 (036 125) 0210

Stomach diseases 088 (070 111) 0281 102 (070 150) 0911

Arthritis or rheumatism 079 (064 098) 0035 096 (067 137) 0807

Other major chronic diseases 088 (064 120) 0413 063 (037 105) 0075

Functional limitations

None 100 Ref 100 Ref

Mild 106 (080 141) 0662 107 (065 177) 0783

Moderate 147 (092 234) 0107 169 (049 587) 0410

Severe 191 (082 446) 0133 152 (031 744) 0603

Li et al BMC Health Services Research (2021) 21895 Page 9 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015

Rural Urban

OR 95 CI P OR 95 CI P

Age group

45ndash54 100 Ref 100 Ref

55ndash64 108 (085 139) 0488 102 (069 150) 0932

ge 65 091 (068 121) 0509 171 (107 273) 0024

Male 103 (084 129) 0727 100 (071 140) 0998

Educational attainment

Illiterate 100 Ref 100 Ref

Elementary school 121 (095 155) 0120 169 (100 285) 0050

Middle school 162 (117 224) 0004 216 (121 385) 0009

High school 189 (116 306) 0010 252 (134 476) 0004

gt three-years of college 556 (097 3181) 0054 294 (126 686) 0013

Married 107 (078 147) 0681 102 (063 165) 0936

Household income

Low income 104 (077 140) 0808 101 (064 160) 0959

Lower middle income 102 (076 136) 0921 063 (036 111) 0110

Upper middle income 111 (083 148) 0498 073 (049 109) 0129

High income 100 Ref 100 Ref

Medical insurance

UEMI 153 (062 375) 0354 155 (076 316) 0227

URMI 284 (090 896) 0075 140 (065 302) 0387

NRCMI 086 (054 136) 0517 058 (028 119) 0136

Other Insurance 110 (033 217) 0726 086 (044 168) 0664

No Insurance 084 Ref 100 Ref

Health status

Poor 159 (125 202) lt 0001 103 (069 156) 0872

Fair 100 Ref

Good 134 (099 181) 0056 099 (065 151) 0972

Specific chronic conditions

Hypertension 102 (079 131) 0897 093 (063 137) 0705

Dyslipidemia 163 (112 237) 0010 094 (060 147) 0778

Diabetes 093 (057 150) 0758 196 (100 383) 0049

Chronic lung diseases 096 (070 131) 0790 104 (061 180) 0876

Heart diseases 120 (086 168) 0291 140 (087 225) 0172

Kidney disease 059 (039 089) 0013 067 (036 125) 0210

Stomach diseases 088 (070 111) 0281 102 (070 150) 0911

Arthritis or rheumatism 079 (064 098) 0035 096 (067 137) 0807

Other major chronic diseases 088 (064 120) 0413 063 (037 105) 0075

Functional limitations

None 100 Ref 100 Ref

Mild 106 (080 141) 0662 107 (065 177) 0783

Moderate 147 (092 234) 0107 169 (049 587) 0410

Severe 191 (082 446) 0133 152 (031 744) 0603

Li et al BMC Health Services Research (2021) 21895 Page 9 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

services andor non-availability of individualized servicesat the PHC [51 52] Offering individualized services is aperson-centered care approach [53] Patients who expe-rienced hospitalization in the past 12 months are morelikely to bypass PHCs as the hospitalization in the recentpast may be associated with actual or perceived higherseverity of illness or need for individualized services en-couraging utilization of STFs [29] A number of chronicconditions also affect the choice of facility-type Patientswith arthritis or rheumatism were less likely to bypassPHCs probably because these conditions make travelmore difficult [54] especially for rural patients who musttravel significantly longer distances to reach STFsOlder adults show high degree of bypassing PHCs in

urban areas but for rural areas the opposite was true(middle-aged individuals more likely to bypass than theolder adults) This tendency may be associated with lackof relevant services at the PHC level Older adults re-quire more personalized care and continuity of care isimportant for their health status In contrast for ruralareas social value of protecting the health of middle-aged individuals may be higher and travel to a STF ismore costly and difficult for the elderly Among urbanpatients older adults were more likely to bypass PHCsthan those aged 45ndash54 years Geriatric services have notbeen properly incorporated at the primary level in urbanChina [55] which may explain urban older adultsrsquo hesi-tancy to seek care from the PHCs Urban patients withdiabetes are also more likely to use upper-level facilitiesagain reflecting the lack of chronic disease managementat the primary level [56]In urban areas where the upper-level facilities are eas-

ily accessible the tendency to bypass is significantlyhigher With improvements in health status and theaging of the population patients need individualized aswell as continuity of care services Unless those servicesare offered from the PHCs bypassing problem is ex-pected to increase further [57 58]There are several limitations of this study The

CHARLS survey provides information only on the mostrecent outpatient service utilized in the previous 4weeks Measuring the incidence of bypassing using themost recent outpatient visits within the last 4 weeks may

bias the results The survey did not collect informationon facility and provider characteristics and the studycould not analyze the effect of provider characteristicson the choice of health facilities

ConclusionsAbout two in five older adults in China bypassed PHCsto obtain care from upper-level providers (STFs) Urbanpatients were twice as likely as rural patients to bypassPHCs The present study found that relative increase intravel time and more educated had a higher likelihoodof bypassing primary care in rural and urban areasMoreover poor health status and being hospitalized inthe past 12 months had a higher likelihood of bypassingprimary care in rural areas On the other hand arthritisor rheumatism decreased the odds of bypassing Further-more older age and diabetes had a higher likelihood ofbypassing primary care in urban areasContinuity of care and individualized attention require

redesigning the mode of care delivery at the PHC levelwith emphasis on patient-provider trust and adoption ofproactive health promotion and disease prevention Struc-tural changes including the staffing of the PHCs will beneeded to make the PHCs more effective in addressing theneeds of the elderly and middle-aged individuals The find-ings of the study indicate the importance of strengtheningthe service provision in rural PHCs to address commonchronic conditions In fact improving the service deliveryfor addressing the needs of chronic conditions will im-prove utilization of PHCs in both rural and urban areasIn conclusion improving the utilization of PHCs in

China will require improving the quality of services ren-dered from these facilities Perceived quality of medicalcare delivered from the PHCs can be improved if the facil-ities are able to offer comprehensive person-centeredhealth care focusing on the family health care needs andmaking critical screening and preventive services availableAvailability of services alone will not improve overall qual-ity of services ndash it will require a system of continuity ofcare by ensuring good rapport between patients and phy-sicians If patients feel that they have their own primarycare physician in the PHCs the likelihood of seeking carefrom PHCs should be significantly higher

Table 3 Random-effects logistic regression results bypassing primary health centers for new visits (excluding revisits for the sameepisode) by older adults the China Health and Aging Longitudinal Study 2011ndash2015 (Continued)

Rural Urban

OR 95 CI P OR 95 CI P

Hospitalization 196 (147 260) lt 0001 147 (091 236) 0113

Relative travel time 131 (124 139) lt 0001 131 (116 148) lt 0001

Constant 015 (007 030) lt 0001 047 (019 117) 0104

Observations 3653 1067

Li et al BMC Health Services Research (2021) 21895 Page 10 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

Supplementary InformationThe online version contains supplementary material available at httpsdoiorg101186s12913-021-06908-0

Additional file 1

AcknowledgementsNot applicable

Authorsrsquo contributionsCL and MK conceptualized the research idea and finalized the researchmethodology to be followed CL analyzed the data and prepared the firstdraft of first few sections of the manuscript CL and MK collaborativelydrafted all sections and finalized the first draft of the full manuscript CL ZCand MK interpreted the results reviewed the manuscript and suggestedchanges All authors read and approved the final manuscript

Authorsrsquo informationNo additional information on authors

FundingNo funding was received for the study The first author however is a post-doctoral fellow at the University of Georgia and his post-doctoral fellowshipis funded by the Scientific Research Foundation for Doctoral Scholars in InnerMongolia Medical University and Scientific Research Projects in Higher Edu-cation Institutions in Inner Mongolia (NJSY20145)

Availability of data and materialsThe dataset used for drafting the paper is a publicly available datasetavailable in the Peking University Open Research Data Platform repositoryThe dataset is downloadable for research purposes through the link httpsopendatapkueducndataverseCHARLS

Declarations

Ethics approval and consent to participateThis research has used a publicly available secondary dataset The datasetdoes not contain any individual identifiers No ethical approval was requireddue to the type and nature of the data used

Consent for publicationNot applicable

Competing interestsThe authors declare that they have no competing interests

Author details1Department of Health Economics School of Health Management InnerMongolia Medical University Hohhot China 2Department of Health Policyand Management College of Public Health University of Georgia 100 FosterRd Wright Hall 116 Athens GA 30602 USA 3Centre for Health EconomicsSchool of Economics University of Nottingham Ningbo China NingboChina

Received 24 March 2021 Accepted 16 August 2021

References1 Meng Q Mills A Wang L Han Q What can we learn from Chinarsquos health

system reform BMJ 2019365l23492 Eggleston K Ling L Qingyue M Lindelow M Wagstaff A Health service

delivery in China a literature review Health Econ 200817(2)149ndash65 httpsdoiorg101002hec1306

3 Yu W Li M Nong X Ding T Ye F Liu J et al Practices and attitudes ofdoctors and patients to downward referral in Shanghai China BMJ Open20177(4)e012565 httpsdoiorg101136bmjopen-2016-012565

4 Chen H Chi I Liu R Hospital utilization among Chinese older adultspatterns and predictors J Aging Health 201931(8)1454ndash78 httpsdoiorg1011770898264318780546

5 Xiao N Long Q Tang X Tang S A community-based approach to non-communicable chronic disease management within a context of advancinguniversal health coverage in China progress and challenges BMC PublicHealth 2014141ndash6

6 Yu H Universal health insurance coverage for 13 billion people whataccounts for Chinas success Health Policy 2015119(9)1145ndash52 httpsdoiorg101016jhealthpol201507008

7 Liu Y Zhong L Yuan S van de Klundert J Why patients prefer high-levelhealthcare facilities a qualitative study using focus groups in rural andurban China BMJ Glob Health 20183(5)e000854 httpsdoiorg101136bmjgh-2018-000854

8 Wu D Lam TP Underuse of primary care in China the scale causes andsolutions J Am Board Fam Med 201629(2)240ndash7 httpsdoiorg103122jabfm201602150159

9 Li L Fu H Chinas health care system reform Progress and prospects Int JHealth Plan Manag 201732(3)240ndash53 httpsdoiorg101002hpm2424

10 National Health Commission of China Chinese Health Statistical Digest2020 httpwwwnhcgovcnguihuaxxss10748202006ebfe31f24cc145b198dd730603ec4442shtml Accessed 1 Sept 2020 Chinese

11 Barber SL Yao L Development and status of health insurance systems inChina Int J Health Plan Manag 201126(4)339ndash56 httpsdoiorg101002hpm1109

12 Yip W Fu H Chen AT Zhai T Jian W Xu R et al 10 years of health-carereform in China progress and gaps in universal health coverage Lancet2019394(10204)1192ndash204 httpsdoiorg101016S0140-6736(19)32136-1

13 Li X Lu J Hu S Cheng KK de Maeseneer J Meng Q et al The primaryhealthcare system in China Lancet 2017390(10112)2584ndash94 httpsdoiorg101016S0140-6736(17)33109-4

14 Gotsadze G Bennett S Ranson K Gzirishvili D Health care-seekingbehaviour and out-of-pocket payments in Tbilisi Georgia Health PolicyPlan 200520(4)232ndash42 httpsdoiorg101093heapolczi029

15 Bell G Macarayan EK Ratcliffe H Kim JH Otupiri E Lipsitz S et alAssessment of bypass of the nearest primary health care facility amongwomen in Ghana JAMA Netw 20203(8)e2012552 httpsdoiorg101001jamanetworkopen202012552

16 Gauthier B Wane W Bypassing health providers the quest for better priceand quality of health care in Chad Soc Sci Med 201173(4)540ndash9 httpsdoiorg101016jsocscimed201106008

17 Akin JS Hutchinson P Health-care facility choice and the phenomenon ofbypassing Health Policy Plan 199914(2)135ndash51 httpsdoiorg101093heapol142135

18 Kruk ME Hermosilla S Larson E Mbaruku GM Bypassing primary care clinicsfor childbirth a cross-sectional study in the Pwani region United Republicof Tanzania Bull World Health Organ 201492(4)246ndash53 httpsdoiorg102471BLT13126417

19 Kruk ME Mbaruku G McCord CW Moran M Rockers PC Galea S Bypassingprimary care facilities for childbirth a population-based study in rural TanzaniaHealth Policy Plan 200924(4)279ndash88 httpsdoiorg101093heapolczp011

20 Liu J Bellamy GR McCormick M Patient bypass behavior and critical accesshospitals implications for patient retention J Rural Health 200723(1)17ndash24httpsdoiorg101111j1748-0361200600063x

21 Paul BK Rumsey DJ Primary care providers bypassing in rural Kansas TransKans Acad Sci 2002105(1 ampamp 2)79ndash90 httpsdoiorg1016600022-8443(2002)105[0079PCPBIR]20CO2

22 Sanders SR Erickson LD Call VR McKnight ML Middle-aged and older adulthealth care selection health care bypass behavior in rural communities inMontana J Appl Gerontol 201736(4)441ndash61 httpsdoiorg1011770733464815602108

23 Yao J Agadjanian V Bypassing health facilities in rural Mozambique spatialinstitutional and individual determinants BMC Health Serv Res 201818(1)1006 httpsdoiorg101186s12913-018-3834-y

24 Aoki T Yamamoto Y Ikenoue T Kaneko M Kise M Fujinuma Y et al Effectof patient experience on bypassing a primary care gatekeeper amulticenter prospective cohort study in Japan J Gen Intern Med 201833(5)722ndash8 httpsdoiorg101007s11606-017-4245-1

25 Damrongplasit K Wangdi T Healthcare utilization bypass and multiplevisits the case of Bhutan Int J Health Econ Manag 201717(1)51ndash81 httpsdoiorg101007s10754-016-9194-4

26 Rao KD Sheffel A Quality of clinical care and bypassing of primary healthcenters in India Soc Sci Med 201820780ndash8 httpsdoiorg101016jsocscimed201804040

Li et al BMC Health Services Research (2021) 21895 Page 11 of 12

27 Sanders SR Erickson LD Call VR McKnight ML Hedges DW Rural healthcare bypass behavior how community and spatial characteristics affectprimary health care selection J Rural Health 201531(2)146ndash56 httpsdoiorg101111jrh12093

28 Shah R Bypassing birthing centres for child birth a community-based studyin rural Chitwan Nepal BMC Health Serv Res 201616(1)597 httpsdoiorg101186s12913-016-1848-x

29 Liu J Bellamy G Barnet B Weng S Bypass of local primary care in ruralcounties effect of patient and community characteristics Ann Fam Med20086(2)124ndash30 httpsdoiorg101370afm794

30 Escarce JJ Kapur K Do patients bypass rural hospitals determinants ofinpatient hospital choice in rural California J Health Care Poor Underserved200920(3)625ndash44 httpsdoiorg101353hpu00178

31 Tai WTC Porell FW Adams EK Hospital choice of rural Medicarebeneficiaries patient hospital attributes and the patientndashphysicianrelationship Health Serv Res 200439(6p1)1903ndash22 httpsdoiorg101111j1475-6773200400324x

32 Perera S Weerasinghe M Bypassing primary care in Sri Lanka a comparativestudy on reasons and satisfaction Vietnam J Public Health 2015369ndash76

33 Radcliff TA Brasure M Moscovice IS Stensland JT Understanding ruralhospital bypass behavior J Rural Health 200319(3)252ndash9 httpsdoiorg101111j1748-03612003tb00571x

34 Leonard KL Mliga GR Haile MD Bypassing health centres in Tanzaniarevealed preferences for quality J Afr Econ 200211(4)441ndash71 httpsdoiorg101093jae114441

35 Roh CY Moon MJ Nearby but not wanted The bypassing of rural hospitalsand policy implications for rural health care systems Policy Stud J 200533(3)377ndash94 httpsdoiorg101111j1541-0072200500121x

36 Varkevisser M van der Geest SA Why do patients bypass the nearesthospital An empirical analysis for orthopaedic care and neurosurgery in theNetherlands Eur J Health Econ 20078(3)287ndash95 httpsdoiorg101007s10198-006-0035-0

37 Greene WH Econometric analysis New York Prentice Hall 200238 Zhao Y Hu Y Smith JP Strauss J Yang G Cohort profile the China health

and retirement longitudinal study (CHARLS) Int J Epidemiol 201443(1)61ndash8 httpsdoiorg101093ijedys203

39 Wang W Maitland E Nicholas S Loban E Haggerty J Comparison of patientperceived primary care quality in public clinics public hospitals and privateclinics in rural China Int J Equity Health 201716(1)176 httpsdoiorg101186s12939-017-0672-1

40 Andreszlig HJ Golsch K Schmidt AW Applied panel data analysis for economicand social surveys Springer Science amp Business Media 2013 httpsdoiorg101007978-3-642-32914-2

41 Hausman JA Specification tests in econometrics Econ Soc 1978461251ndash7142 Fang H Chen J Rizzo JA Explaining urban-rural health disparities in China

Med Care 200947(12)1209ndash16 httpsdoiorg101097MLR0b013e3181adcc32

43 Liu M Zhang Q Lu M Kwon CS Quan H Rural and urban disparity inhealth services utilization in China Med Care 200745(8)767ndash74 httpsdoiorg101097MLR0b013e3180618b9a

44 Guagliardo MF Spatial accessibility of primary care concepts methods andchallenges Int J Health Geogr 20043(1)3 httpsdoiorg1011861476-072X-3-3

45 Kahabuka C Kvaringle G Moland KM Hinderaker SG Why caretakers bypassprimary health care facilities for child care-a case from rural Tanzania BMCHealth Serv Res 201111(1)315 httpsdoiorg1011861472-6963-11-315

46 Kruk ME Paczkowski M Mbaruku G De Pinho H Galea S Womenspreferences for place of delivery in rural Tanzania a population-baseddiscrete choice experiment Am J Public Health 200999(9)1666ndash72 httpsdoiorg102105AJPH2008146209

47 Arcury TA Gesler WM Preisser JS Sherman J Spencer J Perin J The effectsof geography and spatial behavior on health care utilization among theresidents of a rural region Health Serv Res 200540(1)135ndash56 httpsdoiorg101111j1475-6773200500346x

48 Buor D Analysing the primacy of distance in the utilization of healthservices in the Ahafo-Ano south district Ghana Int J Health Plan Manag200318(4)293ndash311 httpsdoiorg101002hpm729

49 Kelly C Hulme C Farragher T Clarke G Are differences in travel time ordistance to healthcare for adults in global north countries associated withan impact on health outcomes A systematic review BMJ Open 20166(11)e013059 httpsdoiorg101136bmjopen-2016-013059

50 Maringlqvist M Sohel N Do TT Eriksson L Persson LAring Distance decay indelivery care utilisation associated with neonatal mortality A case referentstudy in northern Vietnam BMC Public Health 201010762

51 DeSalvo KB Fan VS McDonell MB Fihn SD Predicting mortality andhealthcare utilization with a single question Health Serv Res 200540(4)1234ndash46 httpsdoiorg101111j1475-6773200500404x

52 Jylhauml M What is self-rated health and why does it predict mortalityTowards a unified conceptual model Soc Sci Med 200969(3)307ndash16httpsdoiorg101016jsocscimed200905013

53 Zhao J Gao S Wang J Liu X Hao Y Differentiation between two healthcareconcepts person-centered and patient-centered care J Nurs 201623520132

54 Piva SR Almeida GJ Wasko MCM Association of physical function andphysical activity in women with rheumatoid arthritis Arthritis Care Res201062(8)1144ndash51 httpsdoiorg101002acr20177

55 World Health Organization China country assessment report on ageing andhealth 2015 httpswwwwhointageingpublicationschina-country-assessmenten Accessed 2 Sept 2020

56 Jia W Zhang P Duolikun N Zhu D Li H Bao Y et al Study protocol for theroad to hierarchical diabetes management at primary care (ROADMAP)study in China a cluster randomised controlled trial BMJ Open 202010(1)e032734 httpsdoiorg101136bmjopen-2019-032734

57 Angstman KB Individualized health care moving from population health tocare of the one Inquiry 2014510046958014561637

58 Arslan BK Patients perception of individualized care and satisfaction withnursing care levels in Turkey Int J Caring Sci 20158369

Publisherrsquos NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations

Li et al BMC Health Services Research (2021) 21895 Page 12 of 12