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Hindawi Publishing CorporationInternational Journal of DentistryVolume 2010, Article ID 231398, 13 pagesdoi:10.1155/2010/231398
Research Article
New Casemix Classification as an Alternative Method forBudget Allocation in Thai Oral Healthcare Service: A Pilot Study
Thunthita Wisaijohn,1 Atiphan Pimkhaokham,2 Phenkhae Lapying,3 Chumpot Itthichaisri,2
Supasit Pannarunothai,4 Isao Igarashi,1 and Koichi Kawabuchi1
1 Healthcare Economics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University,Tokyo 113-8510, Japan
2 Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand3 Dental Health Bureau, Department of Health, Ministry of Public Health, Nonthaburi 11000, Thailand4 Faculty of Medicine, Naresuan University, Phitsanulok 65000, Thailand
Correspondence should be addressed to Atiphan Pimkhaokham, [email protected]
Received 27 April 2010; Revised 29 June 2010; Accepted 15 July 2010
Academic Editor: Stephen Richmond
Copyright © 2010 Thunthita Wisaijohn et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.
This study aimed to develop a new casemix classification system as an alternative method for the budget allocation of oralhealthcare service (OHCS). Initially, the International Statistical of Diseases and Related Health Problem, 10th revision, ThaiModification (ICD-10-TM) related to OHCS was used for developing the software “Grouper”. This model was designed to allowthe translation of dental procedures into eight-digit codes. Multiple regression analysis was used to analyze the relationship betweenthe factors used for developing the model and the resource consumption. Furthermore, the coefficient of variance, reduction invariance, and relative weight (RW) were applied to test the validity. The results demonstrated that 1,624 OHCS classifications,according to the diagnoses and the procedures performed, showed high homogeneity within groups and heterogeneity betweengroups. Moreover, the RW of the OHCS could be used to predict and control the production costs. In conclusion, this new OHCScasemix classification has a potential use in a global decision making.
1. Introduction
There are many insurance systems worldwide for UniversalHealthcare Coverage. In Thailand, health insurance systemsare categorized into three major schemes: the Civil Ser-vant Medical Benefit Scheme (CSMBS), the Social SecurityScheme (SSS), and the Universal Coverage Scheme (UCS)or the “30 baht (in 2002, 43.0 Baht/US$ copayment) forall diseases” (UCS was implemented in May 2001 andintroduced nationwide in April 2002) [1]. In 2006, the UCSabolished the 30 baht copayment per visit and made the UCSfree [2]. In the past, the health budget was allocated by thecharacteristics of each healthcare provider, the number ofdoctors, and the number of patient beds. Thus, healthcareresources were not equitably allocated between the healthinsurance systems [3]. In 2001, the revamping of the
health insurance system was initiated to restructure themethodology and the system allocating healthcare resourcesby the Health Systems Research Institute [4, 5]. One keydifference between the insurance schemes is that the UCSseparated the provider budget between the inpatient and theoutpatient for exclusive capitation. Under this paradigm, theoutpatient budget was allocated on the basis of the capitationrate, while the inpatient budget was allocated on the basisof Diagnosis Related Group (DRG) within a global budget[1].
Under the UCS, the budget for the oral healthcareservice (OHCS), based on the benefit package, is part ofthe outpatient and Promotion/Prevention budget, to sharefinancial risks among OHCS and general health services.While the budgets for all capital investment budgets areallocated by the Ministry of Public Health (MOPH) regional
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regulators’ judgment, the OHCS, unfortunately, is usuallythe last priority. Therefore, the efficiency of the allocationis doubted, mainly the methodology and reliability aspect,as follows: (1) Since the Universal Healthcare Coveragepolicy was established in the year 2001, the demands forgovernment-funded OHCS have increased significantly. Inparticular, the demand for dental substitution, which ishighly expensive, has increased [6]. The per capita budget forall healthcare service in the fiscal year of 2003 was the sameamount as the previous year, approximately 1,202 baht (43.0Baht/US$) [7, 8] and became 2,202 Baht (34.34 Baht/US$) in2009. (2) Current budget allocation has not been categorizedfor OHCS separately, and there have been few cost studiesof OHCS. The information on the cost of these serviceactivities is scarce, leading to a shortage of information formaking management decisions. Thus, cost studies of OHCSare important and necessary for the evaluation of healthcaremanagerial efficiency and resource allocation, as well as forgenerating the appropriate parameters to use in makingpolicies for healthcare service improvement in the context ofbudgetary constraints [9, 10].
Casemix is a generic term for the patients’ classificationsystem, including inpatient and outpatient status, budgetingallocation, and payment [11]. Successful outcomes from theadoption of a casemix system have been shown in manycountries [12–14]. The best-known classification systemused in a casemix funding model is the DRG. The DRGclassifies acute inpatient episodes into a discrete number ofmanageable categories, depending on their clinical conditionand resource consumption, assigned by a grouper programbased on their demographics, clinical information (diagnosis(Dx) and procedure (Proc) codes), and comorbidity. TheDRG method has been well evaluated for classifying inpatienttreatment [15, 16]. In Thailand, the initial DRG was imple-mented in 1999 and several successive versions have beendeveloped. Pannarunothai’s studies on DRG development inThailand recommended that casemix systems should be usedin the budget allocation for the healthcare service system[11, 17].
In Thailand, most people are covered by the aforemen-tioned insurance schemes, although the budget allocationsand payment systems are different between the schemes.DRG is currently employed as an allocation method onlyfor inpatient healthcare budgets and not for all healthcarebudgets. However, the DRG system has limitations inreflecting the OHCS cost. The future development of theappropriate inpatient and outpatient casemix for OHCS isimportant and necessary for economic healthcare manage-ment [17].
For the above-described reasons, the development ofa new casemix classification in OHCS is desirable. Thisstudy aimed to develop and examine the feasibility of anew casemix classification system as an alternative methodfor budget allocation in Thai OHCS. These three schemeswere each adapted, on the basis of DRG, as an alternativemethod to inpatient and outpatient-related OHCS forbudget allocation [11, 18, 19]. This system might, in time,be applied in other countries healthcare system for OHCSresource allocation as well.
2. Materials and Methods
This study was conducted utilizing the electronic data ofindividual patients treated from April 2008 to March 2009 atthree selected tertiary hospitals that met the study’s inclusioncriteria. The study protocol was approved by the EthicsCommittee of the participating hospitals. The inclusioncriteria were the use of the International Classification ofDiseases, 10th edition (ICD-10) and International Classifi-cation of Disease, 9th edition, Clinical Modification (ICD-9-CM) for the clinical records [20, 21] and the systematickeeping of a database record that was based on a globalcoding of the clinical records. These databases containedinformation on inpatient and outpatient care utilization,including demographic data (date of birth (DOB), age,and gender), clinical information (Dx, Proc), and resourceconsumption (hospital charge, admission date, dischargedate and type, length of stay (LOS), and health insurance).The five main methods used to develop a new casemixclassification as an alternative method for budget allocationof OHCS in this study were coding, classification, costing,calibration, and payment.
2.1. Coding. The coding process was divided into two parts.
Part I. The development of the new casemix classification forOHCS began with the adoption of the ICD-10, ICD-9-CM,Current Dental Terminology 2007 (CDT) [22], InternationalStatistical of Diseases and Related Health Problem, 10threvision, Thai Modification (ICD-10-TM) [23, 24], ThaiDRG version 4 [25], and International Refined DRG (IR-DRG) [26]. The study designed the analysis method in twosteps. Step one, the ICD-10-TM for Dx and Proc codes relatedto OHCS were retrieved by a researcher and approved byfive dentists with more than ten years of clinical experienceand specialists in OHCS. Step two, these codes were thenmapped to ICD-10 for Dx and ICD-9-CM for Proc byProgram Map version 1.0, copyright of Thai health codingcenter, Cluster for Health Information Division, Bureau ofPolicy and Strategy, MOPH, Thailand. These selected codeswere used as inclusion lists of principal diagnoses (PDx) andprocedures (Proc).
Part II. The electronic data of individual patients from thethree selected tertiary hospitals were checked based on theinclusion lists of PDx and Proc (Figure 1).
2.2. Classification. To develop a new casemix classificationsystem for Thai OHCS, a specially designed computer soft-ware program called “Grouper” was used. Grouper was ableto allocate each episode to a DRG according to the clinicalinformation and other relevant data. This program usedclinical and demographic data as the input and produced acorresponding DRG as the output [27].
The OHCS casemix classification model (Grouper) con-sisted of one procedure in one visit that classified cases intotwo main groups: the oral and maxillofacial surgery (OMFS)group, designated M, and the tooth and periodontium
International Journal of Dentistry 3
All patient data
Inclusion lists byprincipal diagnosis
Inclusion lists byprocedure
Oral and maxillofacialsurgery (M)
Tooth andperiodontium (D)
Ungroupable
Ungroupable
No
Yes
No
Yes
Yes Yes
Figure 1: Diagram presents the steps one and two.
1 2 3 4 5 6 7 8
1
2 3
4 5
6
7
8
Represents the two main groups of oral and maxillofacial surgery, designated M, or tooth and periodontium, designated D.
Represents the procedure clusters using anatomy group by body region as shown in ICD-10-TM.
Represents the subgroups of procedure clusters by root operation as shown in ICD-10-TM.
Represents the level of the complexity; 1 (one) for a simple procedure, 2 (two) for a complex procedure, and 3 (three)
for a multidisciplinary or complex procedures.
Represents the general anesthesia (GA); 1 (one) represented GA and 0 (zero) was non-GA.
Represents the complication and comorbidity (CC); 1 (one) was CC and 0 (zero) was non-CC.
For examples: M0802311 (maxilla, operative procedures, level 3, with GA and with CC)D0527200 (tooth restoration, resin-based composite restorations, level 2, without GA and without CC)
Figure 2: Diagram presents the casemix classification model of OHCS (one procedure in one visit) as represented in eight-digit codes.
group, designated D. Multiple procedures in one visit weredesignated as P. The variables used for the OHCS groupingwere included (1) PDx, (2) secondary diagnosis (SDx), (3)Proc (which were classified by the level of complexity bythe same expert group), (4) anatomy group by body regionsrelated to ICD-10-TM (Table 1), (5) root operation relatedto ICD-10-TM (Table 2), (6) general anesthesia (GA), and(7) complication and comorbidity (CC), using the Charlsonindex. This classification system was developed to allow thetranslation of dental procedures into eight-digit codes assummarized in Figures 2, 3, 4, and 5.
2.3. Costs. Initially, multiple regression analysis was usedto study the relationship between the factors used fordeveloping the codes and resource consumption. Thisanalysis was employed to explore the relationship betweenthe cost of P, D, and M (dependent variables) and sev-eral independent variables including, GA, CC, number ofprocedures in one visit, Proc (separated by the level ofcomplexity), and LOS. Cross-validation was used to test thevalidation of the casemix in a separate set of data. Cross-validation showed the quality of the prediction equationbetween the structure data and the data for validation.
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Table 1: Examples of both groups (M and D), split into procedureclusters using the anatomy group by body region.
OMFS groups (anatomical body region) Code M
Scalp
Include: scalp and subgaleal soft tissues M01
Skull M02
Cranial nerves X, Trigeminal nerve M03
Cranial nerves X1, Accessory nerve M04
Cranial nerve XII, Hypoglossal nerve M05
Cranial nerves M06
Face M07
Maxilla M08
Mandible M09
Tooth and periodontium group(anatomical body region)
Code D
Oral examination D01
Radiographs/Diagnostic imaging D02
Preventive dentistry D03
Oral hygiene instructions and counseling D04
Tooth restoration D05
Endodontic treatment D06
M: oral and maxillofacial surgery (OMFS) corrects a wide spectrum ofdiseases, injuries, and defects in the head, neck, face, jaws, and the hard andsoft tissues of the oral and maxillofacial region.D: tooth and periodontium: periodontium refers to the specialized tissuesthat surround and support the teeth (small, calcified, whitish structuresfound in the jaws (or mouth)) maintaining them in the maxilla andmandible.
Table 2: Examples of the procedure clusters, split into subgroups ofprocedure clusters using a root operation.
OMFS groups (root operation) Code M
Scalp
Include: scalp and subgaleal soft tissues M01
Diagnostic procedures and non-operativeprocedures
M0101
Operative procedures M0102
Miscellaneous procedures M0104
Other procedures and operations M0199
Tooth and periodontium (root operation) Code D
Oral examination D01
Oral examination procedures D0121
Radiographs/Diagnostic imaging D02
Intraoral film D0222
Extraoral film D0223
Others D0299
M: oral and maxillofacial surgery (OMFS).D: tooth and periodontium.
The higher confidence obtained from the cross-validation,the more suitable the estimation of the population predictionequation.
2.4. Calibration. Three statistical analyses, the coefficient ofvariation (CV), the reduction in variance (RIV), and therelative weight (RW), were applied to verify the minimumvariation within each group, the maximum variation amonggroups, and the assignment of a payment weight for the newcasemix classification, respectively.
The CV is calculated as the standard deviation dividedby the arithmetic mean. The CV value demonstrates thehomogeneity of the cases within each group. A high CVindicates wide variation within each group. The acceptedstandard for CV is that each class should have a CV ofless than 1.0 [15]. The expected end results using the newgrouper program are groups of cases that are clinicallysimilar and/or homogeneous with respect to resource use.
The RIV statistic is commonly used to assess the overallperformance of the grouping method by comparing thevariances of cost before and after grouping. The RIV wasalso related to the amount of variation within the datathat requires explanation. A higher RIV reflected betterperformance of the grouping.
The RW is a measure of the resources used: it comparesthe average resource used in each group with the averageresource used in all cases. In this study, statistical outliersbeyond three standard deviations of the average cost for eachOHCS classification were eliminated [28–30]. The RW wascomputed based on the cost data. It was defined in our studyas the mean cost in each group divided by the mean costs ofall patients. The cost in this study focused only on the costof surgery, including general and local anesthesia, medicaldevices and instruments, and medical supplies. The staff costwas not included in this study because it was not paid ona per case basis. In Thailand, all staff salary is paid by thegovernment and is dependent on the degree of education andthe years of experience. Furthermore, the standard of staffcost has not been well established in Thailand.
2.5. Payment. A payment calculation was necessary toestablish the prospective payment system. The paymentwas calculated using the RW of the OHCS classificationmultiplied by the current reimbursement rate (average baserate) in each group.
3. Results
3.1. Coding
Part I (Steps One and Two). The ICD-10-TM, consistingof 813 diagnoses and 1,090 procedures related to OHCS,were retrieved and mapped to ICD-10 and ICD-9-CM,respectively.
Part II. The electronic data of individual patients fromthree selected tertiary hospitals were checked by an inclu-sion list of PDx and Proc. There were 16,165 (84.64%)cases out of 19,098 initial cases (cases with incompletedata were eliminated) that met the inclusion criteria. Thenumber of inpatient and outpatient cases were 2,709 (16.8%)and 13,456 (83.2%), respectively. The demographic details,
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Overviews of Thai oral healthcare service (OHCS)
casemix classification model:
one procedure in one visit
Oral healthcare service(OHCS)
OMFS(M)
Procedures
Tooth andperiodontium
(D)
Oral examinationD01
D02
D03
D04
etc
Level ofcomplexity
Oral examinationprocedure D0121
D01211
D01212
D01213
W GAD012111
W/O GAD012110
W CC D0121111
W/O CC D0121110
W CC D0121101
W/O CC D0121100
Scalp M01
M02
M03
M04
etc
Diagnostic proceduresand non-operative M0101
Level ofcomplexity
M01011
M01012
M01013
W GAM010111
W/O GAM010110
W CC M0101111
W/O CC M0101110
W CC M0101101
W/O CC M0101100
Figure 3: Diagram demonstrates the overviews of the Thai oral healthcare service (OHCS) casemix classification model of one procedurein one visit. M = oral and maxillofacial surgery (OMFS), W = with, W/O = without, GA = general anesthesia, CC = complication andcomorbidity.
1 2 3 4 5 6 7 8
1
2
3
4
5 6
7
8
Represents multiple procedures in one visit designated, P.
Represents the number of total procedures in one visit
Represents the number of oral and maxillofacial surgery (M) procedures.
Represents the number of tooth and periodontium (D) procedures.
Represents the relationship between the levels of complexity (equal to one procedure in one visit)
that was generated by the running software.
Represents the general anesthesia (GA); 1 (one) represented GA and 0 (zero) was non-GA.
Represents the complication and comorbidity (CC); 1 (one) was CC and 0 (zero) was non-CC.
For an example: P2110210 (two procedures in one visit, M and D, complexity level 3 and 2, with GA and without CC)
Figure 4: Diagram presents the casemix classification model of OHCS (multiple procedures in one visit) as represented in eight-digitcodes.
clinical information and health insurance showed that themajority of the patients were female (8,723 cases; 54.0%),non-GA (13,911 cases; 86.05%), non-CC (15,708 cases;97.17%), and CSMBS (6,368 cases; 39.4%).
3.2. Classification. The new OHCS casemix classificationmodel (Grouper) consisted of two major procedure cat-egories, M and D, 62 procedure clusters (Table 1), 165subgroups of procedure clusters (Table 2), and 1,624 OHCS
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Overviews of Thai oral healthcare service (OHCS)casemix classification model:
multiple procedures in one visit (P)
Oral healthcareservice (OHCS)
Total procedures ofOMFS (M)
andtooth-periodontium(D)
Two proceduresin one visit
M, M
D, D
M, D
P220
P202
P211
Relationship betweenlevel of complexity
3, 3
3, 2
3, 1
2, 2
2, 1
1, 1
P22001
P22002
P22003
P22004
P22005
P22006
W GAP220011
W/O GAP220010
W CCP2200111
W/O CCP2200110
W CCP2200101
W/O CCP220100
Figure 5: Diagram demonstrates overviews of the Thai oral healthcare service (OHCS) casemix classification model of multiple proceduresin one visit (P). M = oral and maxillofacial surgery (OMFS), W = with, W/O = without, GA = general anesthesia, CC = complication andcomorbidity.
classifications according to the treatment procedures (AnnexTable 5). Each OHCS classification described a cluster ofpatients with related diagnoses, requiring a similar exam-ination and incurring similar treatment costs. There were16,165 patients who were grouped into OHCS classificationsby the grouper software. After the grouping process, only 307OHCS classifications were achieved to cover these procedurecodes. This result was likely limited by the OHCS data, asthe amount available in this pilot study was not sufficient tosupport the OHCS grouper.
3.3. Costs. For predicting costs, regression analysis wasemployed. Table 3 presents the determination of the cost ofP, D, and M. Because cost did not present a normal distribu-tion, a normal logarithmic transformation was undertaken.The predicted cost of P, D, and M had R2values of 0.892,0.132, and 0.122, respectively, and the probability of the F-test statistic was 0.000. The results showed that the GA, CC,number of procedures in one visit, Proc (divided by the levelof complexity), and LOS were associated with the costs of P,D, and M.
3.4. Calibration. To ensure that the OHCS classificationsreflected resource homogeneity within groups and hetero-geneity between groups, the CV and RIV, respectively, wereused for analysis.
The lowest CVs relative to the outpatient groups for P,D, and M were 0.02 (P2110200), 0.01 (D0843200), and 0.19(M4004100), respectively, while the highest CVs relative tothese groups for P, D, and M were 0.87 (P2020500), 0.99(D0736200), and 0.83 (M4310101), respectively. The lowestCVs relative to the inpatient groups for P, D, and M were 0.31
(P2200511), 0 (the number of cases was less than five), and0.22 (M4004100), respectively, while the inpatients’ highestCVs for P, D, and M were 0.98 (P2200410), 0 (the number ofcases was less than five), and 0.99 (M3002110), respectively.Moreover, all OHCS classifications had a CV on cost of lessthan one (Table 4, Annex Table 5).
The RIVs relative to the outpatient groups for P, D, andM were 27, 87, and 65 %, respectively, while the inpatientgroups’ RIVs for P, D, and M were 16, 0 (number of casesless than five) and 22 %, respectively. The results showedthat 100 % of the OHCS classifications had a higher RIV(RIV greater than 0) on cost (Table 4). Both the CV andRIV analysis demonstrated the superior performance of thegrouper software.
The lowest RWs in the outpatient groups for P, D,and M were 0.51 (P3121800), 0.14 (D0222100), and 0.30(M1999101), respectively, while the highest RWs of theoutpatient groups were 3.59 (P3121000), 21.33 (D0843200),and 7.88 (M3002200), respectively. The lowest RWs relativeto the inpatient groups for P, D, and M were 0.13 (P2200600),0 (the number of cases was less than five) and 0.02(M1999100), respectively, while the inpatients’ highest RWswere 2.03 (P3300510), 0 (the number of cases was less thanfive), and 3.46 (M3202210), respectively (Table 4, AnnexTable 5). A high RW indicated a higher case complexity andmore resources required for treatment than for low RWcases. Moreover, RW was the most important result of thecalibration because it was the determinant for the paymentto healthcare providers.
3.5. Payment. This study calculated the base rate character-istics by splitting cases into three main treatment groups
International Journal of Dentistry 7
Table 3: Multiple regressions of the cost of multiple procedures (P), the cost of OMFS (M), and the cost of tooth and periodontium (D).
Cost of multiple procedures (P) Cost of OMFS (M) Cost of tooth and periodontium (D)
95% CI 95% CI 95% CI
Odds-ratio Lower-upper P-valueOdds-ratio
Lower-upper P-value Odds-ratio
Lower-upper P-value
GenderMale(reference)
Female 0.97 0.89−1.13 .973 1.14 1.02−1.19 .009 0.95 0.88−1.03 .243
Age0−22(reference)
23−40 1.04 0.89−1.22 .671 1.56 1.39−1.74 <.001 1.02 0.91−1.15 .633
41−54 0.88 0.75−1.03 .121 1.17 1.05−1.31 .04 0.82 0.73−0.92 .001
54 + 0.85 0.73−0.99 .039 1.17 1.15−1.30 .03 0.79 0.71−0.88 <.001
GANon-GA(reference)
GA 295.78 162.41−538.67 <.001 1.57 1.49−1.66 <.001 2386.74 891.84−6387.39 <.001
Number ofprocedures
1(reference)
2 9.55 8.72−12.45 .033 1.02 1.01−1.03 <.001 1.02 1.01−1.02 <.001
3 2.72 1.35−4.56 <.001 1.21 1.16−1.28 <.001 1.19 1.14−1.23 <.001
4 8.68 6.78−11.34 <.001 1.16 1.12−1.20 <.001 1.16 1.13−1.27 <.001
CCNon-CC(reference)
CC 3.25 2.31−4.57 <.001 1.17 1.10−1.31 <.001 15.76 11.25−21.96 <.001
Complexity1(reference)
2-3 3.81 2.31−4.57 <.001 1.91 1.89−1.92 <.001 1.91 1.89−1.92 <.001
LOSLE21(reference)
GE22 0.15 0.06−0.33 <.001 1.53 1.38−1.73 <.001 0.02 0.05−0.08 <.001
Adjusted cost of multiple procedures (P) R2 = 0.892, cost of OMFS (M) R2 = 0.122, and cost of tooth and periodontium (D) R2 = 0.132GA = general anesthesia, Number of procedures = total procedures in one visit, CC = complication and comorbidityComplexity = level of complexity (1 = simple procedure, 2 = complex procedure, 3 = multidisciplinary or complicated procedure)LOS = length of stay (LE21 = less than and equal to 21, GE22 = more than 21).
Table 4: Summary of the statistical analysis of the coefficient of variation (CV), reduction in variance (RIV), and relative weight (RW).
OHCSN (cases) CV RIV RW
Inpatient Outpatient Inpatient Outpatient Inpatient Outpatient Inpatient Outpatient
P 365 7,832 0.31−0.98 0.02−0.87 16% 27% 0.13−2.03 0.51−3.59
D 3 2,619 N/A 0.01−0.99 N/A 87% N/A 0.14−21.33
M 2,341 3,005 0.22−0.99 0.19−0.83 22% 65% 0.02−3.46 0.30−7.88
P = multiple procedures in one visit, D = tooth and periodontium, M = oral and maxillofacial surgery (OMFS)CV = coefficient of variation, RIV = reduction in variance, RW = relative weight, N/A = not applicable.
consisting of P, D, and M and two patient groups consistingof inpatient and outpatient. The results showed that thehighest base rate among the three main treatment groupsrelative to the outpatient groups and the inpatient groupswere D and P, respectively.
4. Discussion
This is a study of the preliminary development of a newcasemix classification system related to ICD-10-TM in ThaiOHCS. The results indicated that the new casemix system
8 International Journal of DentistryT
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ne,
Op
erat
ive
proc
edu
res,
leve
l2M
1002
200
M10
0220
1M
1002
210
M10
0221
1
Faci
albo
ne,
Op
erat
ive
proc
edu
res,
leve
l3M
1002
300
M10
0230
1M
1002
310
M10
0231
1
Nos
e,R
epai
ror
reco
nst
ruct
ion
,lev
el1
M19
0610
0M
1906
101
M19
0611
0M
1906
111
Nos
e,O
ther
proc
edu
res
and
oper
atio
ns,
leve
l1M
1999
100
M19
9910
1M
1999
110
M19
9911
1
Nas
alca
vity
,Rem
oval
and
repl
acem
ent
ofn
asal
pack
ing
and
Con
trol
ofep
ista
xis
leve
l1M
2009
100
M20
0910
1M
2009
110
M20
0911
1
Nas
alca
vity
,Oth
erpr
oced
ure
san
dop
erat
ion
s,le
vel1
M20
9910
0M
2099
101
M20
9911
0M
2099
111
Nas
alca
vity
,Oth
erpr
oced
ure
san
dop
erat
ion
s,le
vel2
M20
9920
0M
2099
201
M20
9921
0M
2099
211
Nas
alse
ptu
m,R
epai
ror
reco
nst
ruct
ion
,lev
el3
M22
0630
0M
2206
301
M22
0631
0M
2206
311
Fron
taln
asal
sin
use
s,R
epai
ror
reco
nst
ruct
ion
,lev
el1
M23
0610
0M
2306
101
M23
0611
0M
2306
111
Fron
taln
asal
sin
use
s,R
epai
ror
reco
nst
ruct
ion
,lev
el2
M23
0620
0M
2306
201
M23
0621
0M
2306
211
Fron
taln
asal
sin
use
s,R
epai
ror
reco
nst
ruct
ion
,lev
el3
M23
0630
0M
2306
301
M23
0631
0M
2306
311
Para
nas
alsi
nu
ses,
Inci
sion
and
Exc
isio
nor
dest
ruct
ion
,lev
el1
M25
0410
0M
2504
101
M25
0411
0M
2504
111
Paro
tid
saliv
ary
glan
d,In
cisi
onan
dE
xcis
ion
orde
stru
ctio
n,l
evel
1M
2604
100
M26
0410
1M
2604
110
M26
0411
1
Paro
tid
saliv
ary
glan
d,In
cisi
onan
dE
xcis
ion
orde
stru
ctio
n,l
evel
2M
2604
200
M26
0420
1M
2604
210
M26
0421
1
Saliv
ary
glan
dan
ddu
ct,I
nci
sion
and
Exc
isio
nor
dest
ruct
ion
,lev
el1
M28
0410
0M
2804
101
M28
0411
0M
2804
111
Saliv
ary
glan
dan
ddu
ct,I
nci
sion
and
Exc
isio
nor
dest
ruct
ion
,lev
el2
M28
0420
0M
2804
201
M28
0421
0M
2804
211
Nec
k,D
iagn
osti
cpr
oced
ure
san
dn
onop
erat
ive
proc
edu
res,
leve
l1M
2901
100
M29
0110
1M
2901
110
M29
0111
1
Nec
k,D
iagn
osti
cpr
oced
ure
san
dn
onop
erat
ive
proc
edu
res,
leve
l2M
2901
200
M29
0120
1M
2901
210
M29
0121
1
Nec
ksk
in,D
iagn
osti
cpr
oced
ure
san
dn
onop
erat
ive
proc
edu
res,
leve
l1M
3001
100
M30
0110
1M
3001
110
M30
0111
1
Nec
ksk
in,O
per
ativ
epr
oced
ure
s,le
vel1
M30
0210
0M
3002
101
M30
0211
0M
3002
111
Nec
ksk
in,O
per
ativ
epr
oced
ure
s,le
vel2
M30
0220
0M
3002
201
M30
0221
0M
3002
211
Nec
ksk
in,O
per
ativ
epr
oced
ure
s,le
vel3
M30
0230
0M
3002
301
M30
0231
0M
3002
311
Car
otid
arte
ry,O
per
ativ
epr
oced
ure
s,le
vel1
M32
0210
0M
3202
101
M32
0211
0M
3202
111
Car
otid
arte
ry,O
per
ativ
epr
oced
ure
s,le
vel2
M32
0220
0M
3202
201
M32
0221
0M
3202
211
Cer
vica
llym
phn
odes
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gnos
tic
proc
edu
res
and
non
oper
ativ
epr
oced
ure
s,le
vel1
M33
0110
0M
3301
101
M33
0111
0M
3301
111
Cer
vica
llym
phn
odes
,Dia
gnos
tic
proc
edu
res
and
non
oper
ativ
epr
oced
ure
s,le
vel2
M33
0120
0M
3301
201
M33
0121
0M
3301
211
International Journal of Dentistry 9T
abl
e5:
Con
tin
ued
.
Des
crip
tion
ofor
alh
ealt
hca
rese
rvic
e(O
HC
S)cl
assi
fica
tion
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out
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Wit
hou
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ith
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CC
wit
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CT
hyro
glos
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ant,
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sion
and
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el1
M35
0410
0M
3504
101
M35
0411
0M
3504
111
Thy
rogl
ossa
lrem
inan
t,In
cisi
onan
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xcis
ion
orde
stru
ctio
n,l
evel
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3504
200
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0420
1M
3504
210
M35
0421
1Li
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cisi
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xcis
ion
orde
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ctio
n,l
evel
1M
3604
100
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0410
1M
3604
110
M36
0411
1Li
p,In
cisi
onan
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ctio
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3604
200
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0420
1M
3604
210
M36
0421
1Li
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ror
reco
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ruct
ion
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el1
M36
0610
0M
3606
101
M36
0611
0M
3606
111
Lip,
Rep
air
orre
con
stru
ctio
n,l
evel
2M
3606
200
M36
0620
1M
3606
210
M36
0621
1Fl
oor
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outh
,In
cisi
onan
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xcis
ion
orde
stru
ctio
n,l
evel
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100
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0410
1M
3804
110
M38
0411
1M
outh
,Dia
gnos
tic
proc
edu
res
and
non
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ativ
epr
oced
ure
s,le
vel1
M39
0110
0M
3901
101
M39
0111
0M
3901
111
Mou
th,M
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llan
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oced
ure
s,le
vel1
M39
0310
0M
3903
101
M39
0311
0M
3903
111
Mou
th,I
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sion
and
Exc
isio
nor
dest
ruct
ion
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el1
M39
0410
0M
3904
101
M39
0411
0M
3904
111
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and
Exc
isio
nor
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el2
M39
0420
0M
3904
201
M39
0421
0M
3904
211
Mou
th,R
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ror
reco
nst
ruct
ion
,lev
el1
M39
0610
0M
3906
101
M39
0611
0M
3906
111
Ton
gue,
Inci
sion
and
Exc
isio
nor
dest
ruct
ion
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el1
M40
0410
0M
4004
101
M40
0411
0M
4004
111
Dec
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ous
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h,G
ener
alpr
oced
ure
s,le
vel1
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1010
0M
4210
101
M42
1011
0M
4210
111
Perm
anen
tte
eth
,Gen
eral
proc
edu
res,
leve
l1M
4310
100
M43
1010
1M
4310
110
M43
1011
1Pe
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ent
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oced
ure
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vel2
M43
1020
0M
4310
201
M43
1021
0M
4310
211
Soft
pala
te,R
epai
ror
reco
nst
ruct
ion
,lev
el1
M46
0610
0M
4606
101
M46
0611
0M
4606
111
Soft
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te,R
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ror
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nst
ruct
ion
,lev
el2
M46
0620
0M
4606
201
M46
0621
0M
4606
211
Uvu
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ror
reco
nst
ruct
ion
,lev
el1
M47
0610
0M
4706
101
M47
0611
0M
4706
111
Uvu
la,R
epai
ror
reco
nst
ruct
ion
,lev
el2
M47
0620
0M
4706
201
M47
0621
0M
4706
211
Uvu
la,O
ther
proc
edu
res
and
oper
atio
ns
onor
alca
vity
,lev
el1
M47
9910
0M
4799
101
M47
9911
0M
4799
111
Uvu
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ther
proc
edu
res
and
oper
atio
ns
onor
alca
vity
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el2
M47
9920
0M
4799
201
M47
9921
0M
4799
211
Uvu
la,O
ther
proc
edu
res
and
oper
atio
ns
onor
alca
vity
,lev
el3
M47
9930
0M
4799
301
M47
9931
0M
4799
311
Ora
lexa
min
atio
n,O
rale
xam
inat
ion
proc
edu
res,
leve
l1D
0121
100
D01
2110
1D
0121
110
D01
2111
1R
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gnos
tic
imag
ing,
Intr
aora
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el1
D02
2210
0D
0222
101
D02
2211
0D
0222
111
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iagn
osti
cim
agin
g,E
xtra
oral
film
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el1
D02
2310
0D
0223
101
D02
2311
0D
0223
111
Pre
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Den
tist
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proc
edu
res,
leve
l1D
0324
100
D03
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0324
110
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2411
1To
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Res
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0526
101
D05
2611
0D
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111
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2710
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2711
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0527
111
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D05
2720
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0527
201
D05
2721
0D
0527
211
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on,C
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ns
only
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el1
D05
3010
0D
0530
101
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3011
0D
0530
111
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on,C
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ns
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,lev
el2
D05
3020
0D
0530
201
D05
3021
0D
0530
211
En
dodo
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En
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cTr
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ent
proc
edu
res,
leve
l2D
0631
200
D06
3120
1D
0631
210
D06
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D06
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0633
101
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3311
0D
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111
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210
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210
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3421
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3511
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0735
111
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0736
101
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3611
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0736
111
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3621
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0736
211
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ovab
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l1D
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201
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3721
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0837
211
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iner
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el2
D08
3820
0D
0838
201
D08
3821
0D
0838
211
10 International Journal of DentistryT
abl
e5:
Con
tin
ued
.
Des
crip
tion
ofor
alh
ealt
hca
rese
rvic
e(O
HC
S)cl
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fica
tion
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out
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hou
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5110
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101
D12
5111
0D
1251
111
Two
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111
Two
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Dan
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edu
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edu
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M=
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A=
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ia,C
C=
com
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atio
nan
dco
mor
bidi
ty.
International Journal of Dentistry 11
was reliable and could possibly be utilized as a first version.However, many points need to be discussed.
4.1. Coding. In Thailand, the healthcare system has imple-mented ICD-10 for Dx and ICD-9-CM for Proc for manyyears. Recently, ICD-10-TM has been implemented to pro-vide more details in the OHCS coding by modifying itwith International Classification of Disease to Dentistry andStomatology (ICD-DA) for Dx and CDT for Proc. The mostrecent modification of the codes was finished in 2003 [23,24]. Thus, the ICD-10-TM provides an advantage in termsof accuracy and comprehensive coverage for Dx and Proc. Itis unique, but similar to the CDT and matched with Proc oneby one while ICD-9-CM has many Proc for each code. Thesedifferences indicate that ICD-10-TM was suitable, althoughchallenging, for this study.
4.2. Classification. The development of the new casemix clas-sification for OHCS concentrated on practical application ofthe IR-DRG that was instituted by 3M Health InformationSystem. IR-DRG was able to classify inpatient and outpatientstatus and was also useful for appraising the potential forreplacement on both short stay and ambulatory treatments[31]. Taking this fact into consideration, the new casemixclassification was classified by the nature of the patients’procedures rather than by their diagnoses. This classificationsystem was developed to allow the translation of dentalprocedures into eight-digit codes using various variables toobtain a homogenous resource group.
4.3. Costs. There are a variety of methods for estimating theprovider’s cost. However, each method has limitations. Thecost of OHCS varies depending upon several factors: thecharacteristics of the OHCS, the scope and complexity ofthe treatment, the specialty and experience of physician, thehigh investment cost, and the location of the practice. It wasdifficult to measure the total submitted charges for cases ineach OHCS classification. Therefore, the cost in this studywas calculated based on the use of the patient payment toestimate the provider’s cost.
It was expected that this method would be suitable tocalibrate the OHCS classification in this study. However,a future study using a resource-based relative value scale(RBRVS) would be recommended. Because RBRVS is aschema that is used to calculate what medical providersshould be paid, it assigns a relative value unit (RVUs) toeach physician service that is based on three items: thephysician, the practice expense, and the malpractice expense.This schema is currently used by Medicare in the UnitedStates and by nearly all Health Maintenance Organizations(HMOs) [32–34]. In 2009, Relative Value Studies Incorpo-rated (RVSI) of Denver, Colorado developed Relative Valuesfor Dentists (RVD), a RBRVS for dentistry that is currentlyindexed to the Current Dental Terminology (CDT) andsupplemented by additional coding as recommended bypracticing dentists [35].
4.4. Calibration and Payment. Because of the wide range ofcosts among the set of P, D, M, inpatient, and outpatientcategories, the weight should reflect the relative cost ofproviding care and the health resources required in eachDRG. A CV of less than one and a higher RIV wouldbe expected in the new OHCS classification. Thus, theRIV, RW, and base rate characteristics were split into threemain treatment groups consisting of P, D, and M and twopatient groups consisting of inpatient and outpatient for thefollowing reasons.
(i) The higher RIV reflects the better performance of thegrouping. However, P had the lowest RIV in bothinpatient and outpatient groups because P includedmultiple procedures in one visit, and in some casesP had M and D in one visit. P also had more dataand variation than did the other groups. The RIVof M of the inpatient group was lower than the RIVof M of the outpatient group because all inpatientprocedures were major surgeries with GA, complex,and costly procedures. D had the highest RIV inthe outpatient group because all procedures in theoutpatient group were minor surgeries, tooth andperiodontium treatment, without GA.
(ii) The procedures of each group were different accord-ing to the anatomy group, root operation, and totalprocedures in one visit.
(iii) Elementary procedures in the OHCS were wildlydifferent in each group. The OHCS was mostlyfocused on handiwork. OHCS was intensively skilled,time-consuming labor with a high investment costfor the equipment, instruments, and materials [36].
Taken together, this new OHCS grouper has beenpotentially implemented in Thailand. However, in somecountries that use ICD-10 for Dx, ICD-9-CM for Proc andDRG for budget allocation, this information of the mappingprocess could be used as a guideline to further develop theirown systems. Moreover, the benefits of the DRG grouper forOHCS could be used for expenditure estimation, resourceallocation, payment, and oral healthcare finance focus.
4.5. Limitation. The problems related to the implementationof a new casemix classification for OHCS are elaborated asfollows.
(i) Although computerized information systems arewidely used in Thailand, only a few hospitals pro-vided good clinical data that were ready to use [11].This was an important issue for OHCS informationbecause ICD-10 and ICD-9-CM were not commonlyused for recording with the same standardization.This problem was likely due to the limited data fromOHCS in Thailand, which could not support anOHCS grouper.
12 International Journal of Dentistry
(ii) The diagnoses and procedures of the OHCS codingsystem are scattered throughout the ICD-10 andICD-9-CM, making them difficult to find and use.Moreover, currently OHCS codings are not beingused effectively in dentistry.
(iii) The OHCS patient data from this study did notinvolve patients from university hospitals becausethe patients in university hospitals had more het-erogeneity in their diagnoses and services than didother hospitals. In addition, OHCS classificationsubgroups may be needed to more precisely describethe resource consumption in the university hospitalsetting.
(iv) There were 1,624 OHCS classifications. In this pilotstudy, the data were limited and were not sufficient tosupport the OHCS grouper. A large number of OHCSclassifications might be difficult to handle as a goodpayment tool. In the future, the OHCS classificationshould decrease the number of groups to providemore efficiency and effectiveness in payment.
(v) OHCS cost weights were calculated using only costdata from some areas that might not be applicableto all hospitals in Thailand. This indicated that anexpanded number of cases and data from additionalhospitals would give a more exact cost weight.
5. Conclusion
This study demonstrated the validity of the new OHCSclassification, showing high homogeneity of the cases withineach group and heterogeneity of the cases between eachgroup. Furthermore, it could be used to predict andcontrol production costs. Therefore, this OHCS casemixclassification has the potential to be used in global decision-making in the future. Moreover, some countries using ICD-10 for diagnoses, ICD-9-CM for procedures, and DRGgrouper for budget allocation might be able to apply thismapping process as a guideline to develop their own system,which might benefit from the use of the DRG grouper forexpenditure estimation, resource allocation, payment, andhealthcare finance focus.
Acknowledgments
The authors would like to thank Monbukagakusho schol-arship and Chulalongkorn University Centenary AcademicDevelopment Project for support this research. They alsothank the staffs of Chonburi, Phrapokklao Chantaburi, andQueen Sirikit hospitals that provided helpful data han-dling, Assistant Professor Yosananda Chantravekin and Dr.Kanjana Singkharotai for reviewing the ICD-10-TM codesrelated to OHCS, and Mr. Monthon Buakaew from MOPHfor grouping. Finally, thanks are due to an anonymousperson for helpful comments on the paper.
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