Exploring the Association between Maternal Health Literacy and Pediatric Healthcare Utilization

Exploring the Association between Maternal Health Literacy and

Pediatric Healthcare Utilization:

Is Low Health Literacy a Barrier of Concern?

Rosemary FrassoDissertation Committee

Chair ~ Phyllis Solomon, PhD Steve Marcus PhD

Ian Bennett, MD, PhD

Agency for Healthcare Research and Quality Dissertation Grant

1 R36 HS017471-01

Agenda

• Background and Significance • Methods • Results • Discussion• Limitations and Lessons Learned• Next Steps

Background

Health Literacy (HL)“the degree to which individuals have

the capacity to obtain, process, and understand basic health

information and services needed to make appropriate health decisions”

DHHS, 20003

Background

We know

Women with low health literacy have poor health outcomes and underutilize preventive care

Background

We know

Appropriate use of pediatric preventive care is associated with significant reductions in morbidity and mortality and has been shown to reduce healthcare costs and decrease hospital admissions

Significance

• We don’t know– Are children of mothers with low health

literacy at a disadvantage similar to that of their mothers?

• Conflicting evidence about the impact of maternal HL on pediatric social and health outcomes – Pati et al (2011) -TANF/Vaccination compliance

Methods

Mix methods • Quantitative (secondary data analysis)

• Qualitative• 14 semi-structured interviews• 11 different mothers with varied HL• 1 critical case exploration

MOTHERS FROM THE PARENT

STUDY(REALM)

CHILDREN FROM THE MEDICAID CLAIM DATA

185 DYADS

Parent Study

• Community based prospective cohort study of mothers and infants in Philadelphia– Investigating the contextual, social, behavioral,

and family context of maternal child health (extensive surveys)

– Followed from prenatal period to 24 months post partum

– >5000 participants – 1034 had health literacy assessments – REALM / STOFHLA

• Funded by the CDC and National Institute of Child Health and Development 8

CDC (TS 312 15/15; Culhane) and NICHD (1R01 D36462 01A; Elo and Culhane)

Operationalized Independent Variables

Predisposing

Enabling

Demographic characteristics, such as race, age, and

maternal education have been shown to impact parent

driven pediatric health service useHere Andersen grouped

personal and family factors including social supports,

income, insurance & physical access to providers

Need, the strongest predictor of health service use based

on how people view their own functional capacity,

symptoms, & general state of health

(and that of the children they care for)

Dependent Variables Operationalized

Well- Child Visits Year 1 /Year 2

The primary outcome measure of preventive care utilization is the overall number of documented well-child visits in the first two years of lifeThe AAP recommends 7 WCV in year 1 of life and 3 in year 2 of life

ED. SCV, % Compliance

CPT and ICD-9 Codes were used to identify these visits in the Medicaid claims files AAP, 2011

ED Visits Year 1 /Year 2

Sick - Child Visits Year 1

/Year 2(SCV)

% Compliant Year 1 /Year 2

Andersen’s Model Modified

Maternal Health Literacy and Outcomes of Interest

Year 1 of LifePrimary Study

Outcomes Year 1

Mothers with REALM Scores

< 6th gradeN=25

Mothers with REALM Scores7th & 8th grade

N = 61

>9th gradeN=90

p-value(N)

Well Child Visits mean (range) 3.8 (0,10) 3.5 (0,7) 3.4(0,8) 0.68

Well Child Visits % > 4 / YR 1 56.0 50.8 47.8 0.76

Sick Child Visits mean (range) 2.7(0,10) 2.2 (0,16) 2.0(0,11) 0.46

ED Visits mean (range) 2(0,8) 2.1(0,13) 1.6(0,7) 0.72

Quantitative Analysis Revealed

• HL was not associated with the number of well-child visits, sick-child visits, ED visits or % compliance with a minimum number of visits in year 1 and year 2 of life

• HL did not prove to mediate or moderate the relationships between any of predisposing and enabling factors under study and our outcomes of interest

• Higher health literacy was not protective in this population

Frequency Distribution Well-Child Visits

Year 1

0 2 4 6 8 10Well child visits in the first year of life

AAP Recommends 7 82% of US children in

this age group are meeting this guideline

Frequency Distribution Well-Child Visits

Year 2

0 2 4 6 8Well child visits in the second year of life

AAP Recommends 3 WCV

Qualitative Analysis Revealed

• Women with low HL and women higher HL encountered an overlapping set of challenges when navigating the healthcare system

• Several themes emerged and were used to elaborate on Andersen’s Model and shed light on the quantitative findings and a critical case emerged

Predisposing Enabling Need

DemographicsRace/Ethnicity Nativity *Age Education *Literacy• Health literacy• Ability to function w/o

reading Language Housing Social Structure Marital Status Parity* Few competing demands

Compromising Factors Low literacy Low health literacy Learning disabilities • Dyslexia No coping strategy for dealing with literacy barriers Parity high – too many competing demands Mental Illness

Personal /Family ResourcesIncome People @ home Financial Support Employment *†

Insurance Community Resources• Physical access to care• Availability/Convenience• Time in community /strength

of ties Social support LiteracyStrategies for working around low literacy Access to sources of health information InternetAccess to information Communication Having an advocate Continuity of carePrior satisfaction with a healthcare provider Disabling FactorsPower imbalanceLack of an advocate Limited or no access to health information Administrative/logistic hassles† Work gets in the way (unemployment)

Need FactorsViews & evaluation of the child’s functional capacity, symptoms, & general state of health Informed by health beliefs, values about health and illness & attitudes towards about health services (trust, respect†) and knowledge about health (literacy, access to information in order to appreciate need††). † Feeling respected by the provider and healthcare staff † Your opinion about your child’s health matters †† e.g. knowing when and what vaccinations a child needs Sources of information (lay, pseudo experts, experts) Compromises Ability to Assess Need Low Literacy Low Health LiteracyCompeting demands Lack of trust for the health care system or individual providers 17

Thank You

Special Thanks To

Phyllis Solomon, PhDSteven Marcus, PhD

Ian Bennett, MD, PhD Leny Mathew, MS

Jennifer Culhane, PhD, MPHAll the members of

Dr. Culhane’s Paper GroupSara Cullen, MSW

And of course my terrific kids for all their love, patience and support

Some References (others available upon request)

• Agency for Healthcare Research and Quality. (2011, March 28). Low Health Literacy Linked to Higher Risk of Death and More Emergency Room Visits and Hospitalizations. Retrieved from http://www.ahrq.gov/news/press/pr2011/lowhlitpr.htm

• Andersen, R. M. (1995). Revisiting the behavioral model and access to medical care: Does it matter? J Health Soc Behav, 36(1), 1-10.

• Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual

• Berkman, N. D., Dewalt, D. A., Pignone, M. P., Sheridan, S. L., Lohr, K. N., Lux, L., Bonito, A. J. (2004). Literacy and health outcomes. Evid Rep Technol Assess (Summ), (87), 1-8.

• American Academy of Pediatrics, Committee on Practice and Ambulatory Medicine. (2000). Recommedations for preventive pediatric health care.

• Hakim, R. B., & Bye, B. V. (2001). Effectiveness of compliance with pediatric preventive care guidelines among Medicaid beneficiaries. Pediatrics, 108(1), 90-97.

• Shulman, S. (2006). Poor preventive care achievement and program retention among low birth weight infant Medicaid enrollees. Pediatrics, 118(5), e1509-1515. doi: peds.2004-0489 [pii] 10.1542/peds.2004-0489

Measuring Health Literacy

• Rapid Assessment of Adult Literacy in Medicine– REALM – 66 items – Word familiarity – Approximately three minutes

• Short Test of Functional Health Literacy in Adults– STOFHLA– 36 items – Functional health literacy– Approximately 7 minutes

(Baker, Williams, Parker, Gazmararian, & Nurss, 1999; Davis, Bocchini, et al., 1996; Davis, et al., 1993; Davis, et al., 1994; Moon, et al., 1998)

A Critical Case Emerges Back ground and significance:

•Dyslexia affects 5-17% of adults in the US•No significant difference in the prevalence across socioeconomic strata•Undiagnosed dyslexia, is more common among the poor

Methods: •Four in depth interviews•Participant graduated from high school and had attended community college •Diagnosed with severe dyslexia (mid 20s) had no intervention.

Results: •Poor readers with dyslexia may be difficult to identify•Strategies used to compensate for LD may render common HL screening tools ineffective •REALM did not identify this participant

Conclusions and Implications: •Strategies employed by persons w/ LD may fail in the healthcare setting•Strategies are not well suited for HC where anxiety is high and accuracy is crucial•HL interventions may not be effective in the context of dyslexia or other learning disabilities

Missed Opportunities

“Yes, but I, but I’m like, OK, it prevents cancer, is there any side effects from

it, he’s like no, no, it’s in the pamphlet and I’m like, I see that, I

understand that, I understand it was on paper, but it’s different when you

hear it from someone. And I just wish he would’ve had more of a

conversation about it, ‘cause it was like, no, I, everybody’s getting it, and

I’m like OK?” Note:

This participant declined the HPV vaccine for her daughter, who she generally relies on to translate written materials.

Benefit of Mix Methods

• New Concepts – Lay informants – Pseudo experts– Experts

• Confirmation – Parity – Employment

• Unexpected findings (dyslexia example)

“I don’t take advice from

family or friends as much as I would a doctor”

“I would call

hospital…... I

reprimanded

for calling”“My cousin is

in nursing school”

“Friends, but

their kids are

younger so

they don’t

know”

REALM Grade Equivalent Scores

Raw Score

Grade Equival

Task Examples Trichotomized

61-66 High School

Will be able to read most patient education materials

>9th Grade(strongest )

45-60 7th & 8th Grade

Will struggle with most patient education materials

7th & 8th Grade(middle)

19-44 4th – 6th Grade

Will need low literacy materials, may not be able to read

prescription labelsLow Health

Literacy0-18 <3rd

GradeWill not be able to read most low literacy materials; will need plain

language and repeated oral instructions

(illustrations, audio, video) 30

Dependent Variables Operationalized

Compliant Year 1(WCV)

Compliant Year 2(WCV)

Shulmen, 200631

We also documented the percent of dyads that were compliant with a minimum number of WCV per year

There is a precedent in the literature for setting this bench-mark at 4 for year 1 and 2 for year 2 of life, slightly lower than the AAP recommendations

CPT and ICD-9 Codes were used to identify these visits in the Medicaid claims files

Hypotheses

Mothers with low health literacy (< 6th grade) will be less likely than mothers with marginal to higher health literacy (> 7th grade) to meet pediatric preventive care recommendations.

Hypotheses

Children of mothers with low health literacy (< 6th grade) will be more likely than children of mothers with marginal to high health literacy (> 7th grade) to

•visit an emergency room.

•be seen by a provider for a sick-child visit.

Hypotheses

Low maternal health literacy will mediate the relationship between negative predisposing and enabling factors and

•timely receipt of pediatric preventive care.

•pediatric emergency room visits.

•the number of sick-child visits.34

Hypotheses

Low maternal health literacy will moderate the relationship between negative predisposing and enabling factors and

•timely receipt of pediatric preventive care.

•pediatric emergency room visits.

•the number of sick-child visits.35

Quantitative Analysis• Categorical Variable

– Chi-squared test of independence

• Continuous Variables– Wilcoxon rank-sum test (Mann-Whitney-

Wilcoxon) or Kruskal-Wallis non-parametric test

• Linear Regression– Moderation Analysis– Mediation Analysis

• Likelihood ratio test • STATA Data Analysis Statistical Software

Qualitative Methods

• In depth semi structured interviews– Issues of interest

• Need factors / perceived need• Health beliefs• Social support/relationships• Ability to navigate the healthcare system

• Transcribed verbatim • Coded using NVIVO8 (QSR) software

guided by Andersen’s model

Guiding Qualitative Hypotheses

Qualitative interviews will show that mothers with low health literacy will

report different issues related to access to preventive pediatric care than mothers with marginal to high

health literacy.

Additionally, they will perceive different barriers to care and will suggest different interventions

to reduce these barriers.

The Analytic Sample

Quantitative

• 84% African American

• 5% White • 8% Latina• 89% Born in

the US• All inner-city • > 19 years of

age • 84% completed

HS• Enrollment 1st

prenatal visit (14.8 ± 0.2 weeks)• PH Centers in

Philadelphia• February 2000 -

October 2002• Income (75%

<$11,610/yr)• Children had >10

months of …Medicaid eligibility/yr

• 14% low HL

Non English Speakers (ESL OK)

Results

Andersen’s Model Modified

Pathway 1

<20 20 - <25 25 - < 30 > 300%

>9th7th-8th< 6th

Percent of Participants in Each Age Group by Health Literacy Level

Maternal Age

Post High School

High School or GED

Less than High School

>9th7th-8th< 6th

Percent of Participants in Education Group by Health Literacy Level

Maternal Education

Pathway 2

• Predisposing • Race• Nativity• Age• Education• First Language• Marital Status • Parity

• Enabling• Income• Number of people supported by income• Any other financial support • SSI and Unemployment /WMC • Money left over at the end of the month• Worried about Money • Insurance

Statistically Significant Associations

• Predisposing • Race• Nativity• Age• Education• First Language• Marital Status • Parity

• Enabling• Income• Number of people supported by income• Any other financial support • SSI and Unemployment /WMC • Money left over at the end of the month• Worried about Money • Insurance

• Predisposing • Race

• Age

• Marital Status • Parity

• Enabling

• SSI and Unemployment /WMC

• Insurance

Paritymedian (range) / p –value < 0.05*

-ED Visits 1 / 0.01*

1 child 1 (0-13)2+ children 0 (0-8)

-ED Visits 1 / 0.01*

1 child 1 (0-13)2+ children 0 (0-8)

-WCV YR 1 / 0.02* 1 child 4 (0-7)2+ children 3 (0-10)

-SCV YR 2 / 0.01* 1 child 1 (0-9)2+ children 0 (0-6)

Racemedian (range) / p –value < 0.05*

- ED visits YR 1/ 0.001*

Non Hispanic Whites 0.5 (0 – 5)Latina 3 (0-8)Non Hispanic Black 1 (1 -13)Other 0 (0 -0)

Agemedian (range) / p –value < 0.05*

- ED visits YR 1/ 0.03*

< 20 2 (0 -13)20-<25 1 (0 -10)25-<30 0.5 (0 -6)> 30 1 (0 – 8)

Languagemedian (range) / p –value < 0.05*

- ED visits YR 1/ 0.05* Eng (yes) 1 (0-13)Eng (no) 3 (0-8)

Marriedmedian (range) / p –value < 0.05*

- ED visits YR 1/ 0.03* M (yes) 1 (0-7)M (no) 3 (0-13) 48

Unemployment/Workman’s Comp

median (range) / p –value < 0.05*- WCV YR 2 / 0.04* Received(yes) 2.5 (1-4)Received(no) 1 (0-9)

- SCV YR 1 / 0.02* M (yes) 1.5 (1-4)M (no) 0 (0-9)

Mothers Insurance Status @ Enrollment

median (range) / p –value < 0.05*

- WCV YR 2 / 0.01* Private 1 (0-3)Medicaid 1 (0-5)Uninsured 2 (0-9)

Languagemedian (range) / p –value < 0.05*

- Compliant YR 2/ 0.05* Eng (yes) 1 (0-13)Eng (no) 3 (0-8)

Marriedmedian (range) / p –value < 0.05*

- ED visits YR 1/ 0.03* M (yes) 1 (0-7)M (no) 3 (0-13) 51

% Compliant Year 2

Education (P-value 0.02*)

Post HS 70% > 2 visits year 2 HS or GED 50% > 2 visits year 2 < HS 37% > 2 visits year 2

Maternal Insurance Status (P-value 0.02*)Private 41% > 2 visits year

2Medicaid 29% > 2 visits year

2Uninsured 63% > 2 visits year

Pathway 3 and Mediation

Maternal Health

LiteracyMediator

Primary Study Outcomes

Year 2 of Life

< 6th gradeN=22

7th & 8th gradeN=55

>9th gradeN=64

p-value{N(%)}

Well-Child Visits Median (range) 1(0,7) 1(0,9) 2(0,5) 0.89

% Compliant (> 2/yr) 41 49 52 0.68

No Visits N (%) 5(18.5) 10(37.0) 12(44.5)0.85(27)

Sick-Child Visits Mean (range) 1.4(0,9) 1.1(0,16) 1.1(0,7) 0.60 No Visits N(%) 9(12.3) 27(37.0) 37(57.7) 0.34ED Visits Mean (range) 1.1(0,6) 1.3(0,11) 1.0(0,6) 0.87 No Visits N(%) 12(17.7) 25(36.7) 31(45.6) 0.77

Primary Study Outcomes

Year 1 of Life

< 6th gradeN=25

7th & 8th gradeN = 61

>9th gradeN=90

p-value(N)

Well-Child VisitsMedian (range) 4 (0,10) 4 (0,7) 3 (0,8) 0.68

% Compliant (> 4/yr) 56.0 50.8 47.8 0.76

No Visits N(%) 1(9.0) 5(45.5) 5(45.5)0.71(11)

Sick-Child Visits Mean (range) 2.7(0,10) 2.2 (0,16) 2.0(0,11) 0.46 No Visits N(%) 6(9.8) 22(36.1) 33(54.1) 0.48ED Visits Mean (range) 2(0,8) 2.1(0,13) 1.6(0,7) 0.72 No Visits N(%) 9(14.5) 19(30.7) 34(54.8) 0.70

Controlling for the REALM ~ Likelihood Ratio Tests

Model 1IV DV

Add REALM = Model 2 IV DV

Compare models 1&2 LR Chi2 (p–value)

Parity + WCV yr 1

Parity + REALM + WCV yr 1

Parity + SCV yr 2

Parity + REALM + SCV yr 2

Parity + EDV yr 1

Parity + REALM + EDV yr 1

Parity + EDV yr 2

Parity + REALM + EDV yr 2

Race + EDV yr 1

Race + REALM + EDV yr 1

Age + EDV yr 2

Age + REALM + EDV yr 2

1st Lang + EDV yr 2

1st Lang+ REALM + EDV yr 2

Married + EDV yr 2

Married + REALM + EDV yr 2

UE/WC + EDV yr 2

UE/WC + REALM + EDV yr 2

UE/WC + EDV yr 2

UE/WC + REALM + EDV yr 2

Insurance + EDV yr 2

Insurance + REALM + EDV yr 2

1.49 (0.48)

1.77 (0.41)

0.29 (0.87)

1.09 (0.58)

0.51 (0.76)

1.89 (0.39)1.65 (0.44)

0.39 (0.82)

0.33 (0.85)

0.56 (0.76)

1.02 (0.60)

Pathway 4Moderation

Well-Child Care Sick-Child Care ED Visits % Compliance

(Minimum # of visits/year)

Parity

REALM(categorical)

Parity X

REALM Planned Analysis

Barron & Kenny, 1986

Quantitative Analysis Revealed

• HL was not associated with the number of well-child visits, sick-child visits, ED visits or % compliance with a minimum number of visits in year 1 and year 2 of life

• When we controlled for health literacy we saw no impact on establish associations between a set of independent variables and our outcome variables

Associations of Interest

• 66% of the women in our sample had completed high school or GED however only 50% had a REALM score > 9th grade

• 100% of the women in the highest HL

group were born in the US while that was the case for only 80% of the women in the low HL group

Qualitative Analysis Revealed

• Women with low HL and women higher HL encountered an overlapping set of challenges when navigating the healthcare system

• Confirmed the quantitative findings (for the most part kids are getting the minimum number of visits)

• Several themes emerged and were used to elaborate on Andersen’s Model and shed light on the quantitative findings

• Critical case emerged 58

DemographicsRace/Ethnicity Nativity Age Education LiteracyLanguage Housing Social Structure Marital Status Parity

Personal /Family ResourcesIncome People @ home Financial Support EmploymentInsurance Community Resources

Need FactorsViews & evaluation of the child’s functional capacity, symptoms, & general state of health Informed by health beliefs, values about health and illness & attitudes towards about health services and knowledge about health

Discussion

Compromising Factors Low literacy Low health literacy Learning disabilities Dyslexia No coping strategy for dealing with .. literacy barriers Parity high too many competing demandsMental Illness

* IV in the quantitative analysis and a theme in the qualitative analysis

of ties .Social support LiteracyStrategies for working around low literacy Access to sources of health information InternetAccess to information Communication Having an advocate Continuity of carePrior satisfaction with a healthcare provider Disabling FactorsPower imbalanceLack of an advocate Limited or no access to health information Administrative/logistic hassles† Work gets in the way (unemployment)

Benefit of Mix Methods

• New Concepts – Lay informants – Pseudo experts– Experts

• Confirmation – Parity – Employment

• Unexpected findings (dyslexia example)

“I don’t take advice from

family or friends as much as I would a doctor”

“I would call

hospital…... I

reprimanded

for calling”“My cousin is

in nursing school”

“Friends, but

their kids are

younger so

they don’t

know”

Compromising Factors Low literacy Low health literacy Learning disabilities Dyslexia No coping strategy for dealing with .. literacy barriers Parity high too many competing demandsMental Illness

of ties .Social support LiteracyStrategies for working around low literacy Access to sources of health information InternetAccess to information Communication Having an advocate Continuity of carePrior satisfaction with a healthcare provider Disabling FactorsPower imbalanceLack of an advocate Limited or no access to health information Administrative/logistic hassles† Work gets in the way (unemployment)

A Critical Case Emerges Back ground and significance:

•Dyslexia affects 5-17% of adults in the US•No significant difference in the prevalence across socioeconomic strata•Undiagnosed dyslexia, is more common among the poor

Methods: •Four in depth interviews•Participant graduated from high school and had attended community college •Diagnosed with severe dyslexia (mid 20s) had no intervention.

Results: •Poor readers with dyslexia may be difficult to identify•Strategies used to compensate for LD may render common HL screening tools ineffective •REALM did not identify this participant

Conclusions and Implications: •Strategies employed by persons w/ LD may fail in the healthcare setting•Strategies are not well suited for HC where anxiety is high and accuracy is crucial•HL interventions may not be effective in the context of dyslexia or other learning disabilities

Compromising Factors Low literacy Low health literacy Learning disabilities • Dyslexia No coping strategy for dealing with literacy barriers Parity high – too many competing demands Mental Illness

of ties Social support LiteracyStrategies for working around low literacy Access to sources of health information InternetAccess to information Communication Having an advocate Continuity of carePrior satisfaction with a healthcare provider Disabling FactorsPower imbalanceLack of an advocate Limited or no access to health information Administrative/logistic hassles† Work gets in the way (unemployment)

Missed Opportunities

“Yes, but I, but I’m like, OK, it prevents cancer, is there any side effects from

it, he’s like no, no, it’s in the pamphlet and I’m like, I see that, I

understand that, I understand it was on paper, but it’s different when you

hear it from someone. And I just wish he would’ve had more of a

conversation about it, ‘cause it was like, no, I, everybody’s getting it, and

I’m like OK?” Note:

This participant declined the HPV vaccine for her daughter, who she generally relies on to translate written materials.

Health Literacy

• 50% of the group was compliant in year 1 and this did not vary by health literacy

• 44% of the group was compliant in year 2 and again no variation by health literacy

Does health literacy matter in this population?

Limitations & Lessons Learned

• Sample size / power• Inclusion criteria

– 10 month of eligibility

• Locating the poorest readers • REALM

– Was it reliable in the population? – Does it need to be validated in the context of

• Did not take full advantage of the

available data* • Limited generalizability and transferability 67

Next Steps

• Augment the current analysis and submit a paper for publication – Abstract has been sent to APHA

• Critical Case was presented at Health Literacy Annual Research Conference – Need to further explore how a learning

disability impacts health literacy

Next Steps Continued

• Now that the dyads have been established we plan to revisit the survey data in order to explore additional research questions (many of which were brought to light in the qualitative arm of the study)

• For example:– Feeling respected by a provider (qualitative)– Mastery Scale and Coping Questions (parent study)

• “Sometimes I feel that I am being pushed around in life” • “There is little I can do to change many of the important things in

life”

• For example:– Depression/mental illness (qualitative)– Depression (parent study)

Some References (others available upon request)

• Agency for Healthcare Research and Quality. (2011, March 28). Low Health Literacy Linked to Higher Risk of Death and More Emergency Room Visits and Hospitalizations. Retrieved from http://www.ahrq.gov/news/press/pr2011/lowhlitpr.htm

• Andersen, R. M. (1995). Revisiting the behavioral model and access to medical care: Does it matter? J Health Soc Behav, 36(1), 1-10.

• Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual

• Berkman, N. D., Dewalt, D. A., Pignone, M. P., Sheridan, S. L., Lohr, K. N., Lux, L., Bonito, A. J. (2004). Literacy and health outcomes. Evid Rep Technol Assess (Summ), (87), 1-8.

• American Academy of Pediatrics, Committee on Practice and Ambulatory Medicine. (2000). Recommedations for preventive pediatric health care.

• Hakim, R. B., & Bye, B. V. (2001). Effectiveness of compliance with pediatric preventive care guidelines among Medicaid beneficiaries. Pediatrics, 108(1), 90-97.

• Shulman, S. (2006). Poor preventive care achievement and program retention among low birth weight infant Medicaid enrollees. Pediatrics, 118(5), e1509-1515. doi: peds.2004-0489 [pii] 10.1542/peds.2004-0489

Exploring the Association between Maternal Health Literacy and Pediatric Healthcare Utilization

Education

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