AMBULATORY PEDIATRICS Volume 4, Number 5442Copyright q 2004 by Ambulatory Pediatric Association September–October 2004

Private Dental and Prescription-Drug Coverage in Children: Data Fromthe Medical Expenditure Panel Survey

Alex Y. Chen, MD, MSHS

Objective.—Most studies on health insurance have examined primarily basic medical insurance coverage; few havelooked at supplemental insurance and/or dental-insurance coverage. Prescription-drug and dental-insurance coverage arebecoming increasingly important due to continued increase in health care costs and changes in cost-sharing structure ofhealth plans. This study examined prescription-drug coverage and dental-insurance coverage in the context of overallinsurance coverage.

Method.—This study utilized the Household Component File from the 2000 Medical Expenditure Panel Survey(MEPS), a national survey on medical care conducted by the Agency for Healthcare Research and Quality (AHRQ).Univariate and bivariate analyses were performed to provide estimates on children’s prescription-drug and dental-insur-ance coverage. Multivariate logistic regression analyses were conducted to identify demographic and socioeconomicfactors that influence coverage.

Results.—In 2000, 68.5% of US children had private insurance, 22.2% had public insurance, and 9.3% were uninsured.Among children with private insurance, only 56.9% had dental-insurance coverage and 76.3% had prescription-drugcoverage. Family income level, maternal education, and race were significant predictors of dental insurance and pre-scription-drug coverage.

Conclusion.—Although significant strides have been made to insure US children, a large percentage of children stilldo not have comprehensive coverage. Even among privately insured children, many are without dental or prescription-drug coverage. Those who were poor, minority, and with low maternal education had lower likelihood of dental andprescription-drug coverage.

KEY WORDS: dental insurance, Medical Expenditure Panel Survey, prescription-drug coverage

Ambulatory Pediatrics 2004;4:442 447

Insurance coverage is an important determinant ofhealth services utilization among children. Uninsuredchildren are less likely to receive needed care for med-

ical, mental health, and dental services.1–4 In addition, un-insured children are more likely to experience adversehealth outcomes.1,3,5 Given the importance of insurancecoverage for the health and well being of children, a num-ber of reforms were initiated to provide and expandhealth-insurance coverage, for example, the State Chil-dren’s Health Insurance Program (SCHIP).1,3,6,7

However, despite these advances, approximately 8%–9% of US children remain without medical insurance cov-erage for the entire year.8 More children are insured onlyintermittently during the year. Even for children with con-tinuous coverage, their benefits may not be sufficient tocover their health care needs.

Increases in prescription-drug costs pose as a nontrivialfinancial barrier to those needing prescription medica-

From the Department of Pediatrics, Children’s Hospital Los An-geles, Keck School of Medicine, University of Southern California,Los Angeles, Calif.

Presented in part at the Pediatric Academic Societies’ AnnualMeeting, San Francisco, Calif, May 2004.

Address correspondence to Alex Y. Chen, MD, MSHS, Divisionof Research on Children, Youth, and Families, Children’s HospitalLos Angeles, 4650 Sunset Blvd, Mail Stop 30, Los Angeles, CA90027 (e-mail: achen@chla.usc.edu).

Received for publication January 21, 2004; accepted May 20,2004.

tions.9,10 Studies have shown differences in prescription-drug utilization pattern between those with prescription-drug coverage and those without,11 with decreased pre-scription-drug use for patients without prescription-drugcoverage.12

In addition, oral health and dental services have be-come a key part of overall health.13,14 Children risk dentalmorbidity because of their age and hygiene. Many chil-dren who have medical insurance may not have dentalcoverage. Lack of dental coverage has been linked to de-creased dental visits.15,16 The US Surgeon General13 alsoreported ‘‘profound disparities’’ in access to dental ser-vices.

For all these reasons, the notion of having medical in-surance is no longer equivalent to having coverage forneeded health care services. The availability of prescrip-tion-drug and dental coverage can lead to differences inutilization and outcome among children. Therefore, it isimportant to examine insurance coverage more broadly intoday’s health care environment.

This study aims to demonstrate that even among chil-dren with health insurance, many lack prescription-drugand dental coverage. One can assume that children withmedical insurance but without prescription-drug and/ordental coverage are at risk for decreased access and uti-lization of necessary services such as prescription medi-cations and dental care. Of course, coverage for healthcare services other than prescription-drug or dental ser-vices can also be an important part of overall coverage.

AMBULATORY PEDIATRICS Pediatric Dental and Prescription-Drug Coverage 443

Besides mental health services (generally covered undermedical insurance), prescription-drug and dental servicesare two of the most highly utilized.

This study focuses primarily on children with privateinsurance. Public insurance programs such as SCHIP donot provide similar levels of access to dental servicesacross all 50 states.17 Medicaid does generally providemore consistent coverage; however, its prescription-drugbenefits are subject to state-specific formulary restrictions.This lack of uniformity makes assessment of public pre-scription-drug and dental programs more difficult.

METHODS

Data Source

The source of data was the public use file for theHousehold Component of the 2000 Medical ExpenditurePanel Survey (MEPS), a national survey on the use ofmedical care conducted by the Agency for Healthcare Re-search and Quality.18 The sample for the 2000 HouseholdComponent was a stratified, nationally representative sam-ple of approximately 24 000 persons in 9500 householdsand excluded residents of nursing or personal care homesor facilities for the mentally retarded. The MEPS designis an overlapping panel design. This means that, at anygiven year, two panels of participants are surveyed, onepanel consists of those that were selected in the previousyear and is followed for the second year, and the otherpanel consists entirely of a new panel of participants se-lected in the current year. This design enables the use ofMEPS data for both cross-sectional and longitudinal stud-ies.

Each family in the Household Component participatedin 3 rounds of data collection each year, those belongingto the newly selected panel will continue to participate in3 more rounds of data collection the following year. Acore questionnaire was administered using computer-as-sisted interviewing (CAI) to obtain information abouteach family member’s health status, use of medical care,medical and dental expenditures, income, and health-in-surance coverage. Different versions of the health-statusitems were used for adults and for children. The expen-diture and utilization data were verified and supplementedthrough surveys of medical providers and pharmacies.The MEPS validates information obtained in the House-hold Component survey by contacting medical providersand pharmacies identified by the household respondents.They were asked to supply information on diagnoses(coded according to ICD-9-CM), physician procedurecodes (classified by CPT-4), inpatient stay codes (classi-fied by Diagnosis Related Groups [DRGs]), prescriptions(coded by National Drug Code [NDC] and medicationname), charges, and payments. The information was col-lected through telephone interviews and mailed surveymaterials.

To construct the analytic file, we selected children 0–17 years of age with a positive person-level survey weightin the year 2000. MEPS intentionally oversampled thepoor, certain population groups, and adults and children

with impairment and limitations in order to provide in-creased precision for analytic purposes. Because of thisoversampling strategy, some observations in MEPS filehave 0 person-level weight. These observations were ex-cluded in the analyses. The analytic file consisted of 7534observations.

Insurance Coverage

Insurance coverage was determined based on responsesto questions in the health-insurance section of the ques-tionnaire. Children were classified as insured if the surveyrespondent reported having coverage through private orpublic health insurance at any point in time during the 3survey rounds. An individual was considered having pri-vate health-insurance coverage if, at a minimum, that cov-erage provided benefits for hospital and physician servicesand the coverage was provided through self, employment,or a union group. An individual was considered havingpublic health-insurance coverage if he/she was not cov-ered by private insurance and received coverage underTricare, Medicaid, Medicare, or other federal and statehospital/physician programs such as SCHIP. Those thathad neither private nor public insurance coverage at any-time were classified as uninsured.

For those who had private health insurance, dental-in-surance coverage and prescription-drug coverage were in-dependently assessed and documented in the survey. Forthose with public health-insurance coverage, MEPS didnot contain specific information on the status of their den-tal or prescription-drug coverage. MEPS did not specifythe rationale for omitting this information.

Dependent and Independent Variables

The dependent variable was insurance coverage. Inde-pendent variables were constructed from factors hypoth-esized to influence insurance coverage for children fromthe existing literature.7,19–25 It consisted of three compo-nents: 1) demographic factors, 2) socioeconomic factors,and 3) health-status variables. In the present study, de-mographic and health-status variables were primarily in-tended as control variables. Socioeconomic variables werevariables of interest. Demographic variables included age,gender, and race. Age was included as a continuous var-iable (range, 0–17 years). Race was represented by indi-cator variables Asian, black, Hispanic, others, and white.Health status variables were self or proxy-rated general-health status, health compared with other children of sim-ilar age, and having frequent cold or illness. General-health status was divided into the following categories:excellent, very good, good, fair, and poor. Health com-pared with other children and having frequent illness wereeach indicator variables. Health-status variables were usedto adjust for the need for health care. Socioeconomic fac-tors included in the regression models were family incomelevel (based on the 2000 US Census poverty line [PL])and maternal education level. Family income levels wererepresented by the following indicator variables: less than100% of poverty line as poor; 100%–124% as near poor;125%–199% as low income; 200%–399% as middle in-

AMBULATORY PEDIATRICS444 Chen

Table 1. Weighted Descriptive Statistics

Category Variable N Percent

Gender

Race/ethnicity

MaleFemaleAsianBlackHispanicWhiteOther

38563678176

128124253593

59

51.448.63.4

15.616.164.00.9

Health status PoorFairGoodVery goodExcellent

88205

129320403908

1.32.6

14.627.753.8

Family income level Poor (,100%)Near poor (100%–124%)Low income (125%–199%)Middle income (200%–399%)High income (400% or more)

1733531

141223541504

16.85.6

15.433.728.5

Maternal education Less than high schoolHigh-school educationBachelor’s degreeMaster’s degree or more

196329271300306

20.547.625.56.4

Table 2. Percentage of US Children With Different Types of Medical Insurance Coverage, by Family-Income Levels

Family-Income Levels(% Poverty Line) N

Percent

Private Insurance Public Insurance Uninsured

Poor (,100)Near poor (100–124)Low income (125–199)Middle income (200–399)High income ($400)

1733531

141223541504

20.435.955.981.894.2

65.649.530.29.81.7

14.014.613.98.44.1

come; and 400% and greater as high income. Maternaleducation was represented by indicator variables less thanhigh-school education, high-school education, bachelor’sdegree, and master’s degree or above. These variableswere selected because of known association with insur-ance coverage and utilization.23–27

Statistical Analysis

Data were prepared using SAS Version 8.2 software(SAS Institute Inc, Cary, NC) and statistical analyses wereperformed using STATA Version 7 software for windows(Stata Corp, College Station, Tex). Descriptive statisticswere computed for the analytical sample, weighted to cor-rect for sampling design and survey nonresponse, yieldingestimates that are representative of the US population.Two multivariate logistic regression analyses were con-ducted. The regressions modeled the likelihood of havingdental-insurance coverage and the likelihood of havingprescription-drug coverage among children who were pri-vately insured. Logistic regression analyses accounted forperson-level survey weights and adjusted for clustering atthe family level.

RESULTS

Overall, in the year 2000, according to MEPS, 68.5%of US children had private medical-insurance coverage atsome point in time during the year, 22.2% had public in-

surance coverage, and 9.3% had no coverage for the entireyear. Among those with private insurance, 51.9% werecovered under a health-maintenance organization-man-aged care plan. Forty-eight percent of those covered undera public plan were in a health maintenance organization.

Table 1 summarizes the weighted descriptive statisticsfor the sample. Table 2 presents the medical-insurancecoverage patterns of US children by family-income levels.In general, from low family income level to high familyincome level, the percent of children insured by privatemedical insurance increased, and the percent of childreninsured by public insurance and those that were uninsureddecreased.

Table 3 summarizes the percentage of dental insuranceand prescription-drug coverage among children who hadprivate insurance, by family-income levels. Overall,68.5% of US children had private medical insurance, butonly 56.9% among them had dental-insurance coverageand 76.3% had prescription-drug coverage. (This table ex-cludes the 22% of US children insured by public programsin 2000.)

Table 4 summarizes findings from the multivariate lo-gistic regression analyses. Both regressions had significantWald chi-square statistics with P values less than .0001.

As illustrated in Table 4, among children with privateinsurance, low family income level has a significant neg-ative association with having dental or prescription-drug

AMBULATORY PEDIATRICS Pediatric Dental and Prescription-Drug Coverage 445

Table 3. Percentage of Children With Private Insurance That AlsoHad Dental or Prescription-Drug Coverage, by Family-Income Lev-els

Family-Income Levels(% Poverty Line) N

Percent

DentalInsurance

Prescription-Drug

Coverage

Poor (,100)Near poor (100–124)Low income (125–199)Middle income (200–399)High income ($400)

315161733

18281399

43.030.348.757.063.2

57.346.066.275.485.1

Table 4. Odds Ratio (OR) and 95% Confidence Interval (CI) of Logistic Regression Models for Having Dental Coverage and for HavingPrescription-Drug Coverage With Private Medical Insurance, Adjusted for Age, Gender, Health Status, and Mutually Adjusted for Race,Family Income, and Maternal Education*

Variable

Having Dental Coverage

OR P 95% CI

Having Prescription-Drug Coverage

OR P 95% CI

Race

WhiteBlackAsianHispanicOther

1.001.921.141.021.64

Ref. group,.001

.65

.82

.54

Ref. group(1.41, 2.62)(0.64, 2.02)(0.78, 1.38)(0.34, 7.89)

1.001.020.780.951.90

Ref. group.92.49.77.57

Ref. group(0.71, 1.47)(0.39, 1.57)(0.66, 1.35)(0.21, 17.0)

Family income

PoorNear poorLow incomeMiddle incomeHigh income

0.460.260.570.811.00

.002,.001

.003

.09Ref. group

(0.28, 0.75)(0.12, 0.55)(0.40, 0.82)(0.63, 1.04)Ref. group

0.260.150.370.551.00

,.001,.001,.001,.001

Ref. group

(0.15, 0.45)(0.06, 0.37)(0.24, 0.57)(0.40, 0.77)Ref. group

Maternal education

Less than high schoolHigh schoolBachelor’s degreeMaster’s degree and above

0.470.580.551.00

.009

.024

.012Ref. group

(0.27, 0.83)(0.36, 0.93)(0.35, 0.88)Ref. group

0.590.850.931.00

.12

.59

.81Ref. group

(0.30, 1.14)(0.47, 1.53)(0.52, 1.67)Ref. group

*Variables significant at P # .05 level are highlighted in bold.

coverage. Low maternal education level also had a sig-nificant negative effect on dental-insurance coverage, evenafter adjusting for family income level and racial vari-ables. After controlling for other variables (ie, income,maternal education, health status, etc), among childrenwith private insurance, black children were more likely tohave dental insurance than white children (odds ratio 1.92,P , .001).

DISCUSSION

This study revealed that many children with privatemedical insurance did not have prescription-drug and/ordental coverage. Among children with private insurance,low family income level was an important risk factor fornot having dental insurance or prescription-drug coverage.Maternal education level also played a role in this groupfor both dental and prescription-drug coverage.

Programs such as Medicaid and SCHIP play a criticalrole in insuring children.1,6,7,26 However, despite these ef-forts, approximately 9% of all US children remained un-insured in 2000. In addition to those uninsured for med-ical coverage, this study identified even a greater per-

centage of children uninsured for prescription-drug and/or dental services.

A study published by Elixhauser et al19 using the firsthalf of the 2000 MEPS data showed similar coveragerates. Their study also found that poor children and mi-nority children were less likely to have medical-insurancecoverage, and thus less utilization and expenditures. How-ever, their study focused primarily on medical insuranceand did not examine dental or prescription-drug coveragein children.

Because of the continual rise in health care costs andthe emerging role of oral health in children, it’s importantto consider and examine supplemental insurance and den-tal coverage beyond basic medical insurance in order todepict accurately children’s ability to access care. Dra-matic increases in prescription-drug costs in recent yearscan lead to differential utilization of medications due todifferences in prescription-drug coverage. In seniors, sup-plemental insurance leads to higher utilization,12,28 and thedifference in prescription-drug coverage is an especiallyimportant driver of utilization differences.12

Children without dental coverage are significantly lesslikely than those with dental coverage to utilize dentalservices.15,17 This disparity in utilization among those withdental coverage and those without persists across all in-come groups.15

This study highlighted the vulnerability of children withlower socioeconomic status. Not only were they under-insured with respect to medical coverage, they were alsoless likely to have prescription-drug and/or dental cover-age. The differences in prescription-drug and dental cov-erage will likely widen the gap of service use and healthoutcome in children.

Two additional findings from this study were notewor-thy. First, among children with private insurance, black

AMBULATORY PEDIATRICS446 Chen

children were more likely than white children to have den-tal-insurance coverage, after adjusting for age, gender, andsocioeconomic confounders. This was an unexpected find-ing; it might be a culturally determined phenomenon.Black families may view having dental insurance as ahigher priority than their financially equal white counter-parts. Very few publications commented on this particularphenomenon, but a recent article by Edelstein29 notedblack children have the highest rate of dental coverage at72%. However, he attributed the high dental-coveragerates to Medicaid. The current study also revealed thatprivately insured black children have higher rates of den-tal coverage than white children. Second, near-poor fam-ilies (100%–124% PL) may be at greater risk of beinguninsured than poor families (,100% PL). It is believedthat near-poor families are often financially unable to ob-tain private insurance but are also not poor enough toqualify for public insurance programs. This is not a newfinding; however, this study demonstrated that the vulner-ability of near-poor families extended beyond basic med-ical insurance into dental and prescription-drug cover-age—perhaps even to a greater degree.

This study has several limitations. First, MEPS con-tained only dental-insurance and prescription-drug cov-erage information for children who had private insurance.MEPS documentation does not specify the reasons for ex-cluding publicly insured children from the dental and pre-scription-drug coverage information. One would speculatethat the wide variability of SCHIP dental and prescription-drug benefits and Medicaid’s state-specific pharmacy for-mulary restrictions make it difficult to standardize thesepublicly funded benefits and compare them across differ-ent states. Even though a majority of US children wereprivately insured, one cannot extrapolate the study find-ings to all US children. That being said, there is no reasonto believe publicly insured children would be more likelythan privately insured children to have dental or prescrip-tion-drug coverage unless such benefits are programmat-ically attached to their medical coverage.30

Classifying ‘‘having insurance coverage at any point intime during the year’’ as insured likely overestimates theextent of coverage. Children who have interrupted cov-erage during the year may have similar problems as thoseuninsured for the entire year. However, classifying onlythose children with continuous insurance for the entireyear as insured may also result in underestimation of cov-erage. Another limitation of the study is that insurancestatus reflects only potential access and not realized ac-cess. This study likely underestimates the disparity amongchildren’s access to care by looking at insurance statusalone. For example, poor children and their parents mayfind cost-sharing (such as copayments for prescriptionmedicine) more burdensome than children from high in-come families and thus are less likely to utilize servicesdespite having prescription-drug benefits. In addition, thisstudy did not account for the variation and scope of var-ious prescription-drug and dental plans. A poor child mayhave dental-insurance coverage through the parent’s em-

ployer, but the benefits may be more restrictive and lesscomprehensive than those of his/her wealthier counterpart.

Although many more children are insured today as aresult of programs such as SCHIP, extension of medicalcoverage alone may not be sufficient to allow children toaccess a full range of services. Many children do not havedental or prescription-drug coverage, even privately in-sured children. Among privately insured children, thosewho were poor, minority, and with low maternal educationhad lower likelihood of dental and prescription-drug cov-erage.

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