PEDIATRICS Vol. 111 No. 4 April 2003, pp. 735-740
The First 2 Years of a State Child Health Insurance Plan: Whom Are We Reaching?
* Departments of Pediatrics and Preventive Medicine and Biometrics and University of Colorado HSC, Denver, Colorado, and the Children’s Outcomes Research Program, Children’s Hospital, Denver, Colorado
Child Health Advocates, Denver, Colorado
Department of Public Health and the Environment, Denver, Colorado
|| AMC Cancer Research Center, Denver, Colorado
¶ Department of General Internal Medicine and Colorado Health Outcomes Program, University of Colorado HSC, Denver, Colorado
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Objective. The Colorado Child Health Plan Plus is a non-Medicaid state Child Health Insurance Plan. The objective of this study was to compare early enrolling (EE) children with uninsured children in low-income families (ULI) with respect to 1) sociodemographic factors and previous insurance, 2) health status, and 3) previous health care access and utilization.
Methods. Cross-sectional telephone surveys were conducted during 1999 of 1) randomly selected EE children (n = 711) and 2) ULI children identified by random-dial survey (n = 105).
Results. Enrolling children were less likely to be Hispanic (32.7% vs 55.2%); 5.5% of EE versus 27.6% of ULI children had never been insured. Prevalence of chronic conditions was similar (16.2% of EE vs 13.5% of ULI children), but learning/behavioral difficulties (9.7% of EE vs 18.6% of ULI) and fair/poor health (5.4% of EE vs 17.2% of ULI) were higher for uninsured children. In the previous year, 88.2% of EE versus 66.1% of ULI children had a usual source of care. The mean number of preventive visits was similar (1.4 vs 1.2), but the EE group reported a higher mean number of sick visits (2.0 vs 1.1), emergency visits (0.48 vs 0.15), and hospitalizations (0.09 vs 0.02).
Conclusions. In the first 2 years of the program, Child Health Plan Plus is not yet reaching the "hard-to-reach" but, rather, disproportionately high numbers of non-Hispanic children who already have a usual source of care and recent insurance. EE children did not have higher rates of chronic conditions but did demonstrate higher utilization before enrollment, possibly reflecting patterns of enrollment into the program.
Key Words: health insurance • state child health insurance plan • health care access
Abbreviations: CHIP, Children’s Health Insurance Program • CHP+, Child Health Plan Plus • EE, early enrolling • ULI, uninsured low-income • BRFSS, Behavioral Risk Factor Surveillance System
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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The state Children’s Health Insurance Program (CHIP) legislation was enacted in 1997 to assist states in providing insurance coverage for children from low-income families.1 The program provided great flexibility to states in designing and implementing their insurance programs. Eighteen states expanded their coverage exclusively through Medicaid, whereas 33 developed separate state programs as part or all of their State Child Health Insurance Plan expansion.2 The Colorado legislature chose to expand an existing stand-alone children’s health insurance program, the Child Health Plan Plus (CHP+), although a single application process for Medicaid and the state program was instituted.
Enrollment in CHP+ began in April 1998. As in many states, Colorado put substantial effort into outreach strategies to enroll eligible children.3 Despite these efforts, CHIP enrollment in the first year of the program was lower than had been anticipated in Colorado,4 mirroring a trend seen nationally.5,6 This is reflected by the fact that a majority of states had to return significant amounts of unspent CHIP dollars to the federal government in 2000.
Understanding the barriers to enrollment into CHIP and patterns of enrollment for eligible children over time is critical to creating effective outreach, enrollment, and retention strategies. Several recent reports have begun to explore enrollment,2,4,7–10 but there is currently little available information that allows us to assess how families who enroll their children differ from the population of uninsured families as a whole. For example, is there selective enrollment on the basis of sociodemographic factors or health status? Do enrolling children have a higher burden of medical illness before enrollment than those who are eligible but do not enroll? Have enrolling children had poor access or utilization of care before enrollment? Would we expect them to demonstrate pent-up demand for services after enrollment? Probably most crucial from a medical perspective is whether CHIP is reaching those children who are most in need of coverage either because they have unmet medical needs or have not previously been served by the health care system.
The objectives of the present study were to compare characteristics of families who enrolled a child in CHP+ during the first 2 years of the program, "early enrollers," with families with a child who remained uninsured but seemed to be CHP+ eligible with respect to 1) sociodemographic factors and previous insurance, 2) health status at the time of enrollment into CHP+, and 3) access and health care utilization during the year preceding enrollment. We hypothesized that early enrolling (EE) children would be more likely to be non-Hispanic, to have been previously insured, and to have a chronic medical illness than those who remained uninsured. We also hypothesized that EE children would be more likely to have received preventive care in the preceding year than those who remained uninsured.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Similar telephone surveys were conducted in 2 study populations during the period January 1999 to January 2000, corresponding to the first 6 months to 1.5 years of the CHP+ program. The survey was conducted in English and Spanish, depending on the preference of the families contacted. The study protocol was approved by the Colorado Multiple Institutional Review Board.
Study Populations
The EE population consisted of randomly selected families who had enrolled children in CHP+ 2 months previously. We attempted to contact 1048 families who were randomly selected from computerized databases for the whole state during a 3-month period. Of the sample, 128 (12.2%) were determined to be ineligible because they were actually not enrolled or were not new enrollees. Of the eligible sample, 711 families were surveyed, yielding a 77.3% response rate. Of the 209 families who were not surveyed, 9 (1.0% of total eligible sample) refused interview, 149 (16.2%) had incorrect or nonworking telephone numbers, 43 (4.7%) could not be reached, 6 (0.7%) had language barriers, and 2 (0.2%) had incomplete data.
The uninsured low-income (ULI) population consisted of families with uninsured children identified by 2 random-digit-dial surveys conducted throughout the state during 1999. The Behavioral Risk Factor Surveillance System (BRFSS) was used to identify families from April to December 1999, and the Disability Behavioral Risk Factor Surveillance System was used to identify families from March 1999 through January 2000. After completing the main survey, the adult respondent provided the age, gender, race, ethnicity, and health insurance status of each child in the household. For families with uninsured children, 1 uninsured child was randomly selected and the adult respondent answered appended survey questions about the health status and health care utilization of that child.
The ideal comparison group for our study would have been families with uninsured children who were eligible for CHP+ but were not enrolled. However, because eligibility for Medicaid in Colorado requires asset testing, it was not possible for us to differentiate clearly the proportion that would be eligible for Medicaid versus CHP+. If reported income and family size are used for this estimation, without asset testing, then the results greatly overestimate Medicaid eligibility. In view of these limitations in our ability to determine Medicaid versus CHP+ eligibility, we stratified our samples of uninsured families. We first performed comparative analyses using the entire low-income group, defined as families with incomes 
185% of federal poverty level. We then repeated our analyses excluding any uninsured families with incomes that might have made them Medicaid eligible if they had no other financial assets. Of 179 families with uninsured children, 169 (94.4%) agreed to be interviewed. After interview, 105 (62.1%) were determined to be CHP+ or Medicaid eligible and were retained in the ULI sample.
Telephone Survey
The survey tool incorporated standardized questions with minor modifications from the National Health Interview Survey Household survey, the Prototype Children’s Health Insurance and Health Care Questionnaire from the State and Local Area Integrated Telephone Surveys of the National Center for Health Statistics, and the Consumer Assessment of Health Plans Child Core as well as some questions developed and piloted previously by our study group.4 Interviews were conducted by the Survey Research Unit at the Colorado Department of Public Health and the Environment. Families were called up to 15 times at different calling periods to optimize response rates. The interview was programmed for the Computer Assisted Telephone Interviewing system, and quality control methods included specific training for the survey used, monitoring of 10% of all interviews using Local Area Network Assist Plus software, and recalling of refusals by supervisors.
Definition of Outcome Measures
The focus of this study was the comparison of children who enrolled early into CHP+ versus those who did not but seemed to be eligible. Therefore, the relevant sociodemographic and health status outcomes were assessed at the time of enrollment for enrollers and at the time of survey for nonenrollers, and access and utilization outcomes were assessed for the year before this time in both groups. Health status measures included a global assessment of health status measured on a 5-point Likert scale from poor to excellent, the percentage with 1 or more chronic conditions, defined as a medical condition that has lasted for >3 months, and the percentage with a learning or behavioral difficulty. Health status questions and questions regarding usual sources of care, providers of care, and utilization of health care services were taken from the State and Local Area Integrated Telephone Surveys and Consumer Assessment of Health Plans Child Core surveys, either verbatim or with minor modifications. Previous insurance questions were based on the BRFSS with minor modifications to reflect local insurance programs.
Analysis
Weighting Procedures
All household data from families of ULI children were weighted to adjust for the unequal probability of selection using methods developed by the Centers for Disease Control and Prevention for geographic oversampling in all states that use the BRFSS.11 Data for the enrolling families were weighted to account for both the probability of selection of the household and probability of selection of the child. All percentages reported for both samples, therefore, are weighted.
Statistical Methods
Because the survey design incorporates strata as well as both household- and person-level weighting, all statistics were calculated using STATA 6.0 (Stata Corp, College Station, TX), which is able to analyze survey data with complex sampling designs. 
2 tests and Student t tests were used to compare dichotomous variables and continuous variables, respectively. P < .05, 2-tailed, was considered significant.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Sociodemographic Factors and Previous Insurance
As shown in Table 1, the EE and ULI populations differed in their race/ethnicity, with Hispanics being significantly less likely to enroll. Differences between black and other races were not statistically significant (P = .28) The 2 groups did not differ with respect to age or gender of the index child, with respect to household income or to urban versus rural residence. As Table 2 demonstrates, EE families were more likely to have been insured for most or all of the year before enrolling than ULI families. Of enrolling families, only 5.5% reported that their child had never been insured, compared with almost one third of ULI families. In addition, 36.6% of EE families reported no gap in insurance coverage immediately before enrolling in CHP+. In fact, for families whose employers pay >50% of the dependent premium, a 90-day uninsured period is required before CHP+ enrollment. However, the percentage of families in which the waiting period is imposed is low. The groups did not differ significantly with respect to the last type of insurance, with 35.9% versus 33.6% of the EE and ULI groups, respectively, reporting private employer-based coverage, 5.2% versus 9.6% reporting private non-employer-based insurance, 40.1% versus 35.9% reporting Medicaid, 2.7% versus 6.4% reporting CHP+, and 16.1% versus 14.6% reporting other insurances (P = .64 overall).
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Health Status
Table 3 compares reported health status measures, demonstrating a higher rate of fair/poor health status and a higher percentage of learning or behavioral difficulties in the ULI population. Chronic medical conditions were reported in equal frequency, but EE children were reported to have missed more days from school in the previous year.
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Health Care Utilization
As shown in Table 4, a substantially higher percentage of EE families reported having a usual source of preventive care than did ULI families. Reasons for not having a usual source of care included seldom or never getting sick (35.3% in EE vs 31.6% in ULI, cost of medical care (27.3% EE vs 13.8% ULI), recently moving into the area (11.3% EE vs 25.1% ULI), having just lost insurance (10.7% EE vs 9.5% ULI), not knowing where to go for care (0% EE vs 6.3% ULI), and other reasons (15.3% EE vs 13.7% ULI). Because comparisons of these reasons involved small numbers of families, excluding all those who reported having a usual source of care, differences between groups did not reach statistical significance.
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As demonstrated in Table 4 and Fig 1, EE and ULI families had similar numbers of preventive care visits in the previous year, except in the school-aged and adolescent groups, in which EE families reported significantly more visits. EE families reported more acute visits for injury or illness and more emergency department visits in the previous year, and a larger percentage of EE families reported at least 1 such visit. Although the number of children who reportedly had at least 1 hospitalization was almost 3 times as high in the EE group, the numbers were small in both groups; therefore, we could not exclude the possibility that these differences occurred by chance. Rates of hospitalization were significantly higher in the EE group, however, overall and in all age groups except 1- to 3.99-year-olds.
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Although reported rates of unmet needs were high in both groups in certain categories, these rates did not differ significantly between the 2 groups. Unmet needs in the preceding year were reported in the areas of prescription medications (20.3% EE vs 14.7% ULI; P = .26), mental health care/counseling (7.6% EE vs 4.3% ULI; P = .28), eyeglasses (14.7% EE vs 10.8% ULI; P = .40), and dental care (49.7% EE vs 42.3% ULI; P = .25).
Stratified Analyses Excluding All Potentially Medicaid-Eligible Uninsured Families
After the exclusion of any potentially Medicaid-eligible families, 68 uninsured families remained. The exclusion of these families decreased our statistical power but in most instances did not change the direction of our findings. There was still a trend for Hispanic families to be underrepresented in enrolling (32.7%) versus uninsured (46.0%) families, but these differences no longer reached statistical significance (P = .08). Because of the exclusion of all lower income families, significant differences in income levels were created, with 29.8% of the enrolling versus 7.8% of the uninsured now falling below 100% of the federal poverty level (P < .01). The differences in the percentages of children in fair/poor health were now less notable between enrolling (5.4%) and uninsured children (10.7%), and these differences were no longer significantly different (P = .11), although the findings with regard to learning difficulties in enrolling (16.2%) versus uninsured children (24.0%) were even more marked. Results regarding previous insurance status and health care utilization were unchanged in the stratified analyses.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Understanding how families who choose to enroll their child into a state CHIP differ from those who do not is valuable in guiding efforts to increase enrollment, particularly in identified subpopulations who are preferentially not enrolling or who are in particular medical need. Such data are also important in evaluating the success of the program in increasing access to health care, in resolving unmet needs, and, finally, in planning financially for the program. Our data demonstrate that in the first 2 years of the program, Colorado’s CHIP enrolled disproportionately low numbers of Hispanic children and disproportionately high numbers of children who had been previously and recently insured and who already had a usual source of care. Although there was no evidence that children with chronic illnesses were more likely to enroll, EE families did report more acute office and emergency department visits and a higher rate of hospitalization in the year before enrollment.
Our study is the first of which we are aware that directly compares representative populations who did and did not enroll their children into CHIP during the same time period with respect to a broad array of sociodemographic, insurance, health status, and access and utilization measures. Some descriptive data regarding new enrollees in state CHIPs, however, are available for comparison with our data. Recent studies of New York’s CHIP also suggested underenrollment in minority populations, although in New York the underrepresented minority group was blacks.12 In New York, 4.1% of enrolling children were reported to have fair or poor health,13 and 40% reported no gap in insurance coverage before enrollment, both similar to our data.12 In New York, 45% had experienced a gap of insurance of 12 or more months, compared with 37% in Colorado.14 However, more newly enrolling families in New York reported having a usual source of care in newly enrolling children, with only 5% not having a usual source of care in the year before enrollment.14 Our data for newly enrolling families more closely resemble data from an evaluation of Pennsylvania’s CHIP15 and recent national data from the Medical Expenditure Panel Survey16 showing that, respectively, 88.6% and 91.4% of children had a usual source of care. Comparative data regarding utilization during the year before CHIP enrollment in New York demonstrated higher rates of preventive care in enrollees in Colorado than in New York (4.57 vs 2.14 visits) during the first year but similar rates of acute visits for both the EE and ULI groups.14
In the present study, there were marked differences in health care utilization during the previous year between the newly enrolling and ULI children. Utilization of acute services, both office and emergency department and hospitalization rates, was significantly higher in the enrolling group than in the children who remained uninsured. There are several possible explanations for these differences. The data could suggest more severe chronic illness in the enrolling group; however, this is not supported by the more favorable report of general health status in the enrolling group compared with the uninsured group and the lack of difference in the prevalence of chronic conditions in the 2 groups. Alternatively, they could suggest that families who enrolled early tended to seek care more frequently when ill or perceived a greater need for health care. Finally, they may reflect the way in which children are enrolled into CHP+ in Colorado, as enrollment is frequently initiated at the time of an acute visit, especially a costly emergency department visit, or at the time of a hospital admission if it is determined that the family has low income and no insurance coverage.
Previous studies of patterns of enrollment in adult populations have suggested that those who choose to enroll into voluntary insurance or health intervention programs differ from those who do not enroll. Diehr et al17 compared eligible families who did and did not enroll into the Washington Basic Health Plan, which offered subsidized health insurance to low-income uninsured residents before the State Child Health Insurance Program was established. They found that enrolling individuals were more likely to have been previously insured, to have higher levels of family income and education, to be healthier, and to have less use of medical services than those who did not enroll. In their study, as well as ours, those who enrolled tended to be those who had previously had and presumably valued insurance and those who reported lower levels of chronic illnesses. Similarly, a report of a comprehensive health intervention program implemented by the Indian Health Service in an effort to improve maternal and infant outcomes demonstrated that the populations who enrolled in the program were those who had already sought and received good care before joining.18
There are important limitations to the data reported here. We were limited in our ability to do subgroup comparisons and in our power to assess between-group differences by the relatively small number of ULI patients we could identify using random-dial survey techniques. In addition, our determination of eligibility was based on self-reported income and family size data, and we were unable to differentiate with certainty which families would have been Medicaid eligible versus those that would have been CHP+ eligible. We attempted to control for this by doing stratified analyses, which, in most cases, yielded similar findings. Although the response rate was high for a low-income population, our findings underrepresent those without telephones and populations that are difficult to reach. Finally, our data may not be generalizable to larger, more populous states, particularly those with larger urban populations. In this regard, however, it is surprising how similar our results were to those previously reported for New York State.
Our data support the notion that voluntary health insurance for children first attracts and successfully enrolls families who are more likely to have been previously insured and to be receiving medical care already. These finding have important policy implications. First, early estimates of the effectiveness of CHIP may underestimate the potential impact of the program, because early enrollers may be those who are least in need and the least likely to benefit. Second, because early enrollers seem to differ from the entire potential pool of eligible families, different and more targeted approaches to marketing and enrollment may be needed to enroll subpopulations that are harder to reach. Last and perhaps most important, CHIP may not yet be accomplishing the task of reaching those in most need of a regular source of care. Reaching the "hard to reach" may be the greatest challenge for CHIP. Although not currently mandated, the success of the program should be evaluated not only by measuring outcomes in families who are easily reached but also by assessing the success of the program in enrolling families who have not been receiving health care. Only by aiming for this higher standard and doing the required evaluation to demonstrate it will the program accomplish its aim of reaching the majority of children who remain in the insurance gap between Medicaid and private insurance.
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ACKNOWLEDGMENTS |
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This project was supported by a grant from the Rose Community Foundation.
We acknowledge the critical review of this manuscript by Stephen Berman, MD, and the preparation of the manuscript by Barbara Stucky. We are grateful to the Colorado Department of Health Care Policy and Financing for allowing us access to CHP+ data and for their input into the direction of our research. We also acknowledge Annie Van Deusen of the Rose Community Foundation for help in disseminating our findings locally to those involved in influencing health policy.
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FOOTNOTES |
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Received for publication Apr 17, 2002; Accepted Sep 25, 2002.
Reprint requests to (A.K.) Children’s Hospital, 1056 E 19th Ave, B032, Denver, CO 80218. E-mail: kempe.allison{at}tchden.org
The statements contained in this report are solely those of the authors and do not necessarily reflect the views or policies of the Colorado Department of Health Care Policy and Financing.
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PEDIATRICS (ISSN 1098-4275). ©2003 by the American Academy of Pediatrics
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