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ObjectiveHigh out-of-pocket (OOP) costs can be an obstacle to health care access and treatment compliance. This study investigated trends in high OOP health care burden in people with diabetes.Research design and methodsUsing Medical Expenditure Panel Survey 2001-2011 data, we examined trends in the proportion of people aged 18-64 years with diabetes facing a high OOP burden. We also examined whether the trend differed by insurance status (private insurance, public insurance, or no insurance) or by income level (poor and near poor, low income, middle income, or high income).ResultsIn 2011, 23% of people with diabetes faced high OOP burden. Between 2001-2002 and 2011, the proportion of people facing high OOP burden fell by 5 percentage points (P < 0.01). The proportion of those who were publicly insured decreased by 22 percentage points (P < 0.001) and of those who were uninsured by 12 percentage points (P = 0.01). Among people with diabetes who were poor and near poor and those with low income, the proportion facing high OOP burden decreased by 21 (P < 0.001) and 13 (P = 0.01) percentage points, respectively; no significant change occurred in the proportion with private insurance or middle and high incomes between 2001-2002 and 2011.ConclusionsThe past decade has seen a narrowing of insurance coverage and income-related disparities in high OOP burden in people with diabetes; yet, almost one-fourth of all people with diabetes still face a high OOP burden.

Estimates of county-level disease prevalence have a variety of applications. Such estimation is often done via model-based small-area estimation using survey data. However, for conditions with low prevalence (i.e., rare diseases or newly diagnosed diseases), counties with a high fraction of zero counts in surveys are common. They are often more common than the model used would lead one to expect; such zeros are called 'excess zeros'. The excess zeros can be structural (there are no cases to find) or sampling (there are cases, but none were selected for sampling). These issues are often addressed by combining multiple years of data. However, this approach can obscure trends in annual estimates and prevent estimates from being timely. Using single-year survey data, we proposed a Bayesian weighted Binomial Zero-inflated (BBZ) model to estimate county-level rare diseases prevalence. The BBZ model accounts for excess zero counts, the sampling weights and uses a power prior. We evaluated BBZ with American Community Survey results and simulated data. We showed that BBZ yielded less bias and smaller variance than estimates based on the binomial distribution, a common approach to this problem. Since BBZ uses only a single year of survey data, BBZ produces more timely county-level incidence estimates. These timely estimates help pinpoint the special areas of county-level needs and help medical researchers and public health practitioners promptly evaluate rare diseases trends and associations with other health conditions. [ABSTRACT FROM AUTHOR]

Objectives. We determined the effect of diphtheria and tetanus toxoids and acellular pertussis vaccine (DTaP) and measles, mumps, rubella (MMR) vaccine shortageson timeliness of the third dose of DTaP (DTaP3), the fourth dose of DTaP (DTaP4), and the first dose of MMR (MMR1) among subgroups of preschool children. Methods. Data from the 2001 and 2002 National Immunization Surveys were analyzed. Children age-eligible to receive DTaP3, DTaP4, or MMR1 during the shortages were considered subject to the shortage, and those not age-eligible were not subject to the shortage; timeliness of vaccinations was compared. Results. Among children vaccinated only at public clinics, children residing outside metropolitan Statistical areas, and children in the Southern Census Region, those age-eligible to receive DTaP4 during the shortage were less likely to be vaccinated by 19 months of age than children not subject to the shortage. Conclusions. There was notable disparity in the effects of the recent vaccine shortages; children vaccinated only in public clinics, in rural areas, or in the Southern United States were differentially affected by the shortages. doi: 10.2105/AJPH.2004.053306)

OBJECTIVES. In 1999, the Advisory Committee on Immunization Practices made recommendations for hepatitis A vaccination of children according to historic rates of hepatitis A incidence in different regions of the country. The objective of this study was to examine hepatitis A vaccination coverage rates among children living in states with different vaccination recommendations and to examine individual characteristics associated with vaccination. METHODS. Hepatitis A vaccination status data were collected for children 24 to 35 months of age through the National Immunization Survey, a telephone survey with health care provider-verified vaccination results. Vaccination status data were collected from children in each of the 50 states and 28 selected urban areas. RESULTS. In 2003, 50.9% (95% confidence interval [CI]: 47.6-54.2%) of children living in 11 states where routine hepatitis A vaccination is recommended had received ->1 dose, compared with 25.0% (95% CI: 21.8-28.2%) of children in 6 states where vaccination is suggested and 1.4% (95% CI: 1.0-1.8%) of children in 33 states without a recommendation. Coverage was higher among children who lived in urban areas, were Hispanic or American Indian/Alaska Native, or were born to women with less education. CONCLUSIONS. Hepatitis A vaccination is being targeted successfully to children at higher risk of infection; however, overall vaccination coverage remains lower for hepatitis A vaccination, compared with other routine childhood vaccinations. www.pediatrics.org/cgi/doi/10.1542/ peds.2005-0286 doi:10.1542/peds.2005-0286 Key Words hepatitis A, vaccination coverage, children, race/ethnicity, immunization policy Abbreviations ACIP--Advisory Committee on Immunization Practices AIAN--American Indian/Alaska Native CI--confidence interval NIS--National Immunization Survey OR--odds ratio, HEPATITIS A INCIDENCE rates in the United States have historically differed according to race and ethnicity, socioeconomic status, and region of the country, with rates being highest among American Indian/Alaska [...]

Objective. We examined the timeliness of vaccine administration among children aged 24 to 35 months for each state of the United States and the District of Columbia. Methods. We analyzed the timeliness of vaccinations in the 2000-2002 National Immunization Survey. We used a modified Bonferroni adjustment to compare a reference state with all other states. Results. Receipt of all vaccinations as recommended ranged from 2% (Mississippi) to 26% (Massachusetts), with western states having less timeliness than eastern states. Conclusions. Vaccination coverage measures usually focus on the number of vaccinations accumulated by specified ages. Our analysis of timeliness of administration shows that children rarely receive all vaccinations as recommended. State health departments can use timeliness of vaccinations along with other measures to determine children's susceptibility to vaccine-preventable diseases and to evaluate the quality of vaccination programs. States can use the modified Bonferroni comparison to appropriately compare their results with other states. (doi:10.2105/AJPH.2004.046284)

A study is conducted to determine the extent of delay of vaccination during the first 24 months of life of children in the United States. The study concluded that more than 1 in 3 children were undervaccinated for more than 6 months during their first 24 months of life and 1 in 4 children were delayed for at least 4 vaccines.

Context. Each year 2.1 million children 19 to 35 months of age are undervaccinated. Among these are children who have received no vaccinations. Unvaccinated children are at increased risk of acquiring and transmitting vaccine-preventable diseases. Objectives. To assess whether the characteristics of children with no vaccinations differ from those of undervaccinated children, to monitor trends in the numbers of unvaccinated children, and to identify states with high rates and counties with large numbers of unvaccinated children. Design. A nationally representative probability sample of children 19 to 35 months of age was collected annually between 1995 and 2001. Vaccination histories were ascertained from children&apos;s medical providers. Undervaccinated children had received [greater than or equal to] 1 dose of diphtheria-tetanus-pertussis, polio, measles, Haemophilus influenzae type b, hepatitis B, or varicella vaccine but were not fully vaccinated. Unvaccinated children were children who were reported as having no medical providers and having received no vaccinations or children whose medical providers reported administering no vaccinations. Participants. A total of 151 720 children sampled between 1995 and 2001, 795 of whom were unvaccinated. Results. Undervaccinated children tended to be black, to have a younger mother who was not married and did not have a college degree, to live in a household near the poverty level, and to live in a central city. Unvaccinated children tended to be white, to have a mother who was married and had a college degree, to live in a household with an annual income exceeding $75 000, and to have parents who expressed concerns regarding the safety of vaccines and indicated that medical doctors have little influence over vaccination decisions for their children. Unvaccinated children were more likely to be male than female. Annually, ~17 000 children were unvaccinated. The largest numbers of unvaccinated children lived in counties in California, Illinois, New York, Washington, Pennsylvania, Texas, Oklahoma, Colorado, Utah, and Michigan. States that allowed philosophical exemptions to laws mandating vaccinations for children as they entered school had significantly higher estimated rates of unvaccinated children. Conclusions. Unvaccinated children have characteristics that are distinctly different from those of undervaccinated children. Unvaccinated children are clustered geographically, increasing the risk of transmitting vaccine-preventable diseases to both unvaccinated and undervaccinated children. Pediatrics 2004;114:187-195; exemptor, undervaccinated, unvaccinated. ABBREVIATIONS. CI, confidence interval; NIS, National Immunization Survey; PKAM, Parental Knowledge and Attitudes topical module; RDD, random-digit dialing; UTD, up-to-date; NUTD, not up-to-date; VPD, vaccine-preventable disease; MSA, metropolitan statistical area., Children who have received no vaccinations have not been well studied in the United States. Many studies have assumed that children with no vaccinations are similar to undervaccinated children and [...]

Objectives. We examined current racial/ethnic differences in immunization coverage rates among US preschool children. Methods. Using National Immunization Survey data from 1996 through 2001, we compared vaccination coverage rates between non-Hispanic White, non-Hispanic Black, Hispanic, and Asian preschool children. Results. During the 6-year study period, the immunization coverage gap between White and Black children widened by an average of 1.1% each year, and the gap between White and Hispanic children widened by an average of 0.5% each year. The gap between White and Asian children narrowed by an average of 0.8% each year. Conclusions. Racial/ethnic disparities in preschool immunization coverage rates have increased significantly among some groups; critical improvements in identifying, understanding, and addressing race/ethnicity-specific health care differences are needed to achieve the Healthy People 2010 goal of eliminating disparities.

Background. Insurance status has been shown to have an impact on children&apos;s use of preventive and acute health services. The objective of this study was to determine the relationship between insurance status and vaccination coverage among US preschool children aged 19 to 35 months. Methods. We linked data from 2 national telephone surveys, the National Immunization Survey and the National Survey of Early Childhood Health, conducted during the first half of 2000. Children were considered up to date (UTD) when they had received at least 4 diphtheria-tetanus-acellular pertussis/diphtheria-tetanus-pertussis vaccines, 3 poliovirus vaccines, 1 MMR vaccine, 3 Haemophilus influenza vaccines, and 3 hepatitis B vaccines at the time the interview was conducted. Results. Among the 735 children in our study sample, 72% were UTD. The vast majority (94%) reported some type of health insurance at the time of the survey. Children with private insurance were more likely to be UTD (80%) than those with public insurance (56%) or no insurance (64%). In a multivariate analysis that controlled for child&apos;s race/ethnicity; household income; maternal age/marital status/educational level; location of usual care; and Special Supplemental Nutrition Program for Women, Infants, and Children participation, insurance was no longer an independent predictor of vaccination. Conclusions. The disparity in vaccination coverage among publicly, privately, and uninsured children is dramatic, underscoring its importance as a marker for underimmunization, despite the multivariate findings. The Vaccines for Children Program, a partnership between public health and vaccination providers who serve uninsured children and those enrolled in Medicaid, is well suited to target and improve vaccination coverage among these vulnerable children. Pediatrics 2004;113:1959-1964; children, insurance status, vaccination, vaccination coverage., ABBREVIATIONS. SCHIP, State Children's Health Insurance Program; NIS, National Immunization Survey; NSECH, National Survey of Early Childhood Health; CDC, Centers for Disease Control and Prevention; UTD, up to date; WIC, [...]

The effects of changes in recommendations regarding administration of a hepatitis B birth dose on vaccination coverage is determined. Reductions in hepatitis B vaccine birth-dose coverage persisted after recommendations were made to resume previous newborn vaccination practices.

Abstract Background People with diabetes can suffer from diverse complications that seriously erode quality of life. Diabetes, costing the United States more than $174 billion per year in 2007, is expected to take an increasingly large financial toll in subsequent years. Accurate projections of diabetes burden are essential to policymakers planning for future health care needs and costs. Methods Using data on prediabetes and diabetes prevalence in the United States, forecasted incidence, and current US Census projections of mortality and migration, the authors constructed a series of dynamic models employing systems of difference equations to project the future burden of diabetes among US adults. A three-state model partitions the US population into no diabetes, undiagnosed diabetes, and diagnosed diabetes. A four-state model divides the state of "no diabetes" into high-risk (prediabetes) and low-risk (normal glucose) states. A five-state model incorporates an intervention designed to prevent or delay diabetes in adults at high risk. Results The authors project that annual diagnosed diabetes incidence (new cases) will increase from about 8 cases per 1,000 in 2008 to about 15 in 2050. Assuming low incidence and relatively high diabetes mortality, total diabetes prevalence (diagnosed and undiagnosed cases) is projected to increase from 14% in 2010 to 21% of the US adult population by 2050. However, if recent increases in diabetes incidence continue and diabetes mortality is relatively low, prevalence will increase to 33% by 2050. A middle-ground scenario projects a prevalence of 25% to 28% by 2050. Intervention can reduce, but not eliminate, increases in diabetes prevalence. Conclusions These projected increases are largely attributable to the aging of the US population, increasing numbers of members of higher-risk minority groups in the population, and people with diabetes living longer. Effective strategies will need to be undertaken to moderate the impact of these factors on national diabetes burden. Our analysis suggests that widespread implementation of reasonably effective preventive interventions focused on high-risk subgroups of the population can considerably reduce, but not eliminate, future increases in diabetes prevalence.

Abstract Background Childhood vaccinations help reduce and eliminate many causes of morbidity and mortality among children. The objective of this study was to compare 4:3:1:3:3 (4+ doses of diphtheria and tetanus toxoids and pertussis vaccine, 3+ doses of poliovirus vaccine, 1+ doses of measles-containing vaccine, 3+ doses of Haemophilus influenzae type b vaccine, and 3+ doses of hepatitis B vaccine) coverage among children whose caregivers learned by different methods when their child's most recent immunization was needed. Methods Between July 2001 and December 2002, a portion of households receiving the National Immunization Survey were asked how they knew when to take the child in for his/her most recent immunization. Responses were post-coded into several categories: 'Doctor/nurse reminder at previous immunization visit', 'Shot card/record', 'Reminder/recall', and 'Other'. Respondents could give more than one answer. Children who did not receive any vaccines, had ≤ 1 visits for vaccinations, or whose caregiver did not provide an answer to the question were excluded from analyses. Chi-square analyses were used to compare 4:3:1:3:3 coverage among 19–35 month old children. Results Children whose caregivers indicated that a doctor/nurse told them at a previous immunization visit when to return for the next immunization had significantly greater 4:3:1:3:3 coverage than those who did not choose the response (77.2% vs. 70.1%, p < 0.01). However, no significant difference in coverage was found between households that did/did not indicate that reminder/recalls (71.0% vs. 75.5%, p = 0.24) helped them remember when to take their child for their most recent immunization visit; only borderline significance was found between those that did/did not choose shot cards (70.6% vs. 76.2%, p = 0.07). Conclusion A doctor or nurse's reminder during an immunization visit of the next scheduled immunization visit effectively encourages caregivers to bring children in for immunizations, providing an inexpensive and easy way to effectively increase immunization coverage.

Abstract Aim Childhood immunization coverage in the United States (U.S.) is often measured at age 24 months or, in the National Immunization Survey (NIS) at age of interview, which is between 19 and 35 months. This paper compares these standards. Methods Data from the NIS is used to compare immunization coverage at time of interview, retrospectively among all children aged 24 or more months at time of interview, and obtained via multiple imputation (with 10 imputations) for all children, both nationally, by state, and by demographic groups. Results At the national level, the difference between the 19–35 month estimate and the 24 month complete-case estimate was 1.9 percentage points. For most but not all states and subgroups, the 19–35 month estimate was higher than the 24 month complete-case estimate. The difference between vaccination coverage measured at 19–35 months and 24 months ranged from -2.3 to 7.5 percentage points among states. For three states, the difference between the 19–35 month and 24 month complete-case estimate was more than 6 percentage points, in twelve states there was a 4–6 percentage point difference, and in sixteen states a 2–4 percentage point difference. Conversely, five states had higher 24 month complete-case estimates than 19–35 month estimates. Conclusion We found that the coverages at 19–35 and 24 months differ such that they would rarely be adequate surrogates for one another, particularly at a state level. Multiple imputation, which is easily implemented, increases precision of estimates of coverage at age 24 months.

Bayesian hierarchical regression (BHR) is often used in small area estimation (SAE). BHR conditions on the samples. Therefore, when data are from a complex sample survey, neither survey sampling design nor survey weights are used. This can introduce bias and/or cause large variance. Further, if non-informative priors are used, BHR often requires the combination of multiple years of data to produce sample sizes that yield adequate precision; this can result in poor timeliness and can obscure trends. To address bias and variance, we propose a design assisted model-based approach for SAE by integrating adjusted sample weights. To address timeliness, we use historical data to define informative priors (power prior); this allows estimates to be derived from a single year of data. Using American Community Survey data for validation, we applied the proposed method to Behavioral Risk Factor Surveillance System data. We estimated the prevalence of disability for all U.S. counties. We show that our method can produce estimates that are both more timely than those arising from widely-used alternatives and are closer to ACS' direct estimates, particularly for low-data counties. Our method can be generalized to estimate the county-level prevalence of other health related measurements. [ABSTRACT FROM AUTHOR]