Davern, M., L. A. Blewett, B. Bershadsky, K. T. Call, and T. Rockwood. 2003. “State Variation in SCHIP Allocations: How Much Is There, What Are Its Sources, and Can It Be Reduced?” Inquiry 40 (2): 184-187.

Allocations for the State Children's Health Insurance Program (SCHIP) varied 22% per state between 1999 and 2002. The funding fluctuations present significant problems for states as they develop budget priorities under difficult fiscal conditions. We examine sources of the variation in state allocations during the first four years of SCHIP, focusing on the Current Population Survey's "child component" of the allocation formula. We consider the trade-offs in using alternative estimates from the American Community Survey and model-based estimation. Obtaining reliable estimates of need for SCHIP allocations is critical for states dependent on federal support for insurance programs.

Davern, M., L. A. Blewett, B. Bershadsky, and N. Arnold. 2004. “Missing the Mark? Examining Imputation Bias in the Current Population Survey’s State Income and Health Insurance Coverage Estimates.” Journal of Official Statistics 20(3):519-49.

The Demographic Supplement to the U.S. Current Population Survey (CPS) is used to produce state estimates of health insurance coverage and income. These estimates are used in federal allocation formulas that distribute $10-11 billion annually to states for the State Children's Health Insurance Program (SCHIP) and the Elementary and Secondary Education Act. The purpose of this article is to examine the CPS for evidence of bias in state estimates due to missing data imputation and estimate the extent of the bias for each of the fifty-one states and Washington DC. Comparing three years of CPS (1998-2000), to the Census 2000 Supplementary Survey and 1990 Decennial Census data benchmarks, we find evidence of bias in state estimates of earned income. We also extend the technique to the CPS state health insurance coverage estimates and find even more evidence of bias. In general, the "better off" states (those with higher insurance coverage rates or more income) tend to be even "better off" (have higher estimates of average income and coverage rates) after correcting for bias (and vice versa). We conclude by considering alternative strategies for the U.S. Census Bureau to alter its current imputation procedures.

Davern, M., J. Lepkowski, K. T. Call, N. Arnold, T. L. Johnson, K. Goldsteen, A. T. Malmlov and L. A. Blewett. 2004. “Telephone Service Interruption Weighting for State Health Insurance Surveys.” Inquiry 41(3): 280–290.

Many states rely on telephone surveys to produce estimates of uninsurance. To the extent that people in households without telephones differ from those living in households with telephones, estimates will be biased due to lack of coverage of those in households without telephones. We find the disparity in estimates of uninsurance in the Current Population Survey (all people vs. those living in households without telephones) shows a similar association to the disparity found in the state surveys (all people vs. those living in households with telephone service interruptions). We adjust the state survey weights of those people living in households that experienced telephone interruptions to account for people living in households without telephones and evaluate whether the weighting adjustment for telephone service interruptions is advisable.

Blewett, L. A., S. Parente, M. D. Finch, and E. Peterson. 2005. “National Health Data Warehouse: Issues to Consider." Journal of Healthcare Information Management 18(1): 52-58.

A national data warehouse that links public and private data could be used to monitor trends in healthcare costs, utilization, quality of care, and adherence to quality guidelines and changes in treatment protocols. The development of the data warehouse, however, would require overcoming a number of political and technical challenges to gain access to private insurance data. This article outlines recommendations from a national conference sponsored by the Agency for Healthcare Research and Quality (AHRQ) on the private sector's role in quality monitoring and provides an operational outline for the development of a national private sector health data warehouse.

Blewett, L. A., M. B. Good, K. T. Call, and M. Davern. 2004. “Monitoring the Uninsured: A State Policy Perspective.” Journal of Health Politics, Policy and Law 29(1): 107-145.

Because states have primary responsibility for the implementation of public health insurance programs, states need timely, good quality data to evaluate programs, monitor trends in the number and characteristics of the uninsured, and better understand the dynamics of health insurance coverage. This article provides a synthesis of the data sources available to states for monitoring rates of health insurance coverage. Information was collected through a comprehensive review of state and national health surveys and in-depth interviews with state analysts in all fifty states. Our findings suggest that national surveys do not meet states' needs for data, and in response, states have initiated their own household surveys. We provide information on thirty-six household surveys that are used to estimate state levels of health insurance coverage. We recommend that national and state efforts be better coordinated to facilitate efficient use of resources to achieve good state-level date.