Journal of Economic and Social Measurement - Volume 26, issue 2

Authors: Cohen, Steven B.

Article Type: Other

Abstract: Guest editor's preface

DOI: 10.3233/JEM-2000-0178

Citation: Journal of Economic and Social Measurement, vol. 26, no. 2, pp. 79-81, 2000

Authors: Cohen, Steven B. | Machlin, Steven R.

Article Type: Research Article

Abstract: In panel designs with multiple waves of data collection, the overall survey response rate is a multiplicative function of the wave specific response rates. The 1996 Medical Expenditure Panel Survey (MEPS) Household Component follows this model to acquire data on …health care use, expenditures, insurance coverage and sources of payment that cover two consecutive calendar years. An overlapping panel design was implemented, where data covering the second year of a panel are combined with data from the first year of a new panel. This study identifies the characteristics that distinguish survey participants across waves of the survey from those that only participate in initial rounds and then discontinue their survey participation. The results provide insights regarding the efficacy of the MEPS nonresponse adjustment strategies by comparing the survey estimates from the second year of the longitudinal panel with those from a new panel for the same time period. Show more

DOI: 10.3233/JEM-2000-0173

Citation: Journal of Economic and Social Measurement, vol. 26, no. 2, pp. 83-98, 2000

Authors: Ezzati-Rice, Trena M. | Frankel, Martin R. | Hoaglin, David C. | Loft, John D. | Coronado, Victor G. | Wright, Robert A.

Article Type: Research Article

Abstract: The evaluation of the level of nonresponse in a survey and the impact of that nonresponse on the survey estimates is an important issue in survey research. It is important to apply the most accurate method of calculating response rates in …order to understand the components of nonresponse and to be in a better position to incorporate modifications in the survey procedures as necessary and feasible. Response rates have been defined in a number of ways for RDD surveys. The standard/traditional method of calculating response rates involves the product of three rates -- the resolution rate, the screening completion rate, and the interview completion rate. The coverage rate (population coverage) has often been reported separately from the response rate. The method presented in this paper has the advantage of combining the coverage rate and the response rate in the calculation of the overall response rate. Show more

DOI: 10.3233/JEM-2000-0174

Citation: Journal of Economic and Social Measurement, vol. 26, no. 2, pp. 99-109, 2000

Authors: Cohen, Steven B. | Yu, William W.

Article Type: Research Article

Abstract: The 1996 Medical Expenditure Panel Survey - Household Component (MEPS-HC) was designed as a continuous on-going survey to permit annual estimates of health care utilization, expenditures, insurance coverage and sources of payment for the U.S. civilian noninstitutionalized population. Selected as …a nationally representative subsample from the National Health Interview Survey, it is characterized by a multi-stage area probability design with an oversample of households with Hispanics and blacks. The 1996 MEPS sample consists of 195 primary sampling units (PSUs) which contained 10,597 responding NHIS households. In this paper, the precision of survey estimates derived from a 195 PSU design is compared with precision results for alternative sample allocation schemes that preserve the number of sample respondents and the over-sampling of minorities, while varying the number of PSUs and segments. The results provide insights on the impact of alternative sample allocation schemes on the precision of national health care estimates. Show more

DOI: 10.3233/JEM-2000-0175

Citation: Journal of Economic and Social Measurement, vol. 26, no. 2, pp. 111-128, 2000

Authors: Winglee, Marianne | Valliant, Richard | Brick, J. Michael | Machlin, Steven

Article Type: Research Article

Abstract: This paper discusses the methods of probability record linkage and error estimation for the Medical Expenditure Panel Survey (MEPS). MEPS collects medical expenditure data from both household respondents and their medical providers. The medical events reported by the two sources …are subject to reporting differences and probability linkage methods are used to determine if pairs of medical events belong to the same entities. Match weights are assigned to pairs of events based on the likelihood of being a match, and a decision made to declare pairs as matches or nonmatches. The linkage errors include false matches (false positive) when pairs selected are not true matches, and false nonmatches (false negative) when true pairs are omitted. This study used three approaches: manual reviews, cumulative weight curves, and simulation approaches to provide estimates of linkage errors. Show more

DOI: 10.3233/JEM-2000-0176

Citation: Journal of Economic and Social Measurement, vol. 26, no. 2, pp. 129-140, 2000

Authors: Machlin, Steven R. | Cohen, Joel W. | Thorpe, Joshua M.

Article Type: Research Article

Abstract: Despite declines in recent years, inpatient care remains the largest component of national medical expenditures. The U.S. Department of Health and Human Services currently sponsors five data collection efforts that can be used to estimate the utilization of inpatient hospital …care in the United States. Through a comparison of 1996 inpatient utilization estimates, this paper describes important methodological considerations when using the different data sources for measuring inpatient use. Our results show that surveys with similar target populations and methodologies produced similar estimates. In particular, estimates for the household based surveys (NHIS and MEPS-HC) were comparable while those for the hospital discharge surveys (NHDS and HCUP-NIS) were comparable. Hospital discharge surveys produced substantially higher estimates of total discharges than household surveys, which is partly attributable to differences in target populations. Also, data from the MCBS suggest that underreporting may be another explanation for lower estimates from the household surveys. Show more

Keywords: hospital utilization, benchmarking, healthcare surveys, data collection, NHIS, MEPS, NHDS, HCUP, MCBS

DOI: 10.3233/JEM-2000-0179

Citation: Journal of Economic and Social Measurement, vol. 26, no. 2, pp. 141-151, 2000