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Health Services Research

Alternative OrderingPhone: 1-800-358-9295; Outside of the United States: 703-437-2078; TTY/TDD: 1-888-586-6340
Mail: AHRQ Publications Clearinghouse, P.O. Box 8547, Silver Spring, MD 20907-8547

A Health Services Research Agenda for Cellular, Molecular and Genomic Technologies in Cancer Care AHRQ 09-R071
L. Wideroff, K. Phillips, G. Randhawa, et al., Public Health Genomics, 12(4):April 2009, 233-244. Summarizes the outcomes of a National Cancer Institute workshop that examined the state of health services research on cancer-related technologies and identified priorities for expanding the evidence base on their effectiveness in routine care. (AHRQ 09-R071)

Accuracy of Medicare Expenditures in the Medical Expenditure Panel Survey AHRQ 09-R068
S. Zuvekas, G. Olin, Inquiry, 46(1):Spring 2009, 92-108. Examines underreporting and underrepresentation of high expenditure cases in the Medical Expenditure Panel Survey (MEPS) and their implications for analyses. (AHRQ 09-R068)

Creating and Synthesizing Evidence with Decision Makers in Mind: Integrating Evidence from Clinical Trials and Other Study Designs AHRQ 08-R012
D. Atkins, Medical Care, 45:2007, S16-S22. Examines the limitations of randomized controlled trials (RCTs) in providing the information decisionmakers need to choose the best treatment for individual patients and explains how information from observational studies can supplement evidence from RCTs.

Funding Opportunities in Knowledge Translation: Review of the AHRQ's "Translating Research into Practice" Initiatives, Competing Funding Agencies, and Strategies for Success AHRQ 08-R043
M. Handrigan, J. Slutsky, Academic Emergency Medicine, 14:November 2007, 965-967. Provides a brief overview of AHRQ?s activities in knowledge translation.

Go Out or Stay In? The Effects of Zero Tolerance Laws on Alcohol Use and Drinking and Driving Patterns Among College Students AHRQ 08-R053
L. Liang, J. Huang, Health Economics, January 2008, online. Uses data from the College Alcohol Surveys conducted by the Harvard School of Public Health to examine analyze a number of pathways through which zero tolerance laws reduce drinking and driving among college students.

Health Expenditure Estimation and Functional Form: Applications of the Generalized Gamma and Extended Estimated Equations Models AHRQ 10-R063
S. Hill, G. Miller, Health Economics, May 2010; 19(5):608-627. Uses data from AHRQ's Medical Expenditure Panel Survey to compare the bias, predictive accuracy, and marginal effects of generalized gamma models and extended estimating equations when they are used in health expenditure estimation studies.

Health Expenditure Estimation and Functional Form: Applications of the Generalized Gamma and Extended Estimating Equations Models AHRQ 09-R067
S. Hill, G. Miller, Health Economics, e-pub:May 2009. Uses data from the Medical Expenditure Panel Survey (MEPS) to compare the bias, predictive accuracy, and marginal effects of generalized gamma models and extended estimating equation models with other commonly used regression models. (AHRQ 09-R067)

Identifying, Categorizing, and Evaluating Health Care Efficiency Measures AHRQ 08-0030
Agency for Healthcare Research and Quality, April 2008, 78 pp. Analyzes various measures of health care efficiency, including criteria for evaluating measures, examples of how measures can be applied, and details on the various sources examined for this report.

Improving Depiction of Benefits and Harms: Analyses of Studies of Well-Known Therapeutics and Review of High-Impact Medical Journals AHRQ 08-R013
A. Sedrakyan, C. Shih, Medical Care, 45(10 Suppl 2):October 2007S23-S28. Provides and discusses examples of how researchers present information about benefits and harms for well-known therapeutics when they publish their studies.

National Release of the Nursing Home Quality Report Cards: Implications of Statistical Methodology for Risk Adjustment AHRQ 09-R089
Y. Li, X. Cai, L. Glance, et al., Health Services Research, 44(1):February 2009, 79-102. Examines how alternative statistical risk-adjustment methods may affect the quality measures used in nursing home report cards. (AHRQ 09-R089)

Sensitivity of Household Reported Medical Conditions in the Medical Expenditure Panel Survey AHRQ 09-R073
S. Machlin, J. Cohen, A. Elixhauser, et al., Medical Care, 47(6):June 2009, 618-625. Uses pooled data from 4 years (2002-2005) of the Medical Expenditure Panel Survey to estimate the extent to which household respondents may underreport 23 types of medical conditions. (AHRQ 09-R073)

So What? The Challenge of Doing "Need to Know" Versus "Would Like to Know" Research.AHRQ 08-R024
R. Hughes, C. Clancy, Applied Nursing Research, 20:2007, 210-213. Presents and discusses six considerations for prioritizing health research topics, including intended audience, information gaps, timing, sources of information, determinants of priority, and relevance.

Stochastic Frontier Analysis of Hospital Inefficiency AHRQ 08-R021
M. Rosko, R. Mutter, Medical Care Research and Review, November 28, 2007, e-pub. Presents the results of an analysis of 20 stochastic frontier analysis (SFA) studies of hospital inefficiency in the United States and compares the use of SFA with previously used methods in hospital studies to determine the robustness of SFA in estimating cost inefficiency.

Understanding and Enhancing the Value of Hospital Discharge Data AHRQ 08-R001
J. Schoenman, J. Sutton, A. Elixhauser, D. Love, Medical Care Research and Review, 64(4):August 2007, 449-468. Summarizes how hospital discharge data are used, identifies strengths and shortcomings, and presents suggestions for enhancing the usefulness of the data.

Updated U.S. Population Standard for the Veterans RAND 12-Item Health Survey (VR-12) AHRQ 09-R039
Updated U.S. Population Standard for the Veterans RAND 12-Item Health Survey (VR-12). A. Selim, W. Rogers, J. Fleishman, et al., Quality of Life Research 18(1):February 2009, 43-52. Discusses the development of an updated U.S. population standard for use in quality of life assessments that accounts for the changes in the U.S. population that have taken place in the past 20 years.

Using Proxy Measures and Other Correlates of Survey Outcomes To Adjust for Non-Response: Examples from Multiple Surveys AHRQ 10-R058
F. Kreuter, K. Olson, J. Wagner, et al., Journal of the Royal Statistical Society, April 2010; 173(2):389-407. Examines traditional covariates and new auxiliary variables for use in various surveys, including AHRQ's Medical Expenditure Panel Survey, and provides empirical estimates of the association between proxy measures and response to the survey request.

What Have We Learned from the Application of Stochastic Frontier Analysis to U.S. Hospitals AHRQ 10-R073
M. Rosko, R. Mutter, Medical Care Research and Review, June 2010; e-pub. Discusses the lessons learned from studies of U.S. hospitals that used the statistical technique, stochastic frontier analysis, to examine hospital inefficiency.

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AHRQ - Advancing Excellence in Health Care