Measuring Efficiency in Health Care: Analytic Techniques and Health Policy
Cambridge University Press
Edition: Illustrated, 6/13/2014
EAN 9780521851442, ISBN10: 0521851440
Hardcover, 100 pages, 22.9 x 15.2 x 1.6 cm
Language: English
Originally published in English
With the healthcare sector accounting for a sizeable proportion of national expenditures, the pursuit of efficiency has become a central objective of policymakers within most health systems. However, the analysis and measurement of efficiency is a complex undertaking, not least due to the multiple objectives of health care organizations and the many gaps in information systems. In response to this complexity, research in organizational efficiency analysis has flourished. This 2006 book examines some of the most important techniques currently available to measure the efficiency of systems and organizations, including data envelopment analysis and stochastic frontier analysis, and also presents some promising new methodological approaches. Such techniques offer the prospect of many new and fruitful insights into health care performance. Nevertheless, they also pose many practical and methodological challenges. This is an important critical assessment of the strengths and limitations of efficiency analysis applied to health and health care.
Figures
Tables
Preface
Acknowledgements
1. Efficiency in health care
2. The components of an efficiency model
3. Stochastic frontier analysis of cross-sectional data
4. Stochastic frontier analysis of panel data
5. Data envelopment analysis
6. The Malmquist Index
7. A comparison of SFA and DEA
8. Unresolved issues and challenges in efficiency measurement
9. Some alternative approaches to measuring performance
10. Conclusions
Appendix
References
Author index
Subject index
Acronyms.
'Many health efficiency researchers have locked themselves into becoming experts in a small set of methods, but this excellent book illustrates why everyone's toolkit needs to be more expansive to answer the policy questions at hand. And more importantly, it explains how to choose the right model for the right policy question.' James F. Burgess, Jr, Boston University School of Public Health