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Measuring Efficiency in Health Care Analytic Techniques and Health Policy

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ISBN-10: 0521851440

ISBN-13: 9780521851442

Edition: 2006

Authors: Rowena Jacobs, Peter C. Smith, Andrew Street

List price: $75.99
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Description:

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 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 a timely critical assessment of the strengths and limitations of efficiency analysis applied to health and health care.
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Book details

List price: $75.99
Copyright year: 2006
Publisher: Cambridge University Press
Publication date: 6/1/2006
Binding: Hardcover
Pages: 262
Size: 6.00" wide x 9.00" long x 0.75" tall
Weight: 1.188
Language: English

Rowena Jacobs is a Research Fellow at the Centre for Health Economics, University of York.

Andrew Street is Senior Research Fellow at the Centre for Health Economics, University of York.

List of figures
List of tables
Preface
Acknowledgements
List of abbreviations
Efficiency in health care
Introduction
The demand for efficiency analysis in health care
Organisational efficiency
Analytic efficiency measurement techniques
Experience with efficiency analysis in health care
This book
The components of an efficiency model
Introduction
Unit of analysis
What are outputs in health care?
Health outcomes
Health care activities
Valuing health care outputs
Specifying inputs
Labour inputs
Capital inputs
Summary
Environmental constraints
Practical challenges
Conclusions
Stochastic frontier analysis of cross-sectional data
Introduction
Considerations in stochastic frontier analysis
Whether to estimate a production or a cost function
Whether to transform variables
Whether to estimate a total or an average function
Which explanatory variables to include
How to model the residual
How to extract the efficiency estimates
Application to acute hospitals in England
Conclusions
Stochastic frontier analysis of panel data
Introduction
Time-invariant efficiency
Empirical application
Time-varying efficiency
Empirical application
Unobserved heterogeneity
Empirical application
Summary and sensitivity analysis
Conclusions
Data envelopment analysis
Introduction
The DEA methodology
Input-oriented efficiency
Output-oriented efficiency
DEA formulation
Considerations in data envelopment analysis
Whether to assume constant or variable returns to scale
Whether to assume an input or an output orientation
Whether to apply weight restrictions
Dealing with 'slacks'
Model specification and judging the quality of a DEA model
How to adjust for environmental factors
Application to acute hospitals in England
The methods and data
Model specifications
Results
Conclusions
The Malmquist index
Introduction
The Malmquist methodology
A graphical illustration
The general form of the Malmquist index
Considerations in using the Malmquist index
Previous literature on the Malmquist index in health care
Application to acute hospitals in England
The methods and data
Model specifications
Results
Conclusions
A comparison of SFA and DEA
Introduction
Why SFA and DEA produce different efficiency estimates
Other differences between SFA and DEA
Comparison of different methodologies
The methods and data
Model specifications
Results
Conclusions
Unresolved issues and challenges in efficiency measurement
Introduction
Output weights
Modelling the production process
Environmental constraints
Dynamic effects
Conclusions
Some alternative approaches to measuring performance
Introduction
Multilevel modelling
Generalised statistical modelling
Illustrative example
Seemingly unrelated regression (SUR) in a multilevel context
Illustrative example
Conclusions
Conclusions
Introduction
Output weights
Partitioning unexplained variation
Unresolved technical issues
For policy makers and regulators
Data description
References
Author index
Subject index