Risk Stratification: A Practical Guide for Clinicians

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Format: Paperback
Pub. Date: 2001-04-02
Publisher(s): Cambridge University Press
List Price: $75.99

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Summary

Risk stratification is a statistical process by which quality of care can be assessed independently of patient case mix. The evaluation of risk-adjusted patient outcome has become an important part of managed care contracting in some markets, and risk-adjusted outcome rates for hospitals are being reported more frequently in the popular press and on the Internet. This book, written by a statistician and two surgeons for a clinical audience, is a practical guide to the process of risk stratification and does not require or assume an extensive mathematical background. It describes the rationale and assumptions for risk stratification, and provides information on evaluating the quality of various published risk-stratification studies. Numerous practical examples using real clinical data help to illustrate risk stratification in health care. The volume also serves as a step-by-step guide to the production and dissemination of risk-adjusted outcome results for local programs.

Table of Contents

Preface xi
Introduction
Comparing care across institutions
2(1)
Risk benchmarking for following care over time
3(1)
Predicting risk for individual patients
4(1)
A note on terms
4(2)
References
6(1)
Risk
Populations and samples
7(2)
Probability and risk
9(2)
Risk and odds
11(4)
Risk and a single risk factor
15(2)
Risk and multiple risk factors
17(8)
Selection of variables into logistic models
25(1)
Model error and classification accuracy
26(2)
Generalizing the results
28(1)
Conclusion
29(1)
References
29(1)
Collecting data
Some general comments
30(3)
Identifying a question
33(2)
Identification of variables
35(1)
Case definition
36(4)
Case ascertainment
40(1)
Planning data collection
41(2)
Selecting data collection software
43(1)
Data entry
44(1)
Pilot testing
45(1)
Quality control
46(2)
Source documentation
48(1)
Regulatory issues
48(1)
Conclusion
49(2)
Risk and published studies
Evaluating the quality of a study
51(3)
Classical clinical research
54(7)
Risk studies
61(3)
Determining the appropriateness of a reference population
64(3)
Studies that can be used for risk measurements
67(1)
Conclusion
68(1)
References
69(1)
Applying published risk estimates to local data
Standardization of rates
70(4)
Multivariable risk stratification
74(4)
Calculation of expected risk for a study sample
78(4)
The observed/expected ratio
82(3)
Interpretation issues
85(2)
Conclusion
87(1)
References
87(1)
Interpreting risk models
Population characteristics and their distribution
88(1)
Bias
89(6)
Missing data
95(2)
Presentation of results
97(6)
Administrative versus clinical data
103(2)
Some guidelines for application and interpretation of the methods
105(3)
Conclusion
108(1)
References
109(1)
Advanced issues
Types of studies
110(2)
Design issues
112(6)
Collecting data
118(2)
Univariate analysis
120(17)
Multivariate analysis
137(3)
Statistical significance
140(1)
Evaluating model prediction
141(3)
Variable coding
144(5)
Fit testing
149(3)
Plotting
152(3)
Interpretation
155(6)
Conclusion
161(1)
References
162(2)
Appendices
Appendix 1
164(2)
Appendix 2
166(1)
Appendix 3
167(4)
Index 171

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