Risk Stratification: A Practical Guide for Clinicians

by Charles C. Miller , Michael J. Reardon , Hazim J. Safi

• ISBN13: 9780521669450
• ISBN10: 0521669456
• Format: Paperback
• Copyright: 2001-04-02
• Publisher: Cambridge University Press

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