Description
Book SynopsisThe promotion of standards and guidelines to advance quality assurance and control is an integral part of the health care sector. Quantitative methods are needed to monitor, control and improve the quality of medical processes.
Trade Review"The book is a good resource to have on your desk. I hope that future editions will incorporate some of the previously mentioned constructive suggestions, since the book has the potential to serve as an excellent reference for researchers and practioners in the health sciences." (
The American Statistician, November 2008)
"The book is a good resource to have on your desk. I hope that future editions will incorporate some of the previously mentioned constructive suggestions, since the book has the potential to serve as an excellent reference for researchers and practioners in the health sciences." (The American Statistician, November 2008)
"I recommend this book to people involved in clinical work who wish to learn about control charts and risk adjustment." (Biometrics, June 2008)
"I have greatly benefited from reading this book and I strongly recommend it for all academic libraries." (Journal of Applied Statistics, January 2008)
Table of ContentsPreface.
Acknowledgements.
Introduction – on quality of health care in general.
I.1 Quality of health care.
I.2 Measures and indicators of quality of health care.
I.3 The functions of quality measures and indicators.
References.
Part I Control Charts.
1 Theory of statistical process control.
1.1 Statistical foundation of control charts.
1.2 Use of control charts.
1.3 Design of control charts.
1.4 Rational samples.
1.5 Analysing the properties of a control chart.
1.6 Checklists and Pareto charts.
1.7 Clinical applications of control charts.
1.8 Inappropriate changes of a process.
References.
2 Shewhart control charts.
2.1 Control charts for discrete data.
2.2 Control charts for continuous data.
2.3 Control charts for variable sample size.
References.
3 Time-weighted control charts.
3.1 Shortcomings of Shewhart charts.
3.2 Cumulative sum charts.
3.3 Exponentially weighted moving average (EWMA) charts.
References.
4 Control charts for autocorrelated data.
4.1 Time series analysis.
4.2 Tests of independence of measurements.
4.3 Control charts for autocorrelated data.
4.4 Effect of choice of process standard deviation estimator.
References.
Part II Risk Adjustment.
5 Tools for risk adjustment.
5.1 Variables.
5.2 Statistical models.
5.3 Regression on continuous outcome measure.
5.4 Logistic regression on binary data.
5.5 Assessing the quality of a regression model.
References.
6 Risk-adjusted control charts.
6.1 Risk adjustment.
6.2 Risk-adjusted control charts.
6.3 Comments.
References.
7 Risk-adjusted comparison of healthcare providers.
7.1 Experimental adjustment.
7.2 Statistical risk adjustment of observational data.
7.3 Perils of risk adjusting observational data.
7.4 Public report cards.
References.
Part III Learning and Quality Assessment.
8 Learning curves.
8.1 Assessing a single learning curve.
8.2 Assessing multiple learning curves.
8.3 Factors affecting learning curves.
8.4 Learning curves and randomised clinical trials.
References.
9 Assessing the quality of clinical processes.
9.1 Data processing requirement.
9.2 Benchmarking of processes in statistical control.
9.3 Dealing with processes that are not in statistical control in the same state.
9.4 Overdispersion.
9.5 Multiple significance testing.
References.
Appendix A – Basic statistical concepts.
A.1 An example of random sampling.
A.2 Data.
A.3 Probability distributions.
A.4 Using the data.
References.
Appendix B – X and S chart with variable sample size.
Appendix C – Moving range estimator of the standard deviation of an AR (1) process.
References.
Index.
