Introduction
The need for performance monitoring
Measuring and monitoring quality
The need for this book
Who is this book for and how should it be used?
Common abbreviations used in the book
Acknowledgments
Origins and examples of monitoring
systemsOrigins
Healthcare scandals
Examples of monitoring schemes
Goals of monitoring
Choosing the unit of analysis and
reportingIssues principally concerning the analysis
Issues more relevant to reporting: attributing performance to a
given unit in a system
What to measure: choosing and defining
indicatorsHow can we define quality?
Common indicator taxonomies
The particular challenges of measuring patient safety
The particular challenges of multimorbidity
Measuring the health of the population and quality of the whole
healthcare system
Efficiency and value
Features of an ideal indicator
Steps in construction and common issues in definition
Validation of indicators
Some strategies for choosing among candidates
Time to go: when to withdraw indicators
Conclusion
Sources of dataHow to assess data quality
Administrative data
Clinical registry data
The accuracy of administrative and clinical databases compared
Indicent reports and other ways to capture safety events
Surverys
Other sources
Other issues concering data sources
Conclusion
Risk-adjustment principles and methodsRisk
adjustment and risk prediction
When and why should we adjust for risk?
Alteratives to risk adjustment
What factors should be adjust for?
Selecting an initial set of candidate variables
Dealing with missing and extreme values
Timing of the risk factor measurement
Building the model
Output the observed and model-predicted
outcomesRatios versus differences
Deriving SMRs from standardisation and logistic regression
Other fixed effects approaches to generate an SMR
Random effects based SMRs
Marginal versus multilevel models
Which is the "best" modelling approach overall?
Further reading on producing risk-adjusted outcomes by unit
Composite measuresSome examples
Steps in the construction
Some real examples
Pros and cons of composites
Setting performance thresholds and defining
outliersDefining acceptable performance
Bayesian methods for comparing providers
Statistical process control and funnel plots
Multiple testing
Ways of assessing variation between units
How much variation is "acceptable"?
The impact on outlier status of using fixed versus random effects
to derive SMRs
How reliably can we detect poor performance?
Some resources for quality improvement methods
Making comparisons across national
bordersExamples of multinational patient-level
databases
Challenges
Interpreting apparent differences in performance between
countries
Conclusion
Presenting the results to stakeholdersMain ways
of presenting comparative performance data
Effect on behaviour of the choice of format when providing
performance data
Importance of the method of presentation
Examples of giving performance information to units
Examples of giving performance information to the public
Metadata
Evaluating the monitoring systemStudy design
and statistical approaches to evalutating a monitoring system
Economic evaluation methods
Concluding thoughtsSimple versus complex
Specific versus general
The future
References
Appendix: glossary of main statistical terms used
Dr. Alex Bottle is a Senior Lecturer at Imperial College London,
UK
Dr. Paul Aylin is a Professor at Imperial College London, UK
"… Overall, the book provides an interesting and easily accessible
overview on health care performance monitoring and the statistical
methods associated with it. Each chapter has a short overview at
the beginning and sometimes a conclusion at the end, so it can also
serve as a reference book. According to the authors, this book is
not primarily aimed at statisticians, but all who want to compare
and measure health care performance. The level of statistics
obtained from an undergraduate nursing or medical degree is enough
to follow. Furthermore, the authors marked several chapters and
subchapters more heavy on statistics that can be skipped without
missing the big picture. The rich examples make the book enjoyable
to read and it has my unconditional recommendation to all
interested in the topic."
—Christoph F. Kurz, Helmholtz Zentrum Munich, in Biometrics, March
2018"Bottle and Aylin offer readers a practical approach to
performance measurement, and the statistical tools to get it right.
This topic may seem dry and arcane until you realize that these
methods are what patients and policymakers depend on to tell a good
hospital from a dangerous one, and a superb physician from a quack.
In fact, the authors learned their trade investigating some of the
most famous cases of medical scandals in the world, including a
hospital whose errors killed dozens of babies, and a murderous
physician who killed scores of patients. So, the lessons in this
book matter. Highly recommended."
—Robert M. Wachter, MD, Professor and Chair, Department of
Medicine, University of California, San Francisco"Improving
healthcare and ensuring patient safety relies on timely, valid and
understandable information. Healthcare systems are awash with data
but this seldom translates into useful information. The great value
of this book lies in the combination of statistical sophistication
with an understanding of the healthcare context and a practical
concern for improving the care of patients. Alex Bottle and Paul
Aylin have done us a great service by sharing their extensive
expertise and showing us how healthcare can be effectively
monitored and improved."
—Charles Vincent, Professor of Psychology, University of Oxford,
and Emeritus Professor Clinical Safety Research, Imperial College
London"This book is the most thorough, comprehensive and practical
review of hospital performance monitoring available to my
knowledge. Although a statistical manual, it is not overly
technical with very few formulae, and covers the ground in a
logical way. It is replete with examples and I particularly like
the tabulations of pros and cons of different methods and
approaches and summaries of current controversies.
It discusses real-world issues which affect policy makers,
practitioners and researchers alike and will be of value to all. I
wish I'd had this book when I was working in this area. I can
strongly recommend to anyone wishing to embark on the complexities
of performance monitoring, and everyone who is already engaged in
this area."
—Julian Flowers, Head of Public Health Data Science, Public Health
England
"… Overall, the book provides an interesting and easily accessible
overview on health care performance monitoring and the statistical
methods associated with it. Each chapter has a short overview at
the beginning and sometimes a conclusion at the end, so it can also
serve as a reference book. According to the authors, this book is
not primarily aimed at statisticians, but all who want to compare
and measure health care performance. The level of statistics
obtained from an undergraduate nursing or medical degree is enough
to follow. Furthermore, the authors marked several chapters and
subchapters more heavy on statistics that can be skipped without
missing the big picture. The rich examples make the book enjoyable
to read and it has my unconditional recommendation to all
interested in the topic."
—Christoph F. Kurz, Helmholtz Zentrum Munich, in Biometrics, March
2018"Bottle and Aylin offer readers a practical approach to
performance measurement, and the statistical tools to get it right.
This topic may seem dry and arcane until you realize that these
methods are what patients and policymakers depend on to tell a good
hospital from a dangerous one, and a superb physician from a quack.
In fact, the authors learned their trade investigating some of the
most famous cases of medical scandals in the world, including a
hospital whose errors killed dozens of babies, and a murderous
physician who killed scores of patients. So, the lessons in this
book matter. Highly recommended."
—Robert M. Wachter, MD, Professor and Chair, Department of
Medicine, University of California, San Francisco"Improving
healthcare and ensuring patient safety relies on timely, valid and
understandable information. Healthcare systems are awash with data
but this seldom translates into useful information. The great value
of this book lies in the combination of statistical sophistication
with an understanding of the healthcare context and a practical
concern for improving the care of patients. Alex Bottle and Paul
Aylin have done us a great service by sharing their extensive
expertise and showing us how healthcare can be effectively
monitored and improved."
—Charles Vincent, Professor of Psychology, University of Oxford,
and Emeritus Professor Clinical Safety Research, Imperial College
London"This book is the most thorough, comprehensive and practical
review of hospital performance monitoring available to my
knowledge. Although a statistical manual, it is not overly
technical with very few formulae, and covers the ground in a
logical way. It is replete with examples and I particularly like
the tabulations of pros and cons of different methods and
approaches and summaries of current controversies.
It discusses real-world issues which affect policy makers,
practitioners and researchers alike and will be of value to all. I
wish I'd had this book when I was working in this area. I can
strongly recommend to anyone wishing to embark on the complexities
of performance monitoring, and everyone who is already engaged in
this area."
—Julian Flowers, Head of Public Health Data Science, Public Health
England
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