Healthcare Quality Measurement: Volume 2, Statistical Methodology
Cambridge University Press (Verlag)
978-1-009-64818-9 (ISBN)
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This comprehensive guide presents a data science approach to healthcare quality measurement and provider profiling for policymakers, regulators, hospital quality leaders, clinicians, and researchers. Two volumes encompass basic and advanced statistical techniques and diverse practical applications. Volume 1 begins with a historical review followed by core concepts including measure types and attributes (bias, validity, reliability, power, sample size); data sources; target conditions and procedures; patient and provider observation periods; attribution level; risk modeling; social risk factors; outlier classification; data presentation; public reporting; and graphical approaches. Volume 2 introduces causal inference for provider profiling, focusing on hierarchical regression models. These models appropriately partition systematic and random variation in observations, accounting for within-provider clustering. Item Response Theory models are introduced for linking multiple categorical quality metrics to underlying quality constructs. Computational strategies are discussed, followed by various approaches to inference. Finally, methods to assess and compare model fit are presented.
Sharon-Lise T. Normand is S. James Adelstein Professor of Health Care Policy at Harvard University. She is an authority on the statistical methodology for hierarchical observational data, playing an essential role in emphasizing the importance of statistics in assessing the quality of healthcare. She is Fellow of the American Statistical Association (ASA), American College of Cardiology, American Heart Association (AHA), and American Association for the Advancement of Science. David M. Shahian is Professor of Surgery at Harvard Medical School. With his background as a cardiac surgeon, department chair, and health services researcher, he has been a pioneering leader in healthcare quality measurement and public reporting initiatives at the state and national levels. He has served on the National Quality Forum Board and Executive Committee and was Vice-President of Quality and Safety at Massachusetts General Hospital.
Preface and Acknowledgments; 18. Preliminaries; 19. A causal inference framework; 20. Introduction to hierarchical linear models; 21. Hierarchical generalized linear models; 22. Composite measures and multiple outcomes; 23. Computational approaches; 24. Inference for hierarchical generalized linear models; 25. Model assessment; 26. Future directions; Bibliography; Index.
| Erscheint lt. Verlag | 31.8.2026 |
|---|---|
| Zusatzinfo | Worked examples or Exercises |
| Verlagsort | Cambridge |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Statistik |
| Studium ► Querschnittsbereiche ► Epidemiologie / Med. Biometrie | |
| ISBN-10 | 1-009-64818-7 / 1009648187 |
| ISBN-13 | 978-1-009-64818-9 / 9781009648189 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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