Prognosis Research in Health CareConcepts, Methods, and Impact

Prognosis Research in Health CareConcepts, Methods, and Impact

Richard D. Riley, Danielle van der Windt, Peter Croft, and Karel G.M. Moons

Print publication date: Jan 2019

ISBN: 9780198796619

Publisher: Oxford University Press

Abstract

What is going to happen to me, doctor?’ ‘What outcomes am I likely to experience?’ ‘Will this treatment work for me?’ Prognosis—forecasting the future—has always been a part of medical practice and caring for the sick. In modern healthcare it now has a new importance, with large financial investments being made to personalize clinical decisions and tailor treatment strategies to improve individual health outcomes based on prognostic information. Prognosis research—the study of future outcomes in people with a particular health condition—provides the critical evidence for obtaining, evaluating, and implementing prognostic information within modern healthcare. This new book, written and edited by experts in the field, including clinicians, epidemiologists, statisticians, and other healthcare professionals, is a comprehensive and unified account of prognosis research in the broadest sense. It explains the concepts behind prognosis in medical practice and prognosis research, and provides a practical foundation for those developing, conducting, interpreting, synthesizing, and appraising prognosis studies. It recommends a framework of four basic prognosis research types, pioneered by the PROGRESS group, and provides explicit guidance on the conduct, analysis, and reporting of prognosis studies for each type. Key topics are overall prognosis in clinically relevant populations; prognostic factors associated with changes in prognosis across individuals; prognostic models for individual outcome risk prediction; and predictors of treatment effects. Examples are given of the impact of prognosis research across a broad range of healthcare topics, and the book also signals the latest developments in prognosis research, including systematic reviews and meta-analysis of prognosis studies, and the use of electronic health records and machine learning in prognosis research.