Full Description
"What is going to happen to me?" Most patients ask this question during a clinical encounter with a health professional. As well as learning what problem they have (diagnosis) and what needs to be done about it (treatment), patients want to know about their future health and wellbeing (prognosis). Prognosis research can provide answers to this question and satisfy the need for individuals to understand the possible outcomes of their condition, with and without treatment.
Central to modern medical practise, the topic of prognosis is the basis of decision making in healthcare and policy development. It translates basic and clinical science into practical care for patients and populations. Prognosis Research in Healthcare: Concepts, Methods and Impact provides a comprehensive overview of the field of prognosis and prognosis research and gives a global perspective on how prognosis research and prognostic information can improve the outcomes of healthcare. It details how to design, carry out, analyse and report prognosis studies, and how prognostic information can be the basis for tailored, personalised healthcare. In particular, the book discusses how information about the characteristics of people, their health, and environment can be used to predict an individual's future health.
Prognosis Research in Healthcare: Concepts, Methods and Impact, addresses all types of prognosis research and provides a practical step-by-step guide to undertaking and interpreting prognosis research studies, ideal for medical students, health researchers, healthcare professionals and methodologists, as well as for guideline and policy makers in healthcare wishing to learn more about the field of prognosis.
Contents
Part 1: Introduction to prognosis and prognosis research
1: Peter Croft, Richard D. Riley, Danielle A. van der Windt, and Karel G.M. Moons: Prognosis in healthcare
2: Peter Croft, Richard D. Riley, Danielle A. van der Windt, Karel G.M. Moons, and Harry Hemingway: A framework for prognosis research
Part 2: Fundamental statistics for prognosis research
3: Richard D. Riley, Kym I.E. Snell, Karel G.M. Moons, and Thomas P.A. Debray: Fundamental statistical methods for prognosis research
4: Richard D. Riley, Kym I.E. Snell, Karel G.M. Moons, and Thomas P.A. Debray: Ten principles to strengthen prognosis research
Part 3: Undertaking prognosis research
5: Danielle A. van der Windt, Harry Hemingway, Peter Croft: Overall prognosis research
6: Richard D. Riley, Karel G.M. Moons, Jill A. Hayden, Willi Sauerbrei, Douglas G. Altman: Prognostic factor research
7: Richard D. Riley, Karel G.M. Moons, Thomas P.A. Debray, Kym I.E. Snell, Ewout W. Steyerberg, Douglas G. Altman, Gary S. Collins: Prognostic model research
8: Danielle A. van der Windt, Richard D. Riley, Aroon Hingorani, Karel G.M. Moons: Predictors of treatment effect
9: Richard D. Riley, Karel G.M. Moons, Thomas P.A. Debray, Douglas G. Altman, Gary S. Collins: Systematic reviews and meta-analysis of prognosis research studies
Part 4: Exemplars of prognosis research impact
10: Nadine E Foster, Danielle A. van der Windt, Kate M. Dunn, Peter Croft: Prognosis research in people with low back pain
11: Adam Timmis, Pablo Perel, Peter Croft: Prognosis research in people with coronary heart disease
12: Katherine I. Morley, Pablo Perel: Prognosis research in people with traumatic bleeding
Part 5: Novel Topics in prognosis research
13: Richard D. Riley, Thomas P.A. Debray, Karel G.M.Moons: Individual participant data meta-analysis of prognosis studies
14: Kelvin P. Jordan, Karel G.M. Moons: Electronic healthcare records and prognosis research
15: Michael J. Crowther, Mark J Rutherford: Novel statistical methods for prognosis research
16: Mihaela van der Schaar, Harry Hemingway: Machine learning in prognosis research
