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- Title
Intersections of machine learning and epidemiological methods for health services research.
- Authors
Rose, Sherri
- Abstract
The field of health services research is broad and seeks to answer questions about the health care system. It is inherently interdisciplinary, and epidemiologists have made crucial contributions. Parametric regression techniques remain standard practice in health services research with machine learning techniques currently having low penetrance in comparison. However, studies in several prominent areas, including health care spending, outcomes and quality, have begun deploying machine learning tools for these applications. Nevertheless, major advances in epidemiological methods are also as yet underleveraged in health services research. This article summarizes the current state of machine learning in key areas of health services research, and discusses important future directions at the intersection of machine learning and epidemiological methods for health services research.
- Subjects
MACHINE learning; MEDICAL care; MEDICAL care costs; PUBLIC health research; HEALTH service areas; MEDICAL care research; RESEARCH funding
- Publication
International Journal of Epidemiology, 2020, Vol 49, Issue 6, p1763
- ISSN
0300-5771
- Publication type
journal article
- DOI
10.1093/ije/dyaa035