Affiliation:
1. Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA, 02115, USA
Abstract
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.
Funder
National Institutes of Health
NIH
Publisher
Oxford University Press (OUP)
Subject
General Medicine,Epidemiology
Cited by
24 articles.
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