Risk Adjustment Models
Risk Adjustment Models is a statistical framework used in healthcare analytics that belongs to the class of predictive modeling techniques, distinguished by its specific purpose of adjusting for differences in patient health status and demographic characteristics to enable fair comparisons of healthcare costs, utilization, or outcomes across providers or plans.
385
Publications
26.5K
Citations
1.5K
Authors
601
Institutions
Publications per year
2017–2026
96
Parents
385
The Department of Veterans Affairs' NSQIP
Shukri F. Khuri, Jennifer Daley, William G. Henderson et al. · Annals of Surgery · 1998 · 1.5K citations · Full text
Mark E. Cohen, Clifford Y. Ko, Karl Y. Bilimoria et al. · Journal of the American College of Surgeons · 2013 · 577 citations
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Harvard University
Cambridge, United States
21 h-index
62 publications
2.8K citations
University of Michigan
Ann Arbor, United States
17 h-index
43 publications
3.6K citations

Johns Hopkins University
Baltimore, United States
15 h-index
58 publications
2.8K citations
Boston University
Boston, United States
12 h-index
29 publications
1.9K citations
Stanford University
Stanford, United States
11 h-index
26 publications
1.6K citations
Northwestern University
Evanston, United States
11 h-index
23 publications
2K citations

Brigham and Women's Hospital
Boston, United States
11 h-index
24 publications
6K citations
Case Western Reserve University
Cleveland, United States
11 h-index
34 publications
1.7K citations
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35 publications · 2.7K citations
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Repository · 28 publications · 1.5K citations
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12 publications · 556 citations
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HSR · 11 publications · 686 citations
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6 publications · 746 citations
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