» Articles » PMID: 39177848

End-of-life Cohorts from the Dartmouth Institute: Risk Adjustment Across Health Care Markets, the Relative Efficiency of Chronic Illness Utilization, and Patient Experiences Near the End of Life

Overview
Publisher Springer
Specialty Health Services
Date 2024 Aug 23
PMID 39177848
Authors
Affiliations
Soon will be listed here.
Abstract

Since their inception, small area studies intended to measure health system performance have been challenged by concerns that regional variation in health care may be primarily explained by differences in patient health risk. Controlling for regional population differences depends on appropriate risk adjustment, but the adequacy of the methods used in early analyses was contested. A novel response to these concerns was the development of end-of-life cohorts by Dartmouth Atlas investigators. These were used initially to control for differences in population health status in studies investigating relative efficiency across regions. Later, they became useful for studying hospital-level variation in chronic illness care, and for measuring utilization and patient experiences at the very end of life. Altogether, end-of-life cohorts have been invaluable for clarifying the contribution of health system and provider factors to health care variation and outcomes.

References
1.
Siddiqui A, Ornstein K, Ankuda C . Prevalence of Treatment Burden in the Last Three Years of Life. J Palliat Med. 2020; 24(6):879-886. PMC: 8336237. DOI: 10.1089/jpm.2020.0170. View

2.
WENNBERG J, Mulley Jr A, Hanley D, Timothy R, Fowler Jr F, Roos N . An assessment of prostatectomy for benign urinary tract obstruction. Geographic variations and the evaluation of medical care outcomes. JAMA. 1988; 259(20):3027-30. View

3.
Temel J, Greer J, Muzikansky A, Gallagher E, Admane S, Jackson V . Early palliative care for patients with metastatic non-small-cell lung cancer. N Engl J Med. 2010; 363(8):733-42. DOI: 10.1056/NEJMoa1000678. View

4.
Barnato A, Herndon M, Anthony D, Gallagher P, Skinner J, Bynum J . Are regional variations in end-of-life care intensity explained by patient preferences?: A Study of the US Medicare Population. Med Care. 2007; 45(5):386-93. PMC: 2147061. DOI: 10.1097/01.mlr.0000255248.79308.41. View

5.
Zhang Y, Gupta A, Nicholson S, Li J . Elevated end-of-life spending: A new measure of potentially wasteful health care spending at the end of life. Health Serv Res. 2022; 58(1):186-194. PMC: 9836947. DOI: 10.1111/1475-6773.14093. View