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Citation

Wu, Frances M.; Shortell, Stephen M.; Lewis, Valerie A.; Colla, Carrie H.; & Fisher, Elliott S. (2016). Assessing Differences between Early and Later Adopters of Accountable Care Organizations Using Taxonomic Analysis. Health Services Research, 51(6), 2318-2329. PMCID: PMC5134136

Abstract

OBJECTIVE: To compare early and later adopters of the accountable care organization (ACO) model, using the taxonomy of larger, integrated system; smaller, physician-led; and hybrid ACOs.
DATA SOURCES: The National Survey of ACOs, Waves 1 and 2.
STUDY DESIGN: Cluster analysis using the two-step clustering approach, validated using discriminant analysis. Wave 2 data analyzed separately to assess differences from Wave 1 and then data pooled across waves.
FINDINGS: Compared to early ACOs, later adopter ACOs included a greater breadth of provider group types and a greater proportion self-reported as integrated delivery systems. When data from the two time periods were combined, a three-cluster solution similar to the original cluster solution emerged. Of the 251 ACOs, 31.1 percent were larger, integrated system ACOs; 45.0 percent were smaller physician-led ACOs; and 23.9 percent were hybrid ACOs-compared to 40.1 percent, 34.0 percent, and 25.9 percent from Wave 1 clusters, respectively.
CONCLUSIONS: While there are some differences between ACOs formed prior to August 2012 and those formed in the following year, the three-cluster taxonomy appears to best describe the types of ACOs in existence as of July 2013. The updated taxonomy can be used by researchers, policy makers, and health care organizations to support evaluation and continued development of ACOs.

URL

http://dx.doi.org/10.1111/1475-6773.12473

Reference Type

Journal Article

Year Published

2016

Journal Title

Health Services Research

Author(s)

Wu, Frances M.
Shortell, Stephen M.
Lewis, Valerie A.
Colla, Carrie H.
Fisher, Elliott S.

Article Type

Regular

PMCID

PMC5134136

Data Set/Study

National Survey of ACOs

Continent/Country

United States

State

Nonspecific