Stephen M Shortell 1 , Daniel J Gottlieb 2 , Pablo Martinez Camblor 2 , A James O'Malley 2 Show Affiliations »
Abstract
OBJECTIVE: Building on the original taxonomy of hospital-based health systems from 20 years ago, we develop a new taxonomy to inform emerging public policy and practice developments. DATA SOURCES: The 2016 American Hospital Association's (AHA) Annual Survey; the 2016 IQVIA Healthcare Organizations and Systems (HCOS) database; and the 2017-2018 National Survey of Healthcare Organizations and Systems (NSHOS). STUDY DESIGN: Cluster analysis of the 2016 AHA Annual Survey data to derive measures of differentiation, centralization, and integration to create categories or types of hospital-based health systems. DATA COLLECTION: Principal components factor analysis with varimax rotation generating the factors used in the cluster algorithms. PRINCIPAL FINDINGS: Among the four cluster types, 54% (N = 202) of systems are decentralized (-0.35) and relatively less differentiated (-0.37); 23% of systems (N = 85) are highly differentiated (1.28) but relatively decentralized (-0.29); 15% (N = 57) are highly centralized (2.04) and highly differentiated (0.65); and approximately 9 percent (N = 33) are least differentiated (-1.35) and most decentralized (-0.64). Despite differences in calculation, the Highly Centralized, Highly Differentiated System Cluster and the Undifferentiated, Decentralized System Cluster were similar to those identified 20 years ago. The other two system clusters contained similarities as well as differences from those 20 years ago. Overall, 82 percent of the systems remain relatively decentralized suggesting they operate largely as holding companies allowing autonomy to individual hospitals operating within the system. CONCLUSIONS: The new taxonomy of hospital-based health systems bears similarities as well as differences from 20 years ago. Important applications of the taxonomy for addressing current challenges facing the healthcare system, such as the transition to value-based payment models, continued consolidation, and the growing importance of the social determinants of health, are highlighted. © Health Research and Educational Trust.
OBJECTIVE: Building on the original taxonomy of hospital-based health systems from 20 years ago, we develop a new taxonomy to inform emerging public policy and practice developments. DATA SOURCES: The 2016 American Hospital Association's (AHA) Annual Survey; the 2016 IQVIA Healthcare Organizations and Systems (HCOS) database; and the 2017-2018 National Survey of Healthcare Organizations and Systems (NSHOS). STUDY DESIGN: Cluster analysis of the 2016 AHA Annual Survey data to derive measures of differentiation, centralization, and integration to create categories or types of hospital-based health systems. DATA COLLECTION: Principal components factor analysis with varimax rotation generating the factors used in the cluster algorithms. PRINCIPAL FINDINGS: Among the four cluster types, 54% (N = 202) of systems are decentralized (-0.35) and relatively less differentiated (-0.37); 23% of systems (N = 85) are highly differentiated (1.28) but relatively decentralized (-0.29); 15% (N = 57) are highly centralized (2.04) and highly differentiated (0.65); and approximately 9 percent (N = 33) are least differentiated (-1.35) and most decentralized (-0.64). Despite differences in calculation, the Highly Centralized, Highly Differentiated System Cluster and the Undifferentiated, Decentralized System Cluster were similar to those identified 20 years ago. The other two system clusters contained similarities as well as differences from those 20 years ago. Overall, 82 percent of the systems remain relatively decentralized suggesting they operate largely as holding companies allowing autonomy to individual hospitals operating within the system. CONCLUSIONS: The new taxonomy of hospital-based health systems bears similarities as well as differences from 20 years ago. Important applications of the taxonomy for addressing current challenges facing the healthcare system, such as the transition to value-based payment models, continued consolidation, and the growing importance of the social determinants of health, are highlighted. © Health Research and Educational Trust.
Entities: Chemical
Keywords:
centralization; cluster analysis; differentiation; healthcare systems; integration
Mesh： See more »
Year: 2021
PMID： 33429460 PMCID： PMC8143673 DOI： 10.1111/1475-6773.13621
Source DB: PubMed Journal: Health Serv Res ISSN： 0017-9124 Impact factor: 3.734