Hospital‐based health systems 20 years later: A taxonomy for policy research and analysis

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

Reliability of Therapist Self-Report on Treatment Targets and Focus in Family-Based Intervention

Reliable therapist-report methods appear to be an essential component of quality assurance procedures to support adoption of evidence-based practices in usual care, but studies have found weak correspondence between therapist and observer ratings of treatment techniques. This study examined therapist reliability and accuracy in rating intervention target (i.e., session participants) and focus (i.e., session content) in a manual-guided, family-based preventive intervention implemented with 50 inner-city adolescents at risk for substance use. A total of 106 sessions selected from three phases of treatment were rated via post-session self-report by the participating therapist and also via videotape by nonparticipant coders. Both groups estimated the amount of session time devoted to model-prescribed treatment targets (adolescent, parent, conjoint) and foci (family, school, peer, prosocial, drugs). Therapists demonstrated excellent reliability with coders for treatment targets and moderate to high reliability for treatment foci across the sample and within each phase. Also, therapists did not consistently overestimate their degree of activity with targets or foci. Implications of study findings for fidelity assessment in routine settings are discussed