The Importance of Understanding and Measuring Health System Structural, Functional, and Clinical Integration

Published in: Health Services Research, Volume 55, Issue S3, Special Issue: Comparative Health System Performance, pages 1049–1061 (December 2020). doi: 10.1111/1475-6773.13582

Posted on RAND.org on December 10, 2020

by M. Susan Ridgely, Christine Buttorff, Laura J. Wolf, Erin Lindsey Duffy, Ashlyn Tom, Cheryl L. Damberg, Dennis P. Scanlon, Mary E. Vaiana

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Objective

We explore if there are ways to characterize health systems—not already revealed by secondary data—that could provide new insights into differences in health system performance. We sought to collect rich qualitative data to reveal whether and to what extent health systems vary in important ways across dimensions of structural, functional, and clinical integration.

Data Sources

Interviews with 162 c-suite executives of 24 health systems in four states conducted through "virtual" site visits between 2017 and 2019.

Study Design

Exploratory study using thematic comparative analysis to describe factors that may lead to high performance.

Data Collection

We used maximum variation sampling to achieve diversity in size and performance. We conducted, transcribed, coded, and analyzed in-depth, semi-structured interviews with system executives, covering such topics as market context, health system origin, organizational structure, governance features, and relationship of health system to affiliated hospitals and POs.

Principal Findings

Health systems vary widely in size and ownership type, complexity of organization and governance arrangements, and ability to take on risk. Structural, functional, and clinical integration vary across systems, with considerable activity around centralizing business functions, aligning financial incentives with physicians, establishing enterprise-wide EHR, and moving toward single signatory contracting. Executives describe clinical integration as more difficult to achieve, but essential. Studies that treat "health system" as a binary variable may be inappropriately aggregating for analysis health systems of very different types, at different degrees of maturity, and at different stages of structural, functional, and clinical integration. As a result, a "signal" indicating performance may be distorted by the "noise."

Conclusions

Developing ways to account for the complex structures of today's health systems can enhance future efforts to study systems as complex organizations, to assess their performance, and to better understand the effects of payment innovation, care redesign, and other reforms.

Research conducted by

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