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Reading: Measuring intersectoral collaboration in a health care setting: A knowledge synthesis


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Measuring intersectoral collaboration in a health care setting: A knowledge synthesis


Nelly D Oelke ,

Michelle Lynn Stiphout,

Esther Suter,

Shelanne Hepp,

Mahnoush Rostami,

Arden Birney,

Robert Janke,

Cheryl Van Vliet-Brown


Introduction: The importance of integration across the continuum of care is not limited to the health care sector. Coordinating client care between sectors and including supportive services such as education and social services is considered an essential part of building a fully integrated health system. Building on previous integration research, this study is a part of a comprehensive systematic review focused on identifying indicator and measures of the key principles of integration. We identified 16 indicator domains through a modified Delphi process using an expert panel of policy-makers, decision-makers, providers, and researchers. Intersectoral collaboration was identified as one of two indicator domains for the first principle of successful health systems integration, Comprehensive Services across the Continuum of Care.

Methods: Search terms were generated for intersectoral collaboration to identify tools in the peer-reviewed and targeted gray literature. Tools were identified through a rigorous review process including abstract review, relevancy ratings, identifying additional articles in reference lists, quality ratings, and extraction. To avoid duplication of tools, only “tool development” articles were included in data extraction. If an article was found which used but did not develop an appropriate tool, the original article reporting the development and testing of the tool was identified and data was extracted from this source only. Notable exceptions included articles where the original tool was modified to measure intersectoral collaboration.

Results: A review of 650 abstracts identified 14 tools which measure intersectoral collaboration. Most of the tools were questionnaires or checklists and were created or tested in a health care setting or with health related outcomes. The tools collected information from organizations in different sectors in a number of differed ways. Distributing a questionnaire or checklist to multiple organizations to measure the perceived level of mutual collaboration was the most common way. Network analysis was also used and one tool measured intersectoral collaboration as a quadrant using a balanced scorecard approach.

The variables identified to measure intersectoral collaboration include identifying “high and low structure” between partnering organizations; a low level of connectivity represented “cooperation and coordination” and a high level of connectivity represented “collaboration and consolidation”. Other variables included looking at social networks, assessing interagency linkages, measuring the depth of integration in a model of human services integration, and system integration and change. All the tools came from medium-high to high quality empirical papers where in most cases the tools were tested and the psychometric properties were reported. Only one tool came from the gray literature.

Discussion: Only a small number of tools have been identified, but the diversity among these tools was substantial. Ranging from simple questionnaires to complicated network analyses a number of options were found to capture ways to measure these intersectoral relationships. Some tools not only measured intersectoral collaboration but also provided a blueprint for how to use and build collaborative relationships across health care sectors and the community. For instance, Browne’s Human Services Network Integration model and measure highlights the model and how integration between sectors can be facilitated and measured.

This study has a number of strengths and limitations. The review is strengthened by its thorough methodological approach. The fact that intersectoral collaboration is one indicator domain which is a part of the larger, comprehensive knowledge synthesis allows the results to contribute to the greater picture of healthcare integration. The size of the knowledge synthesis is a strength and a limitation. Given the size of the knowledge synthesis and the breadth of the topic areas, it is possible that articles and tools may have been missed despite extensive search and review strategies.

Conclusion: A lot of emphasis has been put on the importance of integrated health care systems; however, there are few ways to identify and measure indicators and outcomes related to health services integration. It is not only important to identify key dimensions or principles of integrated care but also to be able to measure progress towards these integrated systems. Intersectoral collaboration is an important indicator domain contributing to building and sustaining health care integration. Valid and reliable tools to measure collaboration are essential. As such, this knowledge synthesis provides a number of appropriate tools for users including researchers, policy- and decision-makers, and providers across a wide range of health care systems. In this study we focused on measuring the presence but not the impact of intersectoral collaboration; this is an area we hope to investigate in future research.

How to Cite: Oelke ND, Stiphout ML, Suter E, Hepp S, Rostami M, Birney A, et al.. Measuring intersectoral collaboration in a health care setting: A knowledge synthesis. International Journal of Integrated Care. 2016;16(6):A11. DOI:
Published on 16 Dec 2016.


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