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Original Research

Adopting the Triple Aim Framework in the Saudi Healthcare System: A Delphi Study

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Pages 2189-2197 | Published online: 19 Oct 2020
 

Abstract

Purpose

Helping healthcare systems to optimize performance using particular metrics through objective monitoring will positively impact an organization’s progress toward strategic goals and objectives. The Institute of Healthcare Improvement introduced the Triple Aim framework for guiding new or transforming health systems, concurrently improving population health and patients’ care experience, and reducing per capita cost. Consensus to determine applicable and appropriate measures to monitor this transformation within the scope of the three objectives is required. Thus, the study aimed to adopt the Triple Aim measures and reach a consensus among experts in healthcare systems on the applicability of the measures in the health system of Saudi Arabia.

Methods

A two-round Delphi study was conducted with 17 invited experts who were knowledgeable and experienced in healthcare systems and administration, quality improvement, and strategic planning. These rounds were based on the measures of the three objectives, where they were introduced as statements and grouped under each respective aim. The experts were instructed to score each measure using a 5-point Likert scale and were invited to formulate new measures related to the same aim. Statements reaching a consensus level of 80% were considered applicable measures for the Saudi health system.

Results

A total of 17 measures were circulated among experts; out of which, 16 measures reached a consensus. The 16 measures represent the three main domains of the Triple Aim model, ie, population health, experience of care, and cost per capita. The measure that failed to reach a consensus was the predictive model scores because it requires medical knowledge, where the majority of the experts were non-physicians.

Conclusion

A Delphi study was used to reach consensus among experts on the Triple Aim measures as a first step to building a solid foundation for the population management required to implement these initiatives in the future.

Acknowledgments

The Authors acknowledges the support provided by the  Deanship of Scientific Research through the Research Center in the College of Applied Medical Sciences at King Saud University. Also, the authors thank the Deanship of Scientific Research and RSSU at King Saud University for their technical support. In addition, the authors express appreciation for the experts who participated in the Delphi rounds.

Disclosure

The authors report no conflicts of interest for this work.

Additional information

Funding

The authors acknowledge the financial support provided by the Deanship of Scientific Research through the Research Center in the College of Applies Medical Sciences at King Saud University.