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Health-weighted Composite Quality Metrics Offer Promise to Improve Health Outcomes in a Learning Health System

Authors:

Scott Braithwaite ,

New York University School of Medicine
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Nicholas Stine

New York City Health and Hospitals Corporation
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Abstract

Health systems sometimes adopt quality metrics without robust supporting evidence of improvements in quality and/or quantity of life, which may impair rather than facilitate improved health outcomes. In brief, there is now no easy way to measure how much “health” is conferred by a health system. However, we argue that this goal is achievable. Health-weighted composite quality metrics have the potential to measure “health” by synthesizing individual evidence-based quality metrics into a summary measure, utilizing relative weightings that reflect the relative amount of health benefit conferred by each constituent quality metric. Previously, it has been challenging to create health-weighted composite quality metrics because of methodological and data limitations. However, advances in health information technology and mathematical modeling of disease progression promise to help mitigate these challenges by making patient-level data more accessible and more actionable for use. Accordingly, it may now be possible to use health information technology to calculate and track a health-weighted composite quality metric for each patient that reflects the health benefit conferred to that patient by the health system. These health-weighted composite quality metrics can be employed for a multitude of important aims that improve health outcomes, including quality evaluation, population health maximization, health disparity attenuation, panel management, resource allocation, and personalization of care. We describe the necessary attributes, the possible uses, and the likely limitations and challenges of health-weighted composite quality metrics.
How to Cite: Braithwaite S, Stine N. Health-weighted Composite Quality Metrics Offer Promise to Improve Health Outcomes in a Learning Health System. eGEMs (Generating Evidence & Methods to improve patient outcomes). 2013;1(2):6. DOI: http://doi.org/10.13063/2327-9214.1022
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Published on 28 Oct 2013.
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