A Population Health Measurement Framework: Evidence-Based Metrics for Assessing Community-Level Population Health in the Global Budget Context
Author(s) -
Elham Hatef,
Elyse C. Lasser,
Hadi Kharrazi,
Chad Perman,
Russ Montgomery,
Jonathan P. Weiner
Publication year - 2017
Publication title -
population health management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.998
H-Index - 40
eISSN - 1942-7905
pISSN - 1942-7891
DOI - 10.1089/pop.2017.0112
Subject(s) - population health , population , public health , health indicator , context (archaeology) , health policy , health care , interoperability , conceptual framework , hrhis , data science , computer science , environmental health , medicine , geography , political science , nursing , epistemology , law , philosophy , archaeology , operating system
Population health is one of the pillars of the Triple Aim to improve US health care. The authors developed a framework for population health measurement and a proposed set of measures for further exploration to guide the population health efforts in Maryland. The authors searched peer-reviewed, expert-authored literature and current public health measures. Using a semi-structured analysis, a framework was proposed, which consisted of a conceptual model of several domains and identified population health measures addressing them. Stakeholders were convened to review the framework and identified the most feasible population health measures considering the underlying health information technology (IT) infrastructure in Maryland. The framework was organized based on health system factors, determinants of health, and population-based and clinical outcomes. Measurement specifications were developed that addressed different aspects of selected measures and assessed various national and local data sources for selected measures. Data sources were identified based on their key characteristics, challenges, opportunities, and potential applicability to the proposed measures, as well as the issue of interoperability of data sources among different organizations. The proposed framework and measures can act as a platform to quantify the determinants of health and the state overall population health goals. Key considerations for developing a population health measures framework include health IT infrastructure, data denominators, feasibility, health system environment, and policy factors. Measurement development and progression using the framework will largely depend on the users' focus areas and availability of data. The authors believe that the proposed framework and road map can serve as a model for communities elsewhere.
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