Towards a unified taxonomy of health indicators: academic health centers and communities working together to improve population health

Abstract

The Clinical and Translational Science Awards (CTSA) program represents a significant public investment. To realize its major goal of improving the public's health and reducing health disparities, the CTSA Consortium's Community Engagement Key Function Committee has undertaken the challenge of developing a taxonomy of community health indicators. The objective is to initiate a unified approach for monitoring progress in improving population health outcomes. Such outcomes include, importantly, the interests and priorities of community stakeholders, plus the multiple, overlapping interests of universities and of the public health and health care professions involved in the development and use of local health care indicators.The emerging taxonomy of community health indicators that the authors propose supports alignment of CTSA activities and facilitates comparative effectiveness research across CTSAs, thereby improving the health of communities and reducing health disparities. The proposed taxonomy starts at the broadest level, determinants of health; subsequently moves to more finite categories of community health indicators; and, finally, addresses specific quantifiable measures. To illustrate the taxonomy's application, the authors have synthesized 21 health indicator projects from the literature and categorized them into international, national, or local/special jurisdictions. They furthered categorized the projects within the taxonomy by ranking indicators with the greatest representation among projects and by ranking the frequency of specific measures. They intend for the taxonomy to provide common metrics for measuring changes to population health and, thus, extend the utility of the CTSA Community Engagement Logic Model. The input of community partners will ultimately improve population health.

Figure 1

Hierarchical or nested relationship among community health indicators, based on the need to express observations ranging from broad-based determinants of health to highly specific, quantifiable and measureable phenomena.