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Making the most of common impact metrics: promising approaches that need further study

Authors
Journal
BMC Public Health
1471-2458
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Volume
13
Identifiers
DOI: 10.1186/1471-2458-13-s2-s8
Keywords
  • Commentary

Abstract

Making the most of common impact metrics: promising approaches that need further study COMMENTARY Open Access Making the most of common impact metrics: promising approaches that need further study John Grove*, Joseph W Brown, Philip W Setel There is considerable value in exploring whether and how a limited set of common health metrics, such as the ones presented in this supplement, can produce valid and reliable estimates of impact for global health and family planning. Through a shared vocabulary of transparent data elements drawn from routine service statistics, population-level measures, and measures of proven effect from rigorous trials, such metrics could provide a view of collective impact sufficient to reliably explore scenarios, set priorities, and inform action. This volume represents an important step in the right direction. The remainder of our commentary argues the case for continued work toward valid, common impact metrics and some other ways in which common metrics can contribute to our work. Specifically: more cost-effi- cient monitoring; better collective decision making; trans- parency and alignment; and enhanced accountability. Although we are enthusiastic about this line of scientific work and support the approach to planning, assessment, and performance management reflected in the papers here, there are some important caveats. While keeping the promise of modeled estimates in view, we believe more research into the validity and potential sources of bias and uncertainty in modeled impacts, and in the underlying source data, is required. More cost-efficient monitoring Assuming that routine collection and analysis of service provision data are strong, and that data are verified and robust, there are potential time and resource savings that modeled impact efforts offer. One widely-used global tool that illustrates the potential of this approach is the Lives Saved Tool or ‘LiST’ [1]. By using a variety of data sources to estimate potentially avertable child mor

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