Implementation science and its application to population health
- PMID: 23297655
- PMCID: PMC3901430
- DOI: 10.1146/annurev-publhealth-031912-114444
Implementation science and its application to population health
Abstract
Implementation science studies the use of strategies to adapt and use evidence-based interventions in targeted settings (e.g., schools, workplaces, health care facilities, public health departments) to sustain improvements to population health. This nascent field of research is in the early stages of developing theories of implementation and evaluating the properties of measures. Stakeholder engagement, effectiveness studies, research synthesis, and mathematical modeling are some of the methods used by implementation scientists to identify strategies to embed evidence-based interventions in clinical and public health programs. However, for implementation science to reach its full potential to improve population health the existing paradigm for how scientists create evidence, prioritize publications, and synthesize research needs to shift toward greater stakeholder input and improved reporting on external validity. This shift will improve the relevance of the research that is produced and provide information that will help guide decision makers in their selection of research-tested interventions.
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References
-
- Aarons GA, Horowitz JD, Dlugosz LR, Ehrhart MG. The role of organizational processes in dissemination and implementation research. 2012:128–153. See Ref. 7.
-
- Agency for Healthc. Res. Quality (AHRQ) Health Care Disparities in Rural Areas: Selected Findings from the 2004 National Healthcare Disparities Report AHRQ Publ. No. 05–P022. Rockville MD: AHRQ US Dep. Health Hum. Serv; 2005. http://archive.ahrq.gov/research/ruraldisp/ruraldispar.htm.
-
- Andersen R, Mullner R. Assessing the health objectives of the nation. Health Aff. 1990;9:152–162. - PubMed
-
- Archimedes. Press release. San Franc., Calif.: 2012. May 3rd, HHS enlists Archimedes Inc. to expand government’s use of health care modeling for forecasting quality and cost outcomes. http://archimedesmodel.com/PR-3-May-2012.
-
- Berkey CS, Hoaglin D, Mosteller F, Colditz GA. A random-effects regression model for meta-analysis. Stat. Med. 1995;14:395–411. - PubMed
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