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Abstract

Observational healthcare databases offer significant potential for generating evidence about the effects of medical products. Recent US and international efforts attempt to coordinate analysis activities across observational data networks for active drug safety surveillance and comparative effectiveness research. Several statistical challenges exist that require further research to inform the appropriate use of observational data for identifying and evaluating temporal relationships between medical product exposures and outcomes. This review highlights current work across the areas of data quality, methods development, and performance evaluation that promise to contribute to our understanding of best practices for observational analyses moving forward.

Keywords

drug safety active surveillance epidemiology comparative effectiveness

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References

Report to the President Realizing the Full Potential of Health Information Technology to Improve Healthcare for Americans: The Path Forward. 2010, President’s Council of Advisors on Science and Technology.

Public Law 110-85: Food and Drug Administration Amendments Act of 2007. 2007.

Woodcock

Behrman

Dal Pan

. Role of postmarketing surveillance in contemporary medicine. Ann Rev Med 2011; 62: 1–10.

Behrman

Benner

Brown

McClellan

Woodcock

Platt

. Developing the Sentinel System – a national resource for evidence development. N Engl J Med 2011; 364: 498–499.

Stang

Ryan

Racoosin

et al.

Advancing the science for active surveillance: rationale and design for the observational medical outcomes partnership. Ann Intern Med 2010; 153(9): 600–606.

IMI-PROTECT available from: http://www.imi-protect.eu/ (2009, cited 28 November 2009).

Coloma

Schuemie

Trifirò

et al.

Combining electronic healthcare databases in Europe to allow for large-scale drug safety monitoring: the EU-ADR Project. Pharmacoepidemiol Drug Saf 2011; 20(1): 1–11.

Federal Coordinating Council for Comparative Effectiveness Research Report to the President and the Congress. 2009, US Department of Health and Human Services.

Overhage

. Sensible use of observational clinical data. Stat Meth Med Res 2013; 22(1): 7–13.

10.

Shen

Robins

. On weighting approaches for missing data. Stat Meth Med Res 2013; 22(1): 14–30.

11.

Shen

. Linkage of patient records from disparate sources. Stat Meth Med Res 2013; 22(1): 31–38.

12.

Zorych

Madigan

Ryan

Bate

. Disproportionality methods for pharmacovigilance in longitudinal observational databases. Stat Meth Med Res 2013; 22(1): 39–56.

13.

Noren

Hopstadius

Bate

. Shrinkage observed-to-expected ratios for robust and transparent large-scale pattern discovery. Stat Meth Med Res 2013; 22(1): 57–69.

14.

Danaei

Rodríguez

LAG

Cantero

Logan

Hernán

. Observational data for comparative effectiveness research: An emulation of randomised trials of statins and primary prevention of coronary heart disease. Stat Meth Med Res 2013; 22(1): 70–96.

15.

Beach

Powell

Pattishall

Ryan

Mera

. Performance of a semi-automated approach for risk estimation using a common data model for longitudinal healthcare databases. Stat Meth Med Res 2013; 22(1): 97–110.

Statistical challenges in systematic evidence generation through analysis of observational healthcare data networks

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