Construction of a multisite datalink using electronic health records for the identification, surveillance, prevention, and management of diabetes mellitus: The SUPREME-DM project

Gregory A. Nichols, Jay Desai, Jennifer Elston Lafata, Jean M. Lawrence, Patrick J. O'Connor, Ram D. Pathak, Marsha A. Raebel, Robert J. Reid, Joseph V. Selby, Barbara G. Silverman, John F. Steiner, W. F. Stewart, Suma Vupputuri, Beth Waitzfelder, Christina Clarke, William Troy Donahoo, Glenn Goodrich, Andrea R. Paolino, Emily Schroeder, Michael ShainlineStan Xu, Lora Bounds, Gabrielle Gundersen, Katherine Newton, Eileen Rillamas-Sun, Brandon Geise, Ronald Harris, Rebecca Stametz, Xiaowei Sherry Yan, Nonna Akkerman, Liz Dobie, Aida Li, Heather Morris, Abraham Thomas, Mary Becker, Kris Ohnsorg, Nancy Sherwood, Ameena Ahmed, Cynthia Nakasato, John Parker, Rebecca Williams, Cathy Chou, Assiamira Ferrara, Andy Karter, Romain Neugebauer, Joe Selby, Julie Schmittdiel, Bix Swain, Brian Hazlehurst, Teresa Hillier, Terry Kimes, Eric Kopp, Stephen Kurtz, Daniel Sapp, Melissa Preciado, Jian Leon Zhang, Chengyi Zheng, Melissa Butler, Ashli Owen-Smith, Junling Ren, Douglas Roblin, Amit Acharya, Aaron Miller, Luke Rasmussen, Trish Siegler, Anthony Heymann, Jodi Segal, Michele Heisler

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107 Scopus citations


Introduction: Electronic health record (EHR) data enhance opportunities for conducting surveillance of diabetes. The objective of this study was to identify the number of people with diabetes from a diabetes DataLink developed as part of the SUPREME-DM (SUrveillance, PREvention, and ManagEment of Diabetes Mellitus) project, a consortium of 11 integrated health systems that use comprehensive EHR data for research. Methods: We identified all members of 11 health care systems who had any enrollment from January 2005 through December 2009. For these members, we searched inpatient and outpatient diagnosis codes, laboratory test results, and pharmaceutical dispensings from January 2000 through December 2009 to create indicator variables that could potentially identify a person with diabetes. Using this information, we estimated the number of people with diabetes and among them, the number of incident cases, defined as indication of diabetes after at least 2 years of continuous health system enrollment. Results: The 11 health systems contributed 15,765,529 unique members, of whom 1,085,947 (6.9%) met 1 or more study criteria for diabetes. The nonstandardized proportion meeting study criteria for diabetes ranged from 4.2% to 12.4% across sites. Most members with diabetes (88%) met multiple criteria. Of the members with diabetes, 428,349 (39.4%) were incident cases. Conclusion: The SUPREME-DM DataLink is a unique resource that provides an opportunity to conduct comparative effectiveness research, epidemiologic surveillance including longitudinal analyses, and population-based care management studies of people with diabetes. It also provides a useful data source for pragmatic clinical trials of prevention or treatment interventions.

Original languageEnglish (US)
Article number110311
JournalPreventing Chronic Disease
Issue number6
StatePublished - Jun 2012


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