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

Research output: Contribution to journalArticle

65 Citations (Scopus)

Abstract

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
Volume9
Issue number6
DOIs
StatePublished - Jun 2012
Externally publishedYes

Fingerprint

Electronic Health Records
Diabetes Mellitus
Health
Pragmatic Clinical Trials
Comparative Effectiveness Research
Epidemiological Monitoring
Clinical Laboratory Techniques
Information Storage and Retrieval
Inpatients
Outpatients
Delivery of Health Care
Research
Pharmaceutical Preparations
Population
Therapeutics

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health Policy

Cite this

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

In: Preventing chronic disease, Vol. 9, No. 6, 110311, 06.2012.

Research output: Contribution to journalArticle

Nichols, GA, Desai, J, Lafata, JE, Lawrence, JM, O'Connor, PJ, Pathak, RD, Raebel, MA, Reid, RJ, Selby, JV, Silverman, BG, Steiner, JF, Stewart, WF, Vupputuri, S, Waitzfelder, B, Clarke, C, Donahoo, WT, Goodrich, G, Paolino, AR, Schroeder, E, Shainline, M, Xu, S, Bounds, L, Gundersen, G, Newton, K, Rillamas-Sun, E, Geise, B, Harris, R, Stametz, R, Yan, XS, Akkerman, N, Dobie, L, Li, A, Morris, H, Thomas, A, Becker, M, Ohnsorg, K, Sherwood, N, Ahmed, A, Nakasato, C, Parker, J, Williams, R, Chou, C, Ferrara, A, Karter, A, Neugebauer, R, Selby, J, Schmittdiel, J, Swain, B, Hazlehurst, B, Hillier, T, Kimes, T, Kopp, E, Kurtz, S, Sapp, D, Preciado, M, Zhang, JL, Zheng, C, Butler, M, Owen-Smith, A, Ren, J, Roblin, D, Acharya, A, Miller, A, Rasmussen, L, Siegler, T, Heymann, A, Segal, J & Heisler, M 2012, 'Construction of a multisite datalink using electronic health records for the identification, surveillance, prevention, and management of diabetes mellitus: The SUPREME-DM project', Preventing chronic disease, vol. 9, no. 6, 110311. https://doi.org/10.5888/pcd9.110311
Nichols, Gregory A. ; Desai, Jay ; Lafata, Jennifer Elston ; Lawrence, Jean M. ; O'Connor, Patrick J. ; Pathak, Ram D. ; Raebel, Marsha A. ; Reid, Robert J. ; Selby, Joseph V. ; Silverman, Barbara G. ; Steiner, John F. ; Stewart, W. F. ; Vupputuri, Suma ; Waitzfelder, Beth ; Clarke, Christina ; Donahoo, William Troy ; Goodrich, Glenn ; Paolino, Andrea R. ; Schroeder, Emily ; Shainline, Michael ; Xu, Stan ; Bounds, Lora ; Gundersen, Gabrielle ; Newton, Katherine ; Rillamas-Sun, Eileen ; Geise, Brandon ; Harris, Ronald ; Stametz, Rebecca ; Yan, Xiaowei Sherry ; Akkerman, Nonna ; Dobie, Liz ; Li, Aida ; Morris, Heather ; Thomas, Abraham ; Becker, Mary ; Ohnsorg, Kris ; Sherwood, Nancy ; Ahmed, Ameena ; Nakasato, Cynthia ; Parker, John ; Williams, Rebecca ; Chou, Cathy ; Ferrara, Assiamira ; Karter, Andy ; Neugebauer, Romain ; Selby, Joe ; Schmittdiel, Julie ; Swain, Bix ; Hazlehurst, Brian ; Hillier, Teresa ; Kimes, Terry ; Kopp, Eric ; Kurtz, Stephen ; Sapp, Daniel ; Preciado, Melissa ; Zhang, Jian Leon ; Zheng, Chengyi ; Butler, Melissa ; Owen-Smith, Ashli ; Ren, Junling ; Roblin, Douglas ; Acharya, Amit ; Miller, Aaron ; Rasmussen, Luke ; Siegler, Trish ; Heymann, Anthony ; Segal, Jodi ; Heisler, Michele. / Construction of a multisite datalink using electronic health records for the identification, surveillance, prevention, and management of diabetes mellitus : The SUPREME-DM project. In: Preventing chronic disease. 2012 ; Vol. 9, No. 6.
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abstract = "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.",
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T1 - Construction of a multisite datalink using electronic health records for the identification, surveillance, prevention, and management of diabetes mellitus

T2 - The SUPREME-DM project

AU - Nichols, Gregory A.

AU - Desai, Jay

AU - Lafata, Jennifer Elston

AU - Lawrence, Jean M.

AU - O'Connor, Patrick J.

AU - Pathak, Ram D.

AU - Raebel, Marsha A.

AU - Reid, Robert J.

AU - Selby, Joseph V.

AU - Silverman, Barbara G.

AU - Steiner, John F.

AU - Stewart, W. F.

AU - Vupputuri, Suma

AU - Waitzfelder, Beth

AU - Clarke, Christina

AU - Donahoo, William Troy

AU - Goodrich, Glenn

AU - Paolino, Andrea R.

AU - Schroeder, Emily

AU - Shainline, Michael

AU - Xu, Stan

AU - Bounds, Lora

AU - Gundersen, Gabrielle

AU - Newton, Katherine

AU - Rillamas-Sun, Eileen

AU - Geise, Brandon

AU - Harris, Ronald

AU - Stametz, Rebecca

AU - Yan, Xiaowei Sherry

AU - Akkerman, Nonna

AU - Dobie, Liz

AU - Li, Aida

AU - Morris, Heather

AU - Thomas, Abraham

AU - Becker, Mary

AU - Ohnsorg, Kris

AU - Sherwood, Nancy

AU - Ahmed, Ameena

AU - Nakasato, Cynthia

AU - Parker, John

AU - Williams, Rebecca

AU - Chou, Cathy

AU - Ferrara, Assiamira

AU - Karter, Andy

AU - Neugebauer, Romain

AU - Selby, Joe

AU - Schmittdiel, Julie

AU - Swain, Bix

AU - Hazlehurst, Brian

AU - Hillier, Teresa

AU - Kimes, Terry

AU - Kopp, Eric

AU - Kurtz, Stephen

AU - Sapp, Daniel

AU - Preciado, Melissa

AU - Zhang, Jian Leon

AU - Zheng, Chengyi

AU - Butler, Melissa

AU - Owen-Smith, Ashli

AU - Ren, Junling

AU - Roblin, Douglas

AU - Acharya, Amit

AU - Miller, Aaron

AU - Rasmussen, Luke

AU - Siegler, Trish

AU - Heymann, Anthony

AU - Segal, Jodi

AU - Heisler, Michele

PY - 2012/6

Y1 - 2012/6

N2 - 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.

AB - 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.

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