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Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.

Publication ,  Journal Article
Spratt, SE; Pereira, K; Granger, BB; Batch, BC; Phelan, M; Pencina, M; Miranda, ML; Boulware, E; Lucas, JE; Nelson, CL; Neely, B; Barth, P ...
Published in: J Am Med Inform Assoc
April 1, 2017

OBJECTIVE: We assessed the sensitivity and specificity of 8 electronic health record (EHR)-based phenotypes for diabetes mellitus against gold-standard American Diabetes Association (ADA) diagnostic criteria via chart review by clinical experts. MATERIALS AND METHODS: We identified EHR-based diabetes phenotype definitions that were developed for various purposes by a variety of users, including academic medical centers, Medicare, the New York City Health Department, and pharmacy benefit managers. We applied these definitions to a sample of 173 503 patients with records in the Duke Health System Enterprise Data Warehouse and at least 1 visit over a 5-year period (2007-2011). Of these patients, 22 679 (13%) met the criteria of 1 or more of the selected diabetes phenotype definitions. A statistically balanced sample of these patients was selected for chart review by clinical experts to determine the presence or absence of type 2 diabetes in the sample. RESULTS: The sensitivity (62-94%) and specificity (95-99%) of EHR-based type 2 diabetes phenotypes (compared with the gold standard ADA criteria via chart review) varied depending on the component criteria and timing of observations and measurements. DISCUSSION AND CONCLUSIONS: Researchers using EHR-based phenotype definitions should clearly specify the characteristics that comprise the definition, variations of ADA criteria, and how different phenotype definitions and components impact the patient populations retrieved and the intended application. Careful attention to phenotype definitions is critical if the promise of leveraging EHR data to improve individual and population health is to be fulfilled.

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Published In

J Am Med Inform Assoc

DOI

EISSN

1527-974X

Publication Date

April 1, 2017

Volume

24

Issue

e1

Start / End Page

e121 / e128

Location

England

Related Subject Headings

  • Sensitivity and Specificity
  • Phenotype
  • Medical Informatics
  • Humans
  • Glycated Hemoglobin
  • Electronic Health Records
  • Diabetes Mellitus, Type 2
  • Diabetes Mellitus
  • Algorithms
  • 46 Information and computing sciences
 

Citation

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Spratt, S. E., Pereira, K., Granger, B. B., Batch, B. C., Phelan, M., Pencina, M., … Jelesoff, N. (2017). Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus. J Am Med Inform Assoc, 24(e1), e121–e128. https://doi.org/10.1093/jamia/ocw123
Spratt, Susan E., Katherine Pereira, Bradi B. Granger, Bryan C. Batch, Matthew Phelan, Michael Pencina, Marie Lynn Miranda, et al. “Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.J Am Med Inform Assoc 24, no. e1 (April 1, 2017): e121–28. https://doi.org/10.1093/jamia/ocw123.
Spratt SE, Pereira K, Granger BB, Batch BC, Phelan M, Pencina M, et al. Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus. J Am Med Inform Assoc. 2017 Apr 1;24(e1):e121–8.
Spratt, Susan E., et al. “Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.J Am Med Inform Assoc, vol. 24, no. e1, Apr. 2017, pp. e121–28. Pubmed, doi:10.1093/jamia/ocw123.
Spratt SE, Pereira K, Granger BB, Batch BC, Phelan M, Pencina M, Miranda ML, Boulware E, Lucas JE, Nelson CL, Neely B, Goldstein BA, Barth P, Richesson RL, Riley IL, Corsino L, McPeek Hinz ER, Rusincovitch S, Green J, Barton AB, DDC Phenotype Group, Kelley C, Hyland K, Tang M, Elliott A, Ruel E, Clark A, Mabrey M, Morrissey KL, Rao J, Hong B, Pierre-Louis M, Kelly K, Jelesoff N. Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus. J Am Med Inform Assoc. 2017 Apr 1;24(e1):e121–e128.
Journal cover image

Published In

J Am Med Inform Assoc

DOI

EISSN

1527-974X

Publication Date

April 1, 2017

Volume

24

Issue

e1

Start / End Page

e121 / e128

Location

England

Related Subject Headings

  • Sensitivity and Specificity
  • Phenotype
  • Medical Informatics
  • Humans
  • Glycated Hemoglobin
  • Electronic Health Records
  • Diabetes Mellitus, Type 2
  • Diabetes Mellitus
  • Algorithms
  • 46 Information and computing sciences