Literature DB >> 33006179

High concordance between chart review adjudication and electronic medical record data to identify prevalent and incident diabetes mellitus among persons with and without HIV.

Kathleen A McGinnis1, Amy C Justice1,2,3, Sam Bailin4, Melissa Wellons4, Matthew Freiberg4,5, John R Koethe4,5.   

Abstract

BACKGROUND: Electronic medical records (EMR) represent a rich source of data, but the value of EMR for health research relies on accurate ascertainment of clinical diagnoses. Identifying diabetes in EMR is complicated by the variety of accepted diagnostic criteria, some of which can be confounded by conditions such as HIV infection. We compared EMR-based criteria for estimating diabetes prevalence and incidence in the Veterans Health Administration (VHA), overall and by HIV status, against physician chart review and adjudication. RESEARCH DESIGN AND METHODS: We used laboratory values (serum glucose and hemoglobin A1c% [HbA1c]), ICD-9 codes, and medication records from the United States Veterans Aging Cohort Study Biomarker Cohort to identify veterans with any indication of diabetes in the EMR for subsequent physician adjudication. Sensitivity, specificity, PPV, NPV, and kappa statistics were used to evaluate agreement of EMR-based diabetes diagnoses with chart review adjudicated diagnoses.
RESULTS: EMR entries were reviewed for 1546 persons with HIV (PWH) and 843 HIV-negative participants through 2015. Agreement was at least moderate overall (kappa ≥ 0.42) for all pre-specified measures and among PWH vs HIV-negative, and African-American vs white sub-groups. Having at least one HbA1c ≥6.5% provided substantial agreement with chart adjudication for prevalent and incident diabetes (kappa = 0.89 and 0.73).
CONCLUSIONS: Identification of those with diabetes nationally within the VHA can be used in future studies to evaluate treatments, health outcomes, and adjust for diabetes in epidemiologic studies. Our methodology may provide insights for other organizations seeking to use EMR data for accurate determination of diabetes.
© 2020 John Wiley & Sons Ltd.

Entities:  

Keywords:  HIV; diabetes mellitus; electronic medical record; pharmacoepidemiology; validation

Mesh:

Year:  2020        PMID: 33006179      PMCID: PMC7810212          DOI: 10.1002/pds.5111

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  25 in total

1.  Inappropriately low glycated hemoglobin values and hemolysis in HIV-infected patients.

Authors:  Marie-Emilienne Diop; Jean-Philippe Bastard; Natacha Meunier; Sandrine Thévenet; Mustapha Maachi; Jacqueline Capeau; Gilles Pialoux; Corinne Vigouroux
Journal:  AIDS Res Hum Retroviruses       Date:  2006-12       Impact factor: 2.205

2.  Standards of medical care in diabetes--2010.

Authors: 
Journal:  Diabetes Care       Date:  2010-01       Impact factor: 19.112

3.  Physician and coding errors in patient records.

Authors:  S S Lloyd; J P Rissing
Journal:  JAMA       Date:  1985-09-13       Impact factor: 56.272

4.  Glucose-independent, black-white differences in hemoglobin A1c levels: a cross-sectional analysis of 2 studies.

Authors:  David C Ziemer; Paul Kolm; William S Weintraub; Viola Vaccarino; Mary K Rhee; Jennifer G Twombly; K M Venkat Narayan; David D Koch; Lawrence S Phillips
Journal:  Ann Intern Med       Date:  2010-06-15       Impact factor: 25.391

5.  Utility of glycated hemoglobin in diagnosing type 2 diabetes mellitus: a community-based study.

Authors:  Padala Ravi Kumar; Anil Bhansali; Muthuswamy Ravikiran; Shobhit Bhansali; Pinaki Dutta; J S Thakur; Naresh Sachdeva; Sanjay Kumar Bhadada; Rama Walia
Journal:  J Clin Endocrinol Metab       Date:  2010-04-06       Impact factor: 5.958

6.  Weight Gain and Incident Diabetes Among HIV-Infected Veterans Initiating Antiretroviral Therapy Compared With Uninfected Individuals.

Authors:  Melissa Herrin; Janet P Tate; Kathleen M Akgün; Adeel A Butt; Kristina Crothers; Matthew S Freiberg; Cynthia L Gibert; David A Leaf; David Rimland; Maria C Rodriguez-Barradas; Chris B Ruser; Kevan C Herold; Amy C Justice
Journal:  J Acquir Immune Defic Syndr       Date:  2016-10-01       Impact factor: 3.731

7.  Medical disease and alcohol use among veterans with human immunodeficiency infection: A comparison of disease measurement strategies.

Authors:  Amy C Justice; Elaine Lasky; Kathleen A McGinnis; Melissa Skanderson; Joseph Conigliaro; Shawn L Fultz; Kristina Crothers; Linda Rabeneck; Maria Rodriguez-Barradas; Sharon B Weissman; Kendall Bryant
Journal:  Med Care       Date:  2006-08       Impact factor: 2.983

8.  Inaccuracy of haemoglobin A1c among HIV-infected men: effects of CD4 cell count, antiretroviral therapies and haematological parameters.

Authors:  Laurence Slama; Frank J Palella; Alison G Abraham; Xiuhong Li; Corinne Vigouroux; Gilles Pialoux; Lawrence Kingsley; Jordan E Lake; Todd T Brown
Journal:  J Antimicrob Chemother       Date:  2014-08-04       Impact factor: 5.790

9.  Comparison of two VA laboratory data repositories indicates that missing data vary despite originating from the same source.

Authors:  Kathleen A McGinnis; Melissa Skanderson; Forrest L Levin; Cynthia Brandt; Joseph Erdos; Amy C Justice
Journal:  Med Care       Date:  2009-01       Impact factor: 2.983

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

Authors:  Susan E Spratt; Katherine Pereira; Bradi B Granger; Bryan C Batch; Matthew Phelan; Michael Pencina; Marie Lynn Miranda; Ebony Boulware; Joseph E Lucas; Charlotte L Nelson; Benjamin Neely; Benjamin A Goldstein; Pamela Barth; Rachel L Richesson; Isaretta L Riley; Leonor Corsino; Eugenia R McPeek Hinz; Shelley Rusincovitch; Jennifer Green; Anna Beth Barton; Carly Kelley; Kristen Hyland; Monica Tang; Amanda Elliott; Ewa Ruel; Alexander Clark; Melanie Mabrey; Kay Lyn Morrissey; Jyothi Rao; Beatrice Hong; Marjorie Pierre-Louis; Katherine Kelly; Nicole Jelesoff
Journal:  J Am Med Inform Assoc       Date:  2017-04-01       Impact factor: 4.497

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  1 in total

1.  Circulating CD4+ TEMRA and CD4+ CD28- T cells and incident diabetes among persons with and without HIV.

Authors:  Samuel S Bailin; Suman Kundu; Melissa Wellons; Matthew S Freiberg; Margaret F Doyle; Russell P Tracy; Amy C Justice; Celestine N Wanjalla; Alan L Landay; Kaku So-Armah; Simon Mallal; Jonathan A Kropski; John R Koethe
Journal:  AIDS       Date:  2022-03-15       Impact factor: 4.177

  1 in total

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