Novel Use and Utility of Integrated Electronic Health Records to Assess Rates of Prediabetes Recognition and Treatment: Brief Report From an Integrated Electronic Health Records Pilot Study
Open accessAbstract
OBJECTIVE: This study uses novel methods to examine the frequency of diagnosis and treatment of prediabetes in real-world clinical settings using electronic health record (EHR) data. RESEARCH DESIGN AND METHODS: We identified a cohort of 358,120 adults with incident prediabetes (fasting plasma glucose [FPG] 100–125 mg/dL or glycated hemoglobin 5.7–6.4% [39–46 mmol/mol]) between 2006 and 2010 and examined rates of diagnosis and treatment in the 6 months after identification. RESULTS: In the 6 months after identification of prediabetes, 18% of patients had their blood glucose levels retested; 13% received a physician diagnosis of prediabetes/hyperglycemia; 31.0% had prediabetes, diabetes, or lifestyle documented in the clinical notes; and <0.1% initiated metformin. Among patients with FPG 120–125 mg/dL, 31% were retested; metformin initiation remained <1%. CONCLUSIONS: Documented rates of follow-up and treatment for prediabetes are low. EHR data may be a valuable tool to improve identification and treatment of prediabetes in the U.S.
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This practice of low metformin prescribing has changed very little in real-world settings up to 2018.
“Our study shows this practice has changed very little in realworld settings up to 2018. 12,16”
From Metformin Prescription Rates for Patients with Prediabetes (2022) · cites this paper as [12]
The Results report that fewer than 1% of patients initiated metformin, supporting the earlier low-prescribing rate used for comparison. The Methods place the cohort in 2006–2010; this paper does not establish that prescribing changed very little through 2018. (LLM, conf=0.88)
Experimental — accuracy not yet measuredPrevious studies examining metformin prescriptions have also found low prescribing rates.
“Previous studies examining metformin prescriptions have also found low prescribing rates.”
From Metformin Prescription Rates for Patients with Prediabetes (2022) · cites this paper as [12]
Diabetes incidence can be reduced through effective preventive interventions, such as participation in intensive lifestyle change programs or pharmacotherapy such as metformin.
“Studies have shown diabetes incidence can be reduced through effective preventive interventions, such as participation in intensive lifestyle change programs (LCP) like the National Diabetes Prevention Program (National DPP) lifestyle change program, or with pharmacotherapy such as metformin. 7 -12”
From Metformin Prescription Rates for Patients with Prediabetes (2022) · cites this paper as [12]
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Cites
Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin
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The Finnish Diabetes Prevention Study (DPS)
Lindström, J., Louheranta, A., Mannelin, M., Rastas, M., Salminen, V., Eriksson, J., Uusitupa, M., Tuomilehto, J., & for the Finnish Diabetes Prevention Study Group (2003) · Diabetes Care · doi:10.2337/diacare.26.12.3230 · Cited by 1,848 · see citing works
Schmittdiel, J. A., Uratsu, C. S., Karter, A. J., Heisler, M., Subramanian, U., Mangione, C. M., & Selby, J. V. (2008) · Journal of General Internal Medicine · doi:10.1007/s11606-008-0554-8 · Cited by 239 · see citing works
Self-citationTranslating the Diabetes Prevention Program Into an Urban Medically Underserved Community
Seidel, M. C., Powell, R. O., Zgibor, J. C., Siminerio, L. M., & Piatt, G. A. (2008) · Diabetes Care · doi:10.2337/dc07-1869 · Cited by 164 · see citing works
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Research works printed but not linked: 10
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Cited by
Sorted by citations
Metformin Use in Prediabetes Among U.S. Adults, 2005–2012
Tseng, E., Yeh, H.-C., & Maruthur, N. M. (2017) · Diabetes Care · doi:10.2337/dc16-1509 · Cited by 72 · see citing works
Primary Care Providers’ Prediabetes Screening, Testing, and Referral Behaviors
Nhim, K., Khan, T., Gruss, S. M., Wozniak, G., Kirley, K., Schumacher, P., Luman, E. T., & Albright, A. (2018) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2018.04.017 · Cited by 54 · see citing works
Metformin Prescription Rates for Patients with Prediabetes
Hughes, A., Khan, T., Kirley, K., Moin, T., Mainous, A., Sachdev, N., Williams, J., & Wozniak, G. (2022) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2022.04.210485 · Cited by 15 · see citing works
“12,16 Since the annual progression rate from prediabetes to type 2 diabetes can be as high as 11% in certain populations, these delays represent missed opportunities to delay or prevent progression to type 2 diabetes among adults who are at higher risk.”
Background
- Authors
- Schmittdiel, J. A., Adams, S. R., Segal, J., Griffin, M. R., Roumie, C. L., Ohnsorg, K., Grant, R. W., & O’Connor, P. J.
- Affiliations
- Kaiser Permanente (US)
- Johns Hopkins University (US)
- Vanderbilt University (US)
- HealthPartners (US)
- Corresponding author
- Schmittdiel, Julie A.
- ORCID
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2014-01-11
- Volume
- 37
- Issue
- 2
- Pages
- 565-568
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- PMC
- PMC3898765
- OpenAlex
- W2047761929
- Cited by
- 68
- References
- 5
- Citations by year
- 2025: 3 · 2024: 6 · 2023: 3 · 2022: 8 · 2021: 9 · 2020: 6 · 2019: 8 · 2018: 6 · 2017: 6 · 2016: 8 · 2015: 4 · 2013: 1
- FWCI
- 7.48
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Diabetes Care (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK092986, P30DK092924)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Keywords
- prediabetes, prediabetes diagnosis, fasting blood glucose, HbA1c, follow-up testing, electronic health records, clinical notes, diabetes prevention
- MeSH terms
- Adult, Aged, Blood Glucose, Female, Glycated Hemoglobin, Humans, Male, Middle Aged, Pilot Projects, Prediabetic State, Electronic Health Records
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