The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Who Has Diabetes? Best Estimates of Diabetes Prevalence in the Department of Veterans Affairs Based on Computerized Patient Data
Open accessAbstract
OBJECTIVE—To optimize methods for identifying patients with diabetes based on computerized records and to obtain best estimates of diabetes prevalence in Department of Veterans Affairs (VA) patients. RESEARCH DESIGN AND METHODS—The VA Diabetes Epidemiology Cohort (DEpiC) is a linked national database of all VA patients since 1998 with data from VA medical visits, Medicare claims, pharmacy and laboratory records, and patient surveys. Using DEpiC, we examined concordance of diabetes indicators, including ICD-9-CM codes (250.xx), prescription drug treatment, HbA1c tests, and patient self-report. We determined the optimal criterion for identifying diabetes and used it in estimating diabetes prevalence in the VA. RESULTS—The best criterion was a prescription for a diabetes medication in the current year and/or 2+ diabetes codes from inpatient and/or outpatient visits (VA and Medicare) over a 24-month period. This definition had high sensitivity (93%) and specificity (98%) against patient self-report, and reasonable rates of HbA1c testing (75%). HbA1c testing alone added few additional cases, and a single diagnostic code added many patients, but without confirmation (reduced specificity). However, including codes from Medicare was critical. Applying this definition for 1998–2000, we identified an average of 500,000 VA patients with diabetes per year. We also estimated high and increasing diabetes prevalence rates of 16.7% in FY1998, 18.6% in FY1999, and 19.6% in FY2000 and an incidence estimated to be ∼2% per year. CONCLUSIONS—Development and evaluation of methodology for analyzing computerized patient data can improve the identification of patients with diabetes. The increasing high prevalence of diabetes in VA patients will present challenges for clinicians and health system management.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus
The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus* (2002) · Diabetes Care · doi:10.2337/diacare.25.2007.s5 · Cited by 10,338
Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus
The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus (1997) · Diabetes Care · doi:10.2337/diacare.20.7.1183 · Cited by 6,220
The Continuing Epidemics of Obesity and Diabetes in the United States
Mokdad, A. H. (2001) · JAMA · doi:10.1001/jama.286.10.1195 · Cited by 2,730
Harris, M. I., Flegal, K. M., Cowie, C. C., Eberhardt, M. S., Goldstein, D. E., Little, R. R., Wiedmeyer, H.-M., & Byrd-Holt, D. D. (1998) · Diabetes Care · doi:10.2337/diacare.21.4.518 · Cited by 2,703
Stewart, A. L. (1989) · JAMA · doi:10.1001/jama.262.7.907 · Cited by 2,085
International Classification of Diseases, 10th Revision
(2018) · The SAGE Encyclopedia of Intellectual and Developmental Disorders · doi:10.4135/9781483392271.n276 · Cited by 1,917
Hux, J. E., Ivis, F., Flintoft, V., & Bica, A. (2002) · Diabetes Care · doi:10.2337/diacare.25.3.512 · Cited by 1,290
Risk Adjustment for Measuring Healthcare Outcomes
Iezzoni, L. I. (1994) · Cited by 955
The accuracy of Medicare's hospital claims data: progress has been made, but problems remain.
Fisher, E. S., Whaley, F. S., Krushat, W. M., Malenka, D. J., Fleming, C., Baron, J. A., & Hsia, D. C. (1992) · American Journal of Public Health · doi:10.2105/ajph.82.2.243 · Cited by 709
Economic Consequences of Diabetes Mellitus in the U.S. in 1997
American Diabetes Association (1998) · Diabetes Care · doi:10.2337/diacare.21.2.296 · Cited by 652
Cited by
Economic Costs of Diabetes in the U.S. in 2022
(2023) · doi:10.2337/dci23-0085 · Cited by 808
Mazzaglia, G., Ambrosioni, E., Alacqua, M., Filippi, A., Sessa, E., Immordino, V., Borghi, C., Brignoli, O., Caputi, A. P., Cricelli, C., et al. (2009) · Circulation · doi:10.1161/circulationaha.108.830299 · Cited by 637
Acute Kidney Injury Associates with Increased Long-Term Mortality
Lafrance, J.-P., & Miller, D. R. (2010) · Journal of the American Society of Nephrology · doi:10.1681/asn.2009060636 · Cited by 616
Self-citationHyperglycemia-related mortality in critically ill patients varies with admission diagnosis
Falciglia, M., Freyberg, R. W., Almenoff, P. L., D’Alessio, D. A., & Render, M. L. (2009) · Critical Care Medicine · doi:10.1097/ccm.0b013e3181b083f7 · Cited by 576
Protective effects of NSAIDs on the development of Alzheimer disease
Vlad, S. C., Miller, D. R., Kowall, N. W., & Felson, D. T. (2008) · Neurology · doi:10.1212/01.wnl.0000311269.57716.63 · Cited by 535
Self-citation
Metadata
- Authors
- Miller, D. R., Safford, M. M., & Pogach, L. M.
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2004-05-01
- Volume
- 27
- Issue
- suppl_2
- Pages
- b10-b21
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- OpenAlex
- W2033136851
- Cited by
- 425
- References
- 35
- FWCI
- 45.98
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Who Has Diabetes? Best Estimates of Diabetes Prevalence in the Department of Veterans Affairs Based on Computerized Patient Data. https://app.cochat.ai/papers/10.2337/diacare.27.suppl_2.b10
- The paper
- Miller, D. R., Safford, M. M., & Pogach, L. M. (2004). Who Has Diabetes? Best Estimates of Diabetes Prevalence in the Department of Veterans Affairs Based on Computerized Patient Data. Diabetes Care. https://doi.org/10.2337/diacare.27.suppl_2.b10
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.