Identifying Persons with Diabetes Using Medicare Claims Data
Abstract
The objective of this study was to develop and validate a method for identifying Medicare beneficiaries with diabetes by using Medicare claims data. We used self-reports of diabetes status from participants in the Medicare Current Beneficiary Survey to determine disease status, and then we examined these participants' Medicare claims. Using self-reported diabetes status as the "gold standard," we determined the sensitivity, specificity, and reliability of claims data in identifying beneficiaries with diabetes. We found that to construct a method that is adequately sensitive (> or = 70%), highly specific (> or = 97.5%), and reliable (kappa > or = 0.80), researchers must combine information from different types of Medicare claims files, use 2 years of data to identify cases, and require at least 2 diagnoses of diabetes among claims involving ambulatory care. Since these criteria are met by more than one method, the choice of method should be governed by the goals of the research as well as more practical concerns.
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There is no evidence showing cardiovascular and kidney benefits of older glucose-lowering medications like sulfonylureas in patients with type 2 diabetes and CKD.
“there is no evidence showing cardiovascular and kidney benefits of older glucose-lowering medications like sulfonylureas in this population; however, second-generation sulfonylureas (glyburide, glipizide, and glimepiride) are widely used.17”
From Disparities in SGLT2 Inhibitor or Glucagon-Like Peptide 1 Receptor Agonist Initiation Among Medicare-Insured Adults With CKD in the United States (2023) · cites this paper as [17]
Prescription of SGLT2i and GLP-1RA is low in both type 2 diabetes and patients with CKD.
“prescription of these newer glucose-lowering medications is low in both type 2 diabetes and patients with CKD.17,18”
From Disparities in SGLT2 Inhibitor or Glucagon-Like Peptide 1 Receptor Agonist Initiation Among Medicare-Insured Adults With CKD in the United States (2023) · cites this paper as [17]
Second-generation sulfonylureas are widely used.
“there is no evidence showing cardiovascular and kidney benefits of older glucose-lowering medications like sulfonylureas in this population; however, second-generation sulfonylureas (glyburide, glipizide, and glimepiride) are widely used.17”
From Disparities in SGLT2 Inhibitor or Glucagon-Like Peptide 1 Receptor Agonist Initiation Among Medicare-Insured Adults With CKD in the United States (2023) · cites this paper as [17]
The method of identifying CKD and type 2 diabetes using ≥1 inpatient or ≥2 outpatient claims increases sensitivity and specificity relative to using only 1 claim.
“This method has been shown to increase sensitivity and specificity relative to when only 1 claim is used.20”
From Disparities in SGLT2 Inhibitor or Glucagon-Like Peptide 1 Receptor Agonist Initiation Among Medicare-Insured Adults With CKD in the United States (2023) · cites this paper as [20]
The study used ≥1 inpatient claim or ≥2 physician/outpatient claims to increase sensitivity and specificity.
“We used ≥1 inpatient claim or ≥2 physician/outpatient claims to increase sensitivity and specificity.20”
From Disparities in SGLT2 Inhibitor or Glucagon-Like Peptide 1 Receptor Agonist Initiation Among Medicare-Insured Adults With CKD in the United States (2023) · cites this paper as [20]
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References 25 · Cited by 403
- Authors
- Hebert, P. L., Geiss, L. S., Tierney, E. F., Engelgau, M. M., Yawn, B. P., & McBean, A. M.
- Affiliations
- University of Minnesota (US)
- Centers for Disease Control and Prevention (US)
- Venue
- American Journal of Medical Quality
- Published
- 1999-11
- Volume
- 14
- Issue
- 6
- Pages
- 270-277
- ISSN
- 1062-8606 (ISSN-L)
- 1555-824X
- OpenAlex
- W2050503581
- Cited by
- 403
- References
- 25
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 6 · 2023: 8 · 2022: 16 · 2021: 9 · 2020: 14 · 2019: 14 · 2018: 15 · 2017: 11 · 2016: 23 · 2015: 26 · 2014: 24 · 2013: 26 · 2012: 20
- FWCI
- 12.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Medical Quality (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Public Health Service (S234-15/16)
- Topics
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
- Keywords
- diabetes mellitus, Medicare claims data, disease identification, Medicare Current Beneficiary Survey, diagnostic accuracy, sensitivity and specificity
- MeSH terms
- Aged, Algorithms, Diabetes Mellitus, Female, Medicare, Health Surveys, Humans, Insurance Claim Reporting, Longitudinal Studies, Male, Middle Aged, Sensitivity and Specificity, United States, Reproducibility of Results, Prevalence
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.
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