ArticleJournal of diabetes investigation2022
Appropriate definition of diabetes using an administrative database: A cross-sectional cohort validation study.
Article in Journal of diabetes investigation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed.
- Antihyperglycemic Drugs and Risk of Asthma Exacerbation in Patients With Asthma and Type 2 Diabetes: A Multinational Retrospective Cohort Study.Pharmacotherapy · 2026Observational
- Comparison of SGLT2 Inhibitors for New-Onset Proteinuria Risk in Patients With Type 2 Diabetes and Preserved Kidney Function.Diabetes, obesity & metabolism · 2026Article
- Comorbidities and Concomitant Medications in Middle-Aged Japanese People According to the Charlson Comorbidity Index and Age: Results of the NDB-K7Ps-Study-3.Epidemiologia (Basel, Switzerland) · 2026Article
- Non-steroidal anti-inflammatory drugs versus acetaminophen and risk of venous thromboembolism: An active comparator new user cohort study.Journal of internal medicine · 2026Article
- Frequency, patient characteristics, and clinical management for extravasation with docetaxel: a descriptive study using a large Japanese medical claims database.Journal of pharmaceutical health care and sciences · 2025Article
- Depression risk associated with spouses' diabetes and cardiovascular events: a nationwide cohort study.American journal of epidemiology · 2025Article
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- Disease burden of myasthenia gravis in relation to oral corticosteroid dose: an insurance claims database study in Japan.Frontiers in neurology · 2025Article
- Usefulness and caveats of real-world data for research on hypertension and its association with cardiovascular or renal disease in Japan.Hypertension research : official journal of the Japanese Society of Hypertension · 2024Review
- Depression Onset After a Spouse's Cardiovascular Event.JAMA network open · 2024Article
- Prevalence of Metabolic Syndrome in Patients with Type 2 Diabetes in Japan: A Retrospective Cross-Sectional Study.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2024Article
- Effect of the Diabetic Nephropathy Aggravation Prevention Program on medical visit behavior in individuals under the municipal national health insurance.Journal of diabetes investigation · 2023Article
- Strategies to Address Current Challenges in Real-World Evidence Generation in Japan.Drugs - real world outcomes · 2023Review
- Diabetes mellitus monitoring and control among adults in Australian general practice: a national retrospective cohort study.BMJ open · 2023Article
- Comparison of Operational Definition of Type 2 Diabetes Mellitus Based on Data from Korean National Health Insurance Service and Korea National Health and Nutrition Examination Survey.Diabetes & metabolism journal · 2023Article
- The age of death in Japanese patients with type 2 and type 1 diabetes: A descriptive epidemiological study.Journal of diabetes investigation · 2022Article
- Appropriate definition of diabetes using an administrative database: A cross-sectional cohort validation study.Journal of diabetes investigation · 2022Article
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9 authors.
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Abstract
AIMS/
introductionThe purpose of the present study was to quantify errors in the diagnosis of diabetes for use in the national database, using a sufficient population size. MATERIALS AND
methodsA claims database constructed by the JMDC (Tokyo, Japan), using standardized disease classifications and anonymous record linkage, was used in this validation study. We included patients with health insurance claims data from April 2005 to March 2019 in the JMDC claims database. We excluded patients without a record of specific health checkups in Japan. Sample size calculation was based on a 5% prevalence of diabetes and 0.4% absolute accuracy (i.e., 1,250,000 individuals), to calculate the sensitivity, specificity, positive predictive value and negative predictive value.
resultsIn total, 2,999,152 patients were included in this study, of which 165,515 were classified as having diabetes based on specific health checkups (validation cohort prevalence of 5.5%). The newly devised algorithm had three elements - the diagnosis-related codes for diabetes without suspected flag, the medication codes for diabetes and then these two codes on the same record - and yielded a sensitivity of 74.6%, positive predictive value of 88.4% and Kappa Index of 0.80 (the highest values).
conclusionsIn future claims database studies, our validated algorithms will be useful as diagnostic criteria for diabetes.
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