Journal of Epidemiology (Apr 2023)

Validation Study of Diabetes Definitions Using Japanese Diagnosis Procedure Combination Data Among Hospitalized Patients

  • Rieko Kanehara,
  • Atsushi Goto,
  • Maki Goto,
  • Toshiaki Takahashi,
  • Motoki Iwasaki,
  • Mitsuhiko Noda,
  • Hikaru Ihira,
  • Shoichiro Tsugane,
  • Norie Sawada

DOI
https://doi.org/10.2188/jea.JE20210024
Journal volume & issue
Vol. 33, no. 4
pp. 165 – 169

Abstract

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Background: Validation studies of diabetes definitions using nationwide healthcare databases are scarce. We evaluated the validity of diabetes definitions using disease codes and antidiabetic drug prescriptions in the Japanese Diagnosis Procedure Combination (DPC) data via medical chart review. Methods: We randomly selected 500 records among 15,334 patients who participated in the Japan Public Health Center-Based Prospective Study for the Next Generation in Yokote City and who had visited a general hospital in Akita between October 2011 and August 2018. Of the 500 patients, 98 were linked to DPC data; however, only 72 had sufficient information in the medical chart. Gold standard confirmation was performed by board-certified diabetologists. DPC-based diabetes definitions were based on the International Classification of Diseases, 10th Revision codes and antidiabetic prescriptions. Sensitivity, specificity, and the positive and negative predictive values (PPV and NPV, respectively) of DPC-based diabetes definitions were evaluated. Results: Of 72 patients, 23 were diagnosed with diabetes using chart review; 19 had a diabetes code, and 13 had both a diabetes code and antidiabetic prescriptions. The sensitivity, specificity, PPV, and NPV were 89.5% (95% confidence interval [CI], 66.9–98.7%), 96.2% (95% CI, 87.0–99.5%), 89.5% (95% CI, 66.9–98.7%), and 96.2% (95% CI, 87.0–99.5%), respectively, for (i) diabetes codes alone; 89.5% (95% CI, 66.9–98.7%), 94.3% (95% CI, 84.3–98.8%), 85.0% (95% CI, 62.1–96.8%), and 96.2% (95% CI, 86.8–99.5%) for (ii) diabetes codes and/or prescriptions; 68.4% (95% CI, 43.4–87.4%), 100% (95% CI, 93.3–100%), 100% (95% CI, 75.3–100%), and 89.8% (95% CI, 79.2–96.2%) for (iii) both diabetes codes and prescriptions. Conclusion: Our results suggest that DPC data can accurately identify diabetes among inpatients using (i) diabetes codes alone or (ii) diabetes codes and/or prescriptions.

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