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. 2021 Aug 24;13(2):249–255. doi: 10.1111/jdi.13641

Table 3.

Accuracy of administrative data algorithms to identify patients with diabetes

Algorithm TP TN FN FP Sensitivity (%) 95% CI Specificity (%) 95% CI PPV (%) 95% CI NPV (%) 95% CI Prevalence estimate Kappa Youden
Algorithm 1 151,751 2,127,217 13,764 706,420 91.7% 91.6% 91.8% 75.1% 75.0% 75.1% 17.7% 17.6% 17.8% 99.4% 99.3% 99.4% 0.29 0.22 0.67
Algorithm 2 123,777 2,812,361 41,738 21,276 74.8% 74.6% 75.0% 99.2% 99.2% 99.3% 85.3% 85.2% 85.5% 98.5% 98.5% 98.6% 0.05 0.79 0.74
Algorithm 3 123,695 2,813,530 41,820 20,107 74.7% 74.5% 74.9% 99.3% 99.3% 99.3% 86.0% 85.8% 86.2% 98.5% 98.5% 98.5% 0.05 0.79 0.74
Algorithm 4 123,485 2,816,705 42,030 16,932 74.6% 74.4% 74.8% 99.4% 99.4% 99.4% 87.9% 87.8% 88.1% 98.5% 98.5% 98.5% 0.05 0.80 0.74
Algorithm 5 151,751 2,127,217 13,764 706,420 91.7% 91.6% 91.8% 75.1% 75.0% 75.1% 17.7% 17.6% 17.8% 99.4% 99.3% 99.4% 0.29 0.22 0.67
Algorithm 6 123,695 2,813,530 41,820 20,107 74.7% 74.5% 74.9% 99.3% 99.3% 99.3% 86.0% 85.8% 86.2% 98.5% 98.5% 98.5% 0.05 0.79 0.74
Algorithm 7 145,617 2,595,431 19,898 238,206 88.0% 87.8% 88.1% 91.6% 91.6% 91.6% 37.9% 37.8% 38.1% 99.2% 99.2% 99.2% 0.13 0.49 0.80
Algorithm 8 123,612 2,815,897 41,903 17,740 74.7% 74.5% 74.9% 99.4% 99.4% 99.4% 87.4% 87.3% 87.6% 98.5% 98.5% 98.5% 0.05 0.80 0.74
Algorithm 9 123,415 2,817,411 42,100 16,226 74.6% 74.4% 74.8% 99.4% 99.4% 99.4% 88.4% 88.2% 88.5% 98.5% 98.5% 98.5% 0.05 0.80 0.74
Algorithm 10 145,617 2,595,431 19,898 238,206 88.0% 87.8% 88.1% 91.6% 91.6% 91.6% 37.9% 37.8% 38.1% 99.2% 99.2% 99.2% 0.13 0.49 0.80
Algorithm 11 123,612 2,815,897 41,903 17,740 74.7% 74.5% 74.9% 99.4% 99.4% 99.4% 87.4% 87.3% 87.6% 98.5% 98.5% 98.5% 0.05 0.80 0.74
Algorithm 12 123,415 2,817,411 42,100 16,226 74.6% 74.4% 74.8% 99.4% 99.4% 99.4% 88.4% 88.2% 88.5% 98.5% 98.5% 98.5% 0.05 0.80 0.74
Algorithm 13 149,447 2,156,696 16,068 676,941 90.3% 90.1% 90.4% 76.1% 76.1% 76.2% 18.1% 18.0% 18.2% 99.3% 99.2% 99.3% 0.28 0.23 0.66
Algorithm 14 150,434 1,559,091 15,081 1,274,546 90.9% 90.7% 91.0% 55.0% 55.0% 55.1% 10.6% 10.5% 10.6% 99.0% 99.0% 99.1% 0.48 0.10 0.46
Algorithm 15 49,472 2,816,364 116,043 17,273 29.9% 29.7% 30.1% 99.4% 99.4% 99.4% 74.1% 73.8% 74.5% 96.0% 96.0% 96.1% 0.02 0.41 0.29
Algorithm 16 155,540 1,513,000 9,975 1,320,637 94.0% 93.9% 94.1% 53.4% 53.3% 53.5% 10.5% 10.5% 10.6% 99.3% 99.3% 99.4% 0.49 0.10 0.47
Algorithm 17 119,807 2,818,453 45,708 15,184 72.4% 72.2% 72.6% 99.5% 99.5% 99.5% 88.8% 88.6% 88.9% 98.4% 98.4% 98.4% 0.05 0.79 0.72

Reference standard: the specific health checkups in Japan (n = 165,515); total patients n = 2,999,152.

95% CI; 95% confidence interval; FN, false negative (the number of people for whom reported not having been prescribed diabetic medication, and recorded having been prescribed them); FP, false positive (the number of people for whom reported having been prescribed diabetic medication, and recorded not having been prescribed them); Kappa, Kappa Index; NPV, negative predictive value; PPV, positive predictive value, Prevalence estimate, prevalence of diabetes in the specific health checkups; TN, true negative (the number of people for whom reported not having been prescribed diabetic medication, and recorded not having been prescribed them); TP, true positive (the number of people for whom reported having been prescribed diabetic medication, and recorded having been prescribed them); Youden, Youden Index.