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Table 5 Model fit statistics for the PSSA method in the numeric example

From: Combining population-based administrative health records and electronic medical records for disease surveillance

Model

Overall

Males

Females

18–44 years

45–64 years

65+ years

1

167,249

73,418

93,565

42,925

71,311

26,719

2

166,994

73,405

93,493

42,921

70,983

26,554

3

166,506

73,181

93,351

42,421

71,033

26,622

4

165,719

72,706

92,688

42,220

70,483

26,525

  1. PSSA Probabilistic-based sensitivity-specificity adjusted method, PSSA, model 1 covariates are sex, age group, region, income quintile, Charlson comorbidity score, chronic obstructive pulmonary disease (A, E), diabetes (A, E), depression (A, E), dementia (A, E), obesity (A, E), cerebrovascular disease (A), congestive heart failure (A), coronary heart disease (A), renal disease (A), substance abuse (A); PSSA, model 2 covariates sex, age group, region, income quintile, chronic obstructive pulmonary disease (E), diabetes (E), depression (E), dementia (E), obesity (E), cerebrovascular disease (A), congestive heart failure (A), coronary heart disease (A), renal disease (A), substance abuse (A); PSSA, model 3 covariates are sex, age group, region, income quintile, chronic obstructive pulmonary disease (E), diabetes (E), depression (E), dementia (E), obesity (E), coronary heart disease (A), renal disease (A), substance abuse (A); PSSA, model 4 covariates are sex, age group, chronic obstructive pulmonary disease (E), diabetes (E), obesity (E), coronary heart disease (A), congestive heart failure (A), substance abuse (A); A and E denote disease-specific markers that were identified from AHRs and EMRs, respectively; Values in bold-face font represent the best-fitting model