Table 3.
Four strategies can be employed for identifying PE patients in administrative data. Strategy (A) uses ICD-10 codes to identify PE patients and employs no verification methods. The assumed validity represents how statistical values would appear to an investigator who used our database and assumed correctness of ICD-10 codes. The actual validity demonstrates the true statistical analysis of our database, reflecting the coding errors that we identified. The investigator using a strategy lacking ICD-10 code verification would unknowingly miss false positives and negatives in our database. Strategy (B) uses ICD-10 codes, with the additional step of identifying the false negative population and moving them to the PE-positive population. The assumed validity represents the statistical values when the investigator assumes that the strategy has captured all PEs in the data, and that all patients were correctly assigned a PE ICD-10 code. The actual validity demonstrates the true statistical values of the same strategy; an investigator would unknowingly miss false positives in the data set. Strategy (C) uses ICD-10 codes, with the additional step of identifying the false positive PE patients and moving them to the PE-negative group. The assumed validity represents the statistical values when the investigator assumes that the strategy has removed all patients that were incorrectly assigned a PE diagnostic code; in this case they assume that there are no PE patients who were missed because they are not assigned a PE diagnostic code. The actual validity demonstrates the true statistical values of the same strategy; an investigator assuming all patients diagnosed with PE were assigned the appropriate ICD-10 code for PE would unknowingly miss false negatives in the data set. Strategy (D) uses ICD-10 codes to identify PE patients, and takes the further steps to identify the false positive and negative populations, moving them to the PE-negative and PE-positive populations, respectively; this strategy ensures that all patients’ true diagnoses are known
SN sensitivity, SP specificity, PPV positive predictive value, NPV negative predictive value