Validation of a claims-based algorithm identifying eligible study subjects in the ADAPTABLE pragmatic clinical trial

Abstract

Objective

Validate an algorithm that uses administrative claims data to identify eligible study subjects for the ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) pragmatic clinical trial (PCT).

Materials and methods

This study used medical records from a random sample of patients identified as eligible for the ADAPTABLE trial. The inclusion criteria for ADAPTABLE were a history of acute myocardial infarction (AMI) or percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG), or other coronary artery disease (CAD), plus at least one of several risk-enrichment factors. Exclusion criteria included a history of bleeding disorders or aspirin allergy. Using a claims-based algorithm, based on International Classification of Diseases, 9th Edition, Clinical Modification (ICD-9-CM) and 10th Edition (ICD-10) codes and Current Procedural Terminology (CPT) codes, we identified patients eligible for the PCT. The primary outcome was the positive predictive value (PPV) of the identification algorithm: the proportion of sampled patients whose medical records confirmed their ADAPTABLE study eligibility. Exact 95% confidence limits for binomial random variables were calculated for the PPV estimates.

Results

Of the 185 patients whose medical records were reviewed, 168 (90.8%; 95% Confidence Interval: 85.7%, 94.6%) were confirmed study eligible. This proportion did not differ between patients identified with codes for AMI and patients identified with codes for PCI or CABG.

Conclusion

The estimated PPV was similar to those in claims-based identification of drug safety surveillance events, indicating that administrative claims data can accurately identify study-eligible subjects for pragmatic clinical trials.