Development and Validation of Case‐Finding Algorithms to Identify Periprosthetic Joint Infections After Total Hip Arthroplasty in Veterans Health Administration Data

PURPOSE: To determine the positive predictive values (PPVs) of ICD-9- and ICD-10-based diagnostic coding algorithms to identify periprosthetic joint infection (PJI) following total hip arthroplasty (THA) within the United States (US) Veterans Health Administration (VHA). METHODS: We selected patients with: (1) any position hospital discharge ICD-9 or ICD-10 diagnosis of PJI, (2) ICD-9, ICD-10, or current procedural terminology (CPT) procedure codes for THA any time prior to PJI diagnosis, (3) CPT code for hip X-ray within ±90 days of the PJI diagnosis, and (4) 1 or more CPT codes for arthrocentesis, arthrotomy, or revision arthroplasty all occurring within ±90 days of the PJI diagnosis date. We obtained separate samples of patients for ICD-9 and ICD-10-based PJI diagnoses. These samples were stratified by THA medical center volume. Infectious disease physicians adjudicated each identified PJI event. The PPV (95% confidence interval [CI]) for the ICD-9 and ICD-10 PJI algorithms were calculated. RESULTS: Among the 90 sampled hip PJI events for the ICD-9 era, 79 were confirmed PJIs (PPV 87.8%, 95% CI 79.2%-93.7%). For the 90 sampled hip PJI events for the ICD-10 era, 72 were confirmed PJIs (PPV 80.0%, 95% CI 70.3%-87.7%). CONCLUSION: These algorithms yielded a PPV of 87.8% (ICD-9) and 80.0% (ICD-10), for confirmed PJI events and could be considered for use in future pharmacoepidemiologic studies.