Validation of forearm fracture diagnoses in administrative patient registers

SUMMARY: The validity of forearm fracture diagnoses recorded in five Norwegian hospitals was investigated using image reports and medical records as gold standard. A relatively high completeness and correctness of the diagnoses was found. Algorithms used to define forearm fractures in administrative data should depend on study purpose. PURPOSE: In Norway, forearm fractures are routinely recorded in the Norwegian Patient Registry (NPR). However, these data have not been validated. Data from patient administrative systems (PAS) at hospitals are sent unabridged to NPR. By using data from PAS, we aimed to examine (1) the validity of the forearm fracture diagnoses and (2) the usefulness of washout periods, follow-up codes, and procedure codes to define incident forearm fracture cases. METHODS: This hospital-based validation study included women and men aged ≥ 19 years referred to five hospitals for treatment of a forearm fracture during selected periods in 2015. Administrative data for the ICD-10 forearm fracture code S52 (with all subgroups) in PAS and the medical records were reviewed. X-ray and computed tomography (CT) reports from examinations of forearms were reviewed independently and linked to the data from PAS. Sensitivity and positive predictive values (PPVs) were calculated using image reports and/or review of medical records as gold standard. RESULTS: Among the 8482 reviewed image reports and medical records, 624 patients were identified with an incident forearm fracture during the study period. The sensitivity of PAS registrations was 90.4% (95% CI: 87.8–92.6). The PPV increased from 73.9% (95% CI: 70.6–77.0) in crude data to 90.5% (95% CI: 88.0–92.7) when using a washout period of 6 months. Using procedure codes and follow-up codes in addition to 6-months washout increased the PPV to 94.0%, but the sensitivity fell to 69.0%. CONCLUSION: A relatively high sensitivity of forearm fracture diagnoses was found in PAS. PPV varied depending on the algorithms used to define cases. Choice of algorithm should therefore depend on study purposes. The results give useful measures of forearm fracture diagnoses from administrative patient registers. Depending on local coding practices and treatment pathways, we infer that the findings are relevant to other fracture diagnoses and registers.