Purpose — To validate three approaches for identifying incident cases of pancreatic cancer in Ontario administrative claims data.
Methods — We created a cohort using Ontario (Canada) administrative health data from 2002 to 2012 and identified cases of pancreatic cancer with three approaches, using the Ontario Cancer Registry (OCR) as the reference standard. In the any diagnosis approach, cases were defined by primary or secondary diagnostic codes for pancreatic cancer in outpatient or inpatient records. In the any inpatient diagnosis approach, cases were defined using only diagnoses in hospital discharge abstracts. In the algorithm approach, cases were identified by an algorithm that combined the first two approaches. Comparing each approach to the OCR, we calculated the expected value and 95% confidence interval (CI) of the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We also compared the event dates using each approach with those recorded in the OCR.
Results — Among a total of 12 060 837 patients in Ontario administrative health data sources, 13 999 incident pancreatic cancer cases were identified in the OCR. Sensitivity ranged from 72.5% (algorithm) to 97.5% (any diagnosis), and PPV ranged from 38.4% (any diagnosis) to 78.9% (any inpatient diagnosis). Specificity and NPV were ~100% for all approaches. The median absolute difference in cancer event date ranged 0 to 15 days. The any inpatient diagnosis method had the highest PPV (78.9%; 95% CI: 78.2‐79.5%) and moderate sensitivity (86.6%; 95% CI: 86.0‐87.2%).
Conclusion — Inpatient diagnoses of pancreatic cancer in Ontario administrative heath data are suitable for pancreatic cancer case identification.