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Med Care. 2018 Jun;56(6):e32-e38. doi: 10.1097/MLR.0000000000000777.

Validity of Administrative Data in Identifying Cancer-related Events in Adolescents and Young Adults: A Population-based Study Using the IMPACT Cohort.

Gupta S1,2,3,4, Nathan PC1,2,3,4, Baxter NN3,4,5, Lau C3, Daly C6, Pole JD3,7.

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Division of Haematology/Oncology, The Hospital for Sick Children.
Faculty of Medicine, University of Toronto.
Cancer Research Program, Institute for Clinical Evaluative Sciences.
Institute for Health Policy, Evaluation and Management, University of Toronto.
Department of General Surgery, Li Ka Shing Knowledge Institute St. Michael's Hospital.
Canadian Partnership Against Cancer.
Pediatric Oncology Group of Ontario, Toronto, ON, Canada.



Despite the importance of estimating population level cancer outcomes, most registries do not collect critical events such as relapse. Attempts to use health administrative data to identify these events have focused on older adults and have been mostly unsuccessful. We developed and tested administrative data-based algorithms in a population-based cohort of adolescents and young adults with cancer.


We identified all Ontario adolescents and young adults 15-21 years old diagnosed with leukemia, lymphoma, sarcoma, or testicular cancer between 1992-2012. Chart abstraction determined the end of initial treatment (EOIT) date and subsequent cancer-related events (progression, relapse, second cancer). Linkage to population-based administrative databases identified fee and procedure codes indicating cancer treatment or palliative care. Algorithms determining EOIT based on a time interval free of treatment-associated codes, and new cancer-related events based on billing codes, were compared with chart-abstracted data.


The cohort comprised 1404 patients. Time periods free of treatment-associated codes did not validly identify EOIT dates; using subsequent codes to identify new cancer events was thus associated with low sensitivity (56.2%). However, using administrative data codes that occurred after the EOIT date based on chart abstraction, the first cancer-related event was identified with excellent validity (sensitivity, 87.0%; specificity, 93.3%; positive predictive value, 81.5%; negative predictive value, 95.5%).


Although administrative data alone did not validly identify cancer-related events, administrative data in combination with chart collected EOIT dates was associated with excellent validity. The collection of EOIT dates by cancer registries would significantly expand the potential of administrative data linkage to assess cancer outcomes.

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