Développement d’un algorithme pour la surveillance de l’incidence du cancer colorectal à Montréal avec les banques données médico-administratives de la RAMQ
Background: Cancer case ascertainment methods used in Quebec and elsewhere are known to underestimate the burden of cancer, particularly for certain subgroups. Algorithms using claims data are a low-cost option to improve the quality of cancer surveillance but have not been implemented at the population-level. Objectives: Our objectives were to 1) develop a colorectal cancer (CRC) case ascertainment algorithm using population-level hospitalization and physician billing data, 2) validate the algorithm, and 3) describe the characteristics of newly-captured cases. Methods: We linked physician billing, hospitalization, and tumour registry data for 2,013,430 Montreal residents aged 20 + (2000–2010). We compared the performance of three algorithms based on diagnostic codes and different data sources. We validated cases using receipt of treatment, site distribution, and time trends. We described identified cases according to age, sex, socioeconomic status, and treatment patterns. Results: Our algorithm based on diagnosis and treatment codes identified 11,476 of the 12,933 incident CRC cases contained in the tumour registry as well as 2,317 newly-captured cases. Our cases share similar overall time trends and site distributions to existing data, which increases our confidence in the algorithm. Our algorithm captured, proportionally more individuals aged 50 and younger among newly captured CRC cases: 8.2% vs. 5.3%. Additionally, newly captured cases were more likely to live in socioeconomically advantaged areas. Conclusions: Our algorithm provides a more complete picture of population-wide CRC incidence than existing case ascertainment methods. It could be used to estimate long-term incidence trends, aid in timely surveillance, and to inform interventions, in both Quebec and other jurisdictions.
Incidence Données médico-administratives Colorectal cancer Algorithm Administrative health data Cancer registry data