Prevalence of lung cancer in Colombia and a new diagnostic algorithm using health administrative databases: A real-world evidence study.

Abstract

e18764 Background: Reliable, timely and detailed information of lung cancer mortality and costs from low- and middle-income countries is essential to policy design. We aimed to develop an electronic algorithm to identify lung cancer prevalent patient in Colombia using official databases and to estimate prevalence rates by age, sex, and geographic region. Methods: We performed a cross sectional study based on national claim databases in Colombia ( Base de datos de suficiencia de la Unidad de Pago por Capitación and Base de Datos Única de Afiliados) to identify lung cancer prevalent patients in 2017. Several algorithms based on the presence or absence of oncological procedures (Chemotherapy, radiotherapy and surgery), and a minimum number of months that each individual had lung cancer ICD-10 codes in the previous 3 years, were developed. After testing 16 algorithms, those with the closest prevalence rates to the ones reported by aggregated official sources (GLOBOCAN, National Cancer Institute and Cuenta de Alto Costo) were selected . We estimated prevalence rates by age, sex, and geographic region. Results: Two algorithm s were selected: i) it was defined as the presence of ICD-10 codes for 4 months or more (sensitive algorithm); and ii) adding the presence of at least one oncological procedure (specific algorithm). Estimated prevalence rates per 100,000 population were 15.3 and 9.7 for the sensitive and specific algorithms, respectively. These rates were higher in men (9.9), over 65 years old (37.1), who lived in Central and Bogota regions (14.7 and 10.9, respectively) (Table). Conclusions: Selected algorithms showed similar prevalence estimations to those reported by official sources and allowed us to estimate prevalence rates in specific aging, regional and gender groups for Colombia using national claims databases. These findings could be useful to identify clinical and economical outcomes related to lung cancer patients using national individual-level databases. [Table: see text]