Abstract
e18784 Background: There is need for high quality data about the economic burden of disease in low- and middle-income countries. We aimed to determine the annual incremental cost of health care services utilized by lung cancer patients in the Colombian health system. Methods: We conducted a national cohort study of prevalent patients with lung cancer in Jan-2017 and followed-up until Dec-2017. We used two electronic algorithms to identify all lung cancer prevalent patients in the Contributory regime, using national health claims databases ( Base de datos de suficiencia de la Unidad de Pago por Capitación and Base de Datos Única de Afiliados), based on identification of ICD-10 codes for 4 months or more during the previous 3 years (sensitive algorithm) and adding the presence of at least one oncological procedure (specific algorithm). We identified all health services cost from the health system perspective (2017 USD). We performed a propensity score analysis to estimate the annual incremental cost of care of patients with lung cancer compared to those without the disease. Standardized differences lower than 0.1 were used to measure the balance of baseline variables. We used generalized linear models as a sensitivity analysis. Results: We identified 4,827 and 3,238 lung cancer prevalent patient using the sensitive and specific algorithm, respectively. Each cohort was matched 1:1 with a no-exposed cohort of 14,968,202 individuals without a diagnosis of lung cancer using a caliper of 0.0001. Matched samples showed good balance on baseline characteristics. Annual incremental cost for patients diagnosed with lung cancer in Colombia ranged between USD $ 3,146.92 and USD $ 4,156.23. We also estimated incremental cost for outpatient and inpatient healthcare services as shown in table. Conclusions: In 2017, each patient with lung cancer represented an incremental cost to the Colombian health system between 49.35% and 65.19% of GDP per capita. This information is paramount to understand lung cancer spending in Colombia and for other low- and middle-income countries. [Table: see text]
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