The presence of two or more chronic conditions in the same individual has increased over recent years among different population groups. Studies have indicated that multimorbidity affects many adults and youth and leads to the overuse of healthcare services. In Colombia, the available evidence shows that 19.5% of all patients suffered from several chronic conditions in 2012-2016. The Wayuu people are one of the approximately 115 Indigenous ethnic groups in Colombia, with an estimated population of 380,400 (20% of the Indigenous people in the country). Anas Wayuu (AW) is an Indigenous-led non-profit health insurance company that provides health coverage to Wayuu people and collects data to reimburse health care services. A retrospective cohort study was performed, including a cross-sectional multimorbidity descriptive analysis. Administrative health records from AW healthcare providers were used as the data source. The purpose of the study was to identify multimorbidity patterns amongst AW enrollees. The Agglomerative Hierarchical Cluster analysis was used. Generalized linear mixed models were fitted for model differences in the healthcare services use rates provided to enrollees. In total, 159,921 were enrolled in AW in 2014-2017. The descriptive results indicated greater multimorbidity prevalence in female and older populations. Multimorbidity patterns across subpopulations showed morbidity profiles with a higher prevalence of musculoskeletal conditions. Healthcare utilization assessment in 2018-2019 showed higher use among multimorbid patients suffering from circulatory illnesses, Indigenous females, and those living in urban areas. The evidence about multimorbidity may help identify chronic disease clusters requiring further epidemiological research on causes, prevention, and treatment. The evidence may also be helpful for healthcare services planning and delivery for AW. The study provides information about multimorbidity among the Wayuu people, contributing to the Colombian population's health status monitoring and analysis strategies using administrative data.