BACKGROUND: Healthcare administrative databases have many advantages for conducting studies on asthma. However, identifying asthma patients in these databases requires using algorithms based on reimbursement data. OBJECTIVE: The main objective of this study was to describe published algorithms identifying asthma patients in healthcare administrative databases. METHODS: We performed a systematic review of the studies using an algorithm to identify asthma patients from healthcare administrative databases, and published between 01/01/2016 and 31/12/2020 in Pubmed®. Data related to the characteristics of the studies, the algorithms used, and their validation were extracted using a standardized form. RESULTS: Three hundred and three studies were selected totaling 471 algorithms including 266 (56.5%) identifying asthma patients without details regarding severity or control, 41 (8.7%) identifying asthma exacerbations and 99 (21.0%) characterizing asthma severity or control. Among the 266 algorithms identifying asthma patients, we found a total of 138 "different" algorithms and most of them used only diagnostic codes - from hospital or ambulatory data (n = 64, 46.4%) or combined diagnostic codes with drug dispensations (n = 36, 26.1%). Only 21.1% of the 266 algorithms used were reported as validated. CONCLUSION: Many algorithms for identifying cases of asthma are available; the choice of an algorithm should be based on its relevance according to the objective of the study, the type of asthma, the type of healthcare administrative database, and its validation.