Background: Medical-administrative databases are a valuable source of information in the field of endocrine, nutritional, and metabolic diseases. The aim of this article is to describe the initial work conducted by the Sniiram Data Network (REDSIAM) working group in this field. Methods: Algorithms developed in France for diabetes, dyslipidemia treatment, precocious puberty, and bariatric surgery using data from the National Inter-Regime Health Insurance Information System (Sniiram) were identified and described. Results: Three algorithms for identifying individuals receiving care for diabetes are available in France. These algorithms are based either on long-term care data, reimbursements for antidiabetic treatments, or a combination of these two care modalities linked to diabetes-related hospitalizations. Each of these algorithms serves different purposes, and the choice should depend on the study’s objective. Additionally, algorithms for identifying individuals treated for dyslipidemia, precocious puberty, or who have undergone bariatric surgery are also available. Conclusion: The initial work of the REDSIAM working group in the field of endocrine, nutritional, and metabolic diseases provides an inventory of algorithms currently available in France and their objectives, outlines their limitations and advantages, and makes these findings available to the scientific community. This work will continue with the study of algorithms addressing the incidence of childhood diabetes, thyroidectomy for thyroid nodules, hypothyroidism, hypoparathyroidism, and amyloidosis.