Review highlights real-world clinical datasets’ applications in healthcare training, improving outcomes, suggesting effective methodologies.
Real-world clinical databases offer students, residents, fellows, clinician-educators, librarians, and early-career investigators an accessible entry point into population health, quality improvement, and outcomes research. Leveraging large-scale, de-identified datasets enables the investigation of healthcare delivery, cost, treatment effectiveness, and clinical outcomes without the need for patient recruitment or extensive funding sources. This review provides a synopsis of four widely used real-world clinical datasets: the Healthcare Cost and Utilization Project (HCUP, low-cost with a Data Use Agreement), the Medical Information Mart for Intensive Care (MIMIC-IV, openly available), TriNetX (subscription-based), and Epic Cosmos (institutional access). Highlighting their structure, data types, access requirements, and ideal use cases, the distinguishing features of each database are discussed. Finally, we provide guidance on how learners and research teams can formulate research questions, identify the appropriate dataset, and leverage mentorship resources for database-focused research, allowing them to meaningfully engage in data-driven research and contribute to improving healthcare delivery and patient outcomes.
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Wood et al. (2026) studied this question.
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