Healthcare systems face a dense mix of pressures. To sustain high-quality services, providers must absorb rising patient volumes, extend limited resources, and contain escalating costs. In this context, business analytics has shifted from optional to strategic, enabling data-driven decisions that lift both clinical and operational performance. By using different methods to analyze detailed data from sources like electronic health records and clinical registries, organizations can spot trends, predict what patients will need, and improve staffing, capacity, and supply chains. The result is better outcomes, smoother workflows, and improved cost efficiency. Analytics now supports core domains: operations management, clinical decision support, population health, and personalized care. Predictive models, for example, identify people at higher risk and prompt early actions that reduce unnecessary hospital readmissions while strengthening prevention programs. Just as crucial, prescriptive tools recommend targeted actions, helping leaders weigh trade-offs and choose among constrained options with clarity and confidence. Emerging technologies promise to amplify these gains. Artificial intelligence, the Internet of Medical Things, and genomics-informed precision medicine can deliver real-time insights and tailored interventions at the point of care, tightening feedback loops between data, decision, and action. Yet meaningful impact depends on thoughtful execution grounded in clear governance, high-quality data, interoperability, workforce training, and change management. Taken together, the evidence suggests that when implemented deliberately, business analytics can reshape healthcare delivery into systems that are more efficient, resilient, and patient-centered. By addressing adoption barriers proactively and embracing modern analytic capabilities, organizations can secure durable improvements in operational performance, clinical outcomes, and the overall quality and value of care for patients and communities alike.
Begum et al. (Fri,) studied this question.