Data Analytics for Smart Healthcare Systems: Bridging Patient and Provider Needs

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Gurucharan Marthi Krishna Kumar, Shri Harini Ramesh, Vijay Jeyakumar

Published: 01 Jan 2026, Last Modified: 06 Jan 2026CrossrefEveryoneRevisionsCC BY-SA 4.0
Abstract: The exponential increase in healthcare data offers immense potential for enhancing medical care. However, this data is often fragmented and scattered across various systems, with integration hindered by inconsistent formats and lack of interoperability. These challenges limit the extraction of valuable insights and the enhancement of healthcare services for both patients and providers. For patients, integrating AI-driven chatbots with electronic health records (EHR) provides personalized health guidance and aids in navigating health information effectively. Human–computer interaction tools and data visualization techniques convert complex health data from EHR and wearable devices into user-friendly formats, thereby enhancing health literacy. eHealth and mHealth solutions leverage real-time data from wearables to offer personalized recommendations and continuous feedback. This approach supports proactive health management by alerting patients to potential issues and facilitating timely responses. For healthcare providers, predictive analytics utilize historical and real-time patient data to improve early disease detection, risk stratification, and resource management. By analyzing data on hospital bed occupancy, staff schedules, and patient flow, these tools enable more efficient resource allocation and operational decisions. Large language models enhance real-time consultations by summarizing patient histories and clinical guidelines, ensuring that providers have comprehensive, upto-date information at their fingertips. This improves treatment planning and overall healthcare delivery. This review study explores the data analytics solutions for both patient and provider challenges, as well as the ethical and security issues associated with these solutions, focusing on data privacy, security, and the responsible use of artificial intelligence. By addressing these issues and adopting new technological solutions, healthcare services can achieve increased efficiency, personalization, and accessibility.