AI-Based Clinical Decision Support Systems in Smart Hospitals

Dhanaraj Sathiri

Abstract: Artificial Intelligence (AI) has the potential to transform healthcare delivery and enhance clinical decision-making. AI-based Clinical Decision Support Systems (CDSS) can complement human expertise, leading to improved patient care and greater efficiency in smart hospitals. Smart hospitals represent an evolution of the concept of smart health by incorporating real-time, event-driven monitoring of patients and the hospital environment, enabling intelligent deployment of AI techniques in CDSS. Three architectural features characterize smart hospital CDSS: integration with Electronic Health Records for patient and environmental monitoring, a human-AI collaboration model aligned with clinical workflow, and seamless communication with monitoring equipment, devices, and other CDSS. AI-based CDSS support a variety of clinical tasks, including diagnostic and therapeutic decision-making, critical care, medication safety, and adverse event prevention. Evaluation of AI-based CDSS encompasses the effects on clinical outcomes, care quality, user experience, safety, security, privacy, intelligibility, bias and discrimination, alignment with regulatory frameworks, implementation roadmaps, governance, and continuous improvement. A foundational strategy for developing AI-based CDSS in smart hospitals combines existing knowledge and evidence with breakthroughs in intelligent predictive models and natural language processing. There are three principal driving forces: the massive quantities of health-related data generated within smart hospitals, the increasing overlap and redundancy in clinical work due to repetitive and routine tasks, and the societal imperative to enhance the science of medicine in order to achieve precision medicine and precision public health. When used responsibly, AI-based CDSS reduce system-wide heterogeneity, standardize responses to predictable scenarios, improve system efficiency, and minimize latent error. However, it is crucial to ensure that AI is not deployed simply for efficiency gains, which shifts the balance of responsibility and may have negative consequences for patients, hospital staff, and society. Promising AI-based CDSS applications will serve as testbeds for the implementation of these systems in real-time operation at scale in smart hospital environments.

Keywords: Artificial intelligence, clinical decision support systems, smart hospitals, electronic health records, differential diagnosis clinical decision support systems, disease-specific literature-based support, telemedicine, COVID-19, patient safety

How to Cite?: Dhanaraj Sathiri, "AI-Based Clinical Decision Support Systems in Smart Hospitals", Volume 12 Issue 12, December 2023, International Journal of Science and Research (IJSR), Pages: 2291-2302, https://www.ijsr.net/getabstract.php?paperid=MS2312181849, DOI: https://dx.doi.org/10.21275/MS2312181849