ARTIFICIAL INTELLIGENCE GOVERNANCE AND RISK MANAGEMENT FRAMEWORK FOR HEALTHCARE INFORMATION SYSTEMS
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Keywords
Artificial Intelligence, Healthcare Governance, Risk Management, Clinical Decision Support, Patient Safety, Regulatory Compliance, Algorithm Accountability
Abstract
Healthcare organizations increasingly deploy artificial intelligence systems for diagnostic support, treatment recommendations, and operational optimization, yet these implementations often lack comprehensive governance and risk management frameworks. This research develops an integrated AI governance framework specifically designed for healthcare information systems, addressing unique challenges including patient safety, data privacy, regulatory compliance, and clinical accountability. We analyzed 156 healthcare AI implementations across multiple institutions to identify governance gaps and risk factors. Our framework encompasses five core dimensions: ethical oversight structures, technical risk assessment protocols, clinical validation requirements, data governance standards, and regulatory compliance mechanisms. Through systematic evaluation of existing AI deployments, we identified critical risk categories including algorithmic bias affecting patient populations, model drift compromising diagnostic accuracy, data quality issues undermining predictions, and inadequate human oversight enabling automation errors. The framework incorporates continuous monitoring processes, stakeholder accountability structures, and incident response protocols tailored to healthcare contexts. Implementation results demonstrate that organizations adopting structured governance frameworks reduced AI-related adverse events by 67% and improved regulatory audit outcomes significantly. This research provides healthcare administrators with practical guidance for establishing responsible AI governance while maintaining innovation capacity and patient safety standards.
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Md Tanzimul Islam
Master of Science in Information Technology Management Webster University, Missouri, USA
Md Rokibul Hasan
Department of Computer Science Southeast Missouri State University
Md Jahid Howlader
Graduate Student, Master of Arts in Information Technology Management Webster University
Md Minar Hossain
MS in Business Analytics, Trine University MBA, BBA, University of Dhaka
Md Mehedi Hasan Antor
BBA in Finance, National University
Sinigdha Islam
Epidemiology analyst Metro Medical Center Pllc , Michigan, USA, MBBS, Master of Public Health (MPH)(Epidemiological and Biostatistics) King Graduate School, Monroe University, New Yor
