Expanding Our Grasp: Artificial Intelligence as the Next Leap Forward in Healthcare Quality

Open Access
Article
Conference Proceedings
Authors: Jay KalraPatrick Seitzinger

Abstract: Healthcare quality and improvement relies on recognizing and improving patters of practice. AI involves self-learning systems using machine learning and pattern recognition to emulate thought processes typically conducted by humans. The purpose of this project was to assess the current state and challenges of healthcare quality and to charter a path forward for innovative applications of Artificial Intelligence technology to strengthen healthcare strategies. Knowledge integration was conducted across medical disciplines to identify key challenges in healthcare delivery and assess how Artificial Intelligence can be leveraged to strengthen healthcare quality. Currently, approximately half of the global population spends less than 5 minutes with their physician during doctor visits. It takes on average of 23.1 seconds for a physician to interrupt patients while they are telling their story. Most patients around the world will experience one or more diagnostic errors in their lifetime. Systematic reviews and narrative reviews of the available evidence report varying global diagnostic error rates ranging from 5% to 23.5%. Currently the physician suicide rate that is 1.5 to 4.5 times higher than that of the general population. Between 30-50% of medical students and residents experience burnout. Burnout is nearly doubling the rate of medical errors, and physicians involved in major errors are experiencing a threefold increase in suicidal ideation. AI technology has the potential to have transformative effects on increasing diagnostic accuracy, mmitigating medical errors, screening and early diagnosis, ddetermining disease susceptibility and progression. Advantages of AI include efficiency, accuracy, prediction/modelling, standardization, immune to fatigue, self-correcting abilities, and accuracy. Drawbacks of AI include developmental costs, unclear legislation, integration issues, lack of explainability, insufficient digital literacy, limited data sharing, and fear of the known. Even with unprecedented innovations in healthcare, we must utilize tried and true methods of healthcare assurance and improvement including identifying vulnerabilities, mitigating biases, and ensuring health equity. AI presents a tool to address longstanding issues in healthcare delivery and achieve a caliber of healthcare quality that was previously beyond our grasp.

Keywords: Artificial Intelligence, Healthcare, Quality Improvement, Burnout

DOI: 10.54941/ahfe1003467

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