TITLE:
Translating AI Ethics into Hospital Operations: A PPTO Framework for Evidence-Based Governance
AUTHORS:
Vernette Grant, Robert E. Levasseur
KEYWORDS:
AI Governance, Ethical AI, Healthcare Management, Bias Mitigation, Organizational Frameworks, Responsible AI
JOURNAL NAME:
Open Journal of Business and Management,
Vol.14 No.2,
March
5,
2026
ABSTRACT: Healthcare organizations face mounting pressure to adopt artificial intelligence (AI) responsibly despite ethical risks that include algorithmic bias, opacity, and inequitable care delivery. While high-level AI ethics principles abound, hospitals lack practical frameworks to operationalize these principles into governance structures with measurable outcomes. This paper advances the People-Process-Technology-Operations (PPTO) framework specifically for ethical AI governance in hospital settings, extending prior organizational applications to address unique challenges of translating abstract ethical principles into concrete operational practices. Drawing on recent governance case studies, implementation protocols, and scoping reviews of AI ethics frameworks in healthcare, this work provides hospital leaders with actionable guidance including role definitions, lifecycle review workflows, monitoring mechanisms, and performance metrics aligned with ethical commitments. The framework emphasizes scalability across varying organizational maturity levels and resource constraints while integrating with existing clinical governance structures. By systematically connecting governance activities to operational outcomes, including equity indicators, safety metrics, and stakeholder trust measures, PPTO transforms ethical AI from compliance burden into strategic advantage. Hospital executives can use this framework as both a diagnostic tool for assessing governance readiness and a roadmap for building capabilities that accelerate responsible AI adoption while mitigating legal, ethical, and reputational risks.