Strengthening Resilience in Healthcare Organizations through an AI- enhanced Performance Management Framework

This doctoral thesis embarks on a unique exploration, delving into the intersection oforganizational resilience and artificial intelligence (AI) technologies in the context of thehealthcare sector. It is a timely and significant endeavor, considering the compellingpressures healthcare organizations face to adapt, evolve, and remain resilient in an era ofcomplex global challenges. The research begins by contextualizing healthcare organizationswithin their complex environments, discussing the inherent characteristics of the setting andthe diverse and intricate challenges that it poses.The necessity for resilience, a multidisciplinary and multifaceted concept, central toorganizational survival and success, derives from critical issues arising from communitydemands, configuring the urgent need for an indispensable transition toward organizationalresilience in the healthcare sector. Then, AI's transformative potential is explored byanalyzing its applications in clinical and management practice. The research findings revealthat, by leveraging AI-based technological innovations, decision-makers can not onlyremodel healthcare management paradigms but also address the challenges presented by arapidly evolving environment. The adoption of AI-based technologies, however, posescritical challenges, including economic, social, technical, environmental, ethical, andregulatory issues, which are further addressed. Against this backdrop, the primary objectiveof this research is to develop a framework integrating AI into performance management(PM) systems of healthcare organizations, resulting in strengthened organizational resilienceand increased efficiency and effectiveness, called the Resilient AI Performance OptimizationFramework (RAIPOF).The methodology section describes the methods used to build the framework, notably theliterature review and employment of the Design Science Research Methodology (DSRM)process model. Specifically, a literature review is performed to assess the validity of thefollowing research questions, constituting the theoretical grounding of the proposedframework:RQ1: Can formulation and control of key performance indicators (KPIs) influenceorganizational elements of resilience?RQ2: Can AI-based technologies produce more efficient and effective KPIs?If both hypotheses are validated, the conceptualization of a framework able to capitalize onthe relationship between AI-based algorithms, KPIs, and elements of resilience is possible.Then, it becomes plausible to propose the RAIPOF for improving organizational resilienceand overall performance through the use of AI-based enhanced KPIs.Once these research questions are verified through a literature review, the framework is builtusing the DSRM process model.Finally, this study concludes the exploration of the impact of AI integration into the PMsystems of healthcare organizations through a single-case study approach at MediterraneanInstitute for Transplantation and Advanced Specialized Therapies (ISMETT), a hospital ofmedical excellence, to assess the validity of the framework.The research employed a systems thinking approach to identify the complex interrelationsarising from the potential implementation of AI-driven information systems in healthcare.The approach was complemented by an analysis of the potential impact on KPIs, which wasconducted using OpenAI’s ChatGPT, a popular large language model (LLM). This analysishighlighted that the RAIPOF offers a systematic way to capture the dynamics surroundingAI integration.This framework represents a robust tool to assist decision-makers in devising enhancedstrategies to optimize patient flow and the whole resource allocation process while reducingthe organization’s vulnerabilities to sudden disruptive events. In summary, this thesisexplores the potential of AI applications in PM to strengthen the resilience of healthcareorganizations. By strategically employing AI-based technologies, healthcare organizationscan navigate complexity, anticipate change, and thrive in the face of change and threats withhigh disruptive potential.