Date of Award

2023

Degree Name

Healthcare Administration

College

College of Business

Type of Degree

M.S.

Document Type

Research Paper

First Advisor

Alberto Coustasse

Abstract

Introduction: There has been the transformative potential of Artificial Intelligence (AI) in addressing challenges within the Revenue Cycle Management (RCM) of healthcare organizations. The RCM process, laden with delays, inefficiencies, and high costs, has prompted a search for innovative solutions. With $400 billion of the country's healthcare spending that went toward RCM processes, 80% of healthcare leaders that reported staff stress and burnout from RCM processes, and 80% of patients that reported anger or confusion with their medical bills, RCM has posed as a great candidate for AI.

Methodology: The study utilized a literature review and a semi-structured virtual interview. Four databases were used to collect 102 total sources. These sources were reviewed and reduced to 36 total sources that were used in the written search. Of these 15 were used in the results section. Purpose of the Study: The purpose of this research was to analyze the effects of Artificial Intelligence implemented in Revenue Cycle Management that would impact administrative costs, staff burnout rate, and the quality of customer experience.

Results: The integration of Artificial Intelligence (AI) in healthcare Revenue Cycle Management (RCM) has revolutionized various facets, including estimating out-of-pocket costs, coding claims, and significantly streamlining processes. AI adoption has led to a substantial reduction in the workload associated with claim billing and collection, addressing a previously estimated $470 billion cost to RCM. Healthcare organizations implementing AI and automation have experienced accelerated payment cycles, with payments processed within 40 days instead of the conventional 90 days. This has not only improved understanding of past denials but has also ensured better adherence to payer rules, resulting in a higher revenue percentage from claims.

Moreover, the impact of AI extended to Accounts Receivable (AR) management, with targeted recommendations that enhanced decision-making processes and increased AR collections by 1% of Net Patient Service Revenue (NPSR). AI's role in improving work quality, as indicated by a 1.3% enhancement in resolved customer problems, has positively influenced job satisfaction among RCM professionals. Case studies, such as those of Auburn Community Hospital and OhioHealth, showcased AI's effectiveness in computer-assisted coding, reduced unnecessary correspondences, improved staff experience, and generated personalized consumer profiles. Overall, AI's integration has not only addressed workforce shortages and burnout but has also significantly improved comprehensive patient data analysis resulting in better quality of customer experience.

Discussion/ Conclusion: The research on the implementation of Artificial Intelligence (AI) in Revenue Cycle Management (RCM) demonstrated significant positive outcomes. The study supported the hypothesis that AI adoption in healthcare organizations leads to a substantial reduction in administrative costs, decreased staff burnout rates, and a notable improvement in the quality of customer experience. The multifaceted advantages of AI in RCM are highlighted, including precise estimation of out-of-pocket costs, automation of claim coding processes, and optimization of labor-intensive billing tasks. Financially, organizations leveraging AI report improved revenue capture, contributing to a significant reduction in the estimated $470 billion cost associated with RCM. The study emphasized the practical implications of AI, showcasing its ability to streamline processes, alleviate staff burnout, and enhance the overall patient financial experience. Despite certain limitations, the research underscored the transformative impact of AI in healthcare RCM, paving the way for increased efficiency, improved job satisfaction, and enhanced financial well-being for healthcare institutions.

Subject(s)

Health Services Administration.

Health facilities -- Business management.

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