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Optimizing Healthcare Operations (Scheduling, Billing, and Resource Allocation, Reducing Operational Inefficiencies in Hospitals and Clinics.) with Generative AI: Records, Trial Requirements, and Patient Preferences

Author(s) Antony Ronald Reagan Panguraj
Country United States
Abstract The healthcare segment especially hospitals and clinics remain challenged to find the best practices in health system functioning for arranging work, fee recovery, and resources management. These things can result in higher costs, delays in providing treatments, patient dissatisfaction, and in general, the lowered quality of treatments. Thus, there is a new remarkable opportunity with the evolution of Generative Artificial Intelligence (AI) technologies to solve these operational issues. Thus, on the basis of using the models of machine learning, Generative AI can significantly improve scheduling, billing and help in the management of their users’ resources so that hospitals and clinics operate more efficiently. AI is useful in other areas; forecasting patient attendance, managing appointment bookings online, and improving billing for patients besides managing resources in line with actual data acquired through AI analytics. The following paper seeks to ascertain how Generative AI can be adopted within the healthcare sector to minimise the numerous wastages, optimize services, and incrementally reduce expense. Through integrating Generative AI in ways to reinvent or optimize operational aspects of different healthcare institutions substantial enhancements are achieved concerning: The emphasis is made upon the usage of artificial intelligence in scheduling systems, billing automatization, and resource management, which is the main reason of the decrease of operational efficiency in hospitals and clinics. In the paper conclusion, the existing problems, including data privacy, implementation difficulties, and the necessity for reliable AI models, for Generative AI implementation are highlighted and explained in terms of the potential for healthcare operationalization.
Keywords Healthcare Operations, Generative AI, Scheduling, Resource Allocation, Billing Automation
Field Engineering
Published In Volume 2, Issue 11, November 2021
Published On 2021-11-03
Cite This Optimizing Healthcare Operations (Scheduling, Billing, and Resource Allocation, Reducing Operational Inefficiencies in Hospitals and Clinics.) with Generative AI: Records, Trial Requirements, and Patient Preferences - Antony Ronald Reagan Panguraj - IJLRP Volume 2, Issue 11, November 2021. DOI 10.5281/zenodo.14960441
DOI https://doi.org/10.5281/zenodo.14960441
Short DOI https://doi.org/g86v48
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