Artificial Intelligence in Healthcare Systems: Strategic Applications for Budget Management, Resource Allocation and Workflow Optimization

Healthcare has been facing an increase in costs, a rise in complexity of administrative activities and a lack of resources which ultimately threatens the long-term viability of quality healthcare services. The purpose of this paper is to explore ways in which Artificial Intelligence (AI) will assist in addressing the issues listed above by creating better methods to manage budgets, allocate resources and create efficient workflows.

Although there have been many studies on AI as it relates to medical diagnoses and treatment plans, very little research has focused on its use in healthcare administration or finances. However, the potential benefits at the level of the entire system are substantial

As predictive analytics used in budget management can be mentioned:

• Organizations using predictive analytics for forecasting expenditures

• Tools such as predictive analytics can aid administrators in detecting inefficiency, identifying areas where additional funding may be needed and developing adaptable financial strategies.

Intelligent system proved a means to integrate disparate data sets such as patient demographics, clinical protocols and operational expenses information. With this integrated data sets intelligent systems can perform what-if scenarios and respond quickly to fiscal pressure based on evidence rather than opinion.

The integration of computational models provides a method for matching available capacity with dramatically changing demand. Workflow optimization addresses operational problems on a daily basis by automating routine administrative functions, directing patients in an intelligent manner. It can predict and manage inventory supplies also. Examples include reducing documentation burdens through natural language processing, enhancing triage and referrals through decision-support tools. To successful implement AI solutions are required several factors including having high-quality data, being able to communicate, interoperability, strong security measure for protecting personal heath information, privacy and to proactively mitigate possible biases in AI algorithms that would perpetuate existing social inequalities.