Open AccessMeasuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Allocation
Author(s) -
Feras A. Batarseh,
ChihHao Huang
Publication year - 2021
Publication title -
proceedings of the ... international florida artificial intelligence research society conference
Language(s) - English
Resource type - Journals
eISSN - 2334-0762
pISSN - 2334-0754
DOI - 10.32473/flairs.v34i1.128496
Subject(s) - health care , resource allocation , computer science , cluster analysis , operations research , outlier , quality (philosophy) , travelling salesman problem , operations management , artificial intelligence , economics , engineering , computer network , philosophy , epistemology , algorithm , economic growth
The quality of service in healthcare is constantly challengedby outlier events such as pandemics and naturaldisasters. In most cases, such events lead to critical uncertaintiesin decision making, as well as in multiple medicaland economic aspects of a hospital. External (geographical)or internal factors (medical and managerial) at hospitals,lead to shifts in planning, budgeting, and confidencein conventional processes. In some cases, support fromother hospitals becomes inevitable. This manuscript presentsthree intelligent methods that provide data-drivenindicators to help healthcare managers organize their economicsand identify the most optimum plan for resourceallocation and sharing. Using reinforcement learning, geneticalgorithms, traveling salesman, and clustering, weexperimented with different healthcare variables and presentedtools and outcomes that could be applied at healthinstitutes. In this poster, initial experiments are performed;the results are recorded, evaluated, and illustrated.