@article{Batarseh_Huang_2021, title={Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Allocation}, volume={34}, url={https://journals.flvc.org/FLAIRS/article/view/128496}, DOI={10.32473/flairs.v34i1.128496}, abstractNote={<p>The quality of service in healthcare is constantly challenged<br>by outlier events such as pandemics and natural<br>disasters. In most cases, such events lead to critical uncertainties<br>in decision making, as well as in multiple medical<br>and economic aspects of a hospital. External (geographical)<br>or internal factors (medical and managerial) at hospitals,<br>lead to shifts in planning, budgeting, and confidence<br>in conventional processes. In some cases, support from<br>other hospitals becomes inevitable. This manuscript presents<br>three intelligent methods that provide data-driven<br>indicators to help healthcare managers organize their economics<br>and identify the most optimum plan for resource<br>allocation and sharing. Using reinforcement learning, genetic<br>algorithms, traveling salesman, and clustering, we<br>experimented with different healthcare variables and presented<br>tools and outcomes that could be applied at health<br>institutes. In this poster, initial experiments are performed;<br>the results are recorded, evaluated, and illustrated.</p>}, journal={The International FLAIRS Conference Proceedings}, author={Batarseh, Feras A. and Huang, Chih-Hao}, year={2021}, month={Apr.} }