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4375. The Role of Ethics and Altruism: Mapping the Determinants of Healthcare Accessibility for Medicare Beneficiaries
Invited abstract in session WD-18: Developing Countries and Sustainable Humanitarianism , stream OR for Development and Developing Countries.
Wednesday, 14:30-16:00Room: 42 (building: 116)
Authors (first author is the speaker)
1. | Nina Kajiji
|
Computer Science and Statistics, University of Rhode Island, and The NKD Group, Inc. | |
2. | Gordon Dash
|
Finance and Decision Sciences, University of Rhode Island | |
3. | Miriam Dash
|
Urologic Surgery, Mayo Clinic |
Abstract
It is widely acknowledged that healthcare providers' interests may diverge from those of patients. In and of itself, healthcare accessibility is a complex measure rooted in the ability of an individual to receive healthcare effectively with demonstrated anxiolytic effects. Annually, the Center for Medicare and Medicaid Services gathers survey data from current beneficiaries of Medicare in the United States and Puerto Rico (excluding healthcare facilities) to assess healthcare equity. These surveys delve into chronic risk factors associated with various diseases and mental health conditions. This study innovates extant Medicare patient care models by identifying the error-minimizing determinants underlying the probability of delivering a correct chronic condition diagnosis. We propose a novel multiobjective and multi-target shallow-learning radial basis function artificial neural network specification for classification. Using Explainable AI, we provide policy-based results, allowing providers to understand Medicare patients' disease pathology better. Diagnosticians are likely to have a lesser financial incentive to recommend profitable procedures regardless of appropriateness, reducing poor quality and costly care when providers are profit-incentivized instead of generous.
Keywords
- Machine Learning
- Complex Societal Problems
- Humanitarian Applications
Status: accepted
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