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An expert system for determining Medicaid eligibility.

A M Sear1

  • 1Department of Health Policy and Management, University of South Florida, Tampa 33612.

Journal of Medical Systems
|October 1, 1988
PubMed
Summary

Most healthcare providers struggle with complex Aid to Families with Dependent Children (AFDC) Medicaid eligibility rules, leading to significant revenue loss. An expert system, MEDELEX, streamlines this process, enabling faster and more accurate patient eligibility assessments.

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Area of Science:

  • Health Informatics
  • Artificial Intelligence in Healthcare
  • Public Health Policy

Background:

  • Complex Aid to Families with Dependent Children (AFDC) Medicaid eligibility criteria pose challenges for healthcare providers.
  • Inaccurate or unattempted eligibility checks result in substantial annual revenue loss for health service providers nationwide.

Purpose of the Study:

  • To present MEDELEX, an expert system designed to rationalize and automate the Medicaid eligibility determination process.
  • To enable real-time assessments of patient eligibility for AFDC Medicaid.

Main Methods:

  • Development of MEDELEX, an expert system utilizing Prolog programming language.
  • Implementation on an 8 MHz MS-DOS microcomputer with 640 KB RAM for data entry and determination.

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Main Results:

  • MEDELEX requires approximately 20 minutes for data entry and only 5 seconds for eligibility determination.
  • The system is designed for adaptability to state-specific AFDC Medicaid eligibility variations.

Conclusions:

  • Expert systems like MEDELEX offer a viable technological solution to the complexities of Medicaid eligibility determination.
  • Implementing such systems can improve revenue capture for healthcare providers and streamline access to care for eligible patients.