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Discovering Primary Medical Procedures and their Associations with Other Procedures in HCUP Data

Author

Listed:
  • Mamoun T. Mardini

    (University of Florida
    University of Florida)

  • Zbigniew W. Raś

    (University of North Carolina
    Polish-Japanese Academy of Information Technology)

Abstract

In recent years, healthcare spending has risen and become a burden on governments especially in the US. The selection of the primary medical procedure by physicians is the first step in the patient treatment process and is considered to be one of the main causes for hospital readmissions if it is not done correctly. In this paper, we propose a system that can identify with high accuracy the primary medical procedure for a newly admitted patient. We propose three approaches to anticipate which medical procedure should be primary. Additionally, we propose the procedure graph, which shows all possible paths that a new patient may undertake during the course of treatment. Finally, we extract the possible associations between the primary procedure and other procedures in the same hospital visit. The results show the ability of our proposed system to identify which procedure should be primary and extract its associations with other procedures.

Suggested Citation

  • Mamoun T. Mardini & Zbigniew W. Raś, 2022. "Discovering Primary Medical Procedures and their Associations with Other Procedures in HCUP Data," Information Systems Frontiers, Springer, vol. 24(1), pages 133-147, February.
    • Handle: RePEc:spr:infosf:v:24:y:2022:i:1:d:10.1007_s10796-020-10058-9
    DOI: 10.1007/s10796-020-10058-9
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    References listed on IDEAS

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    1. Linda Gorman, 2013. "John C. Goodman, Priceless: Curing the Healthcare Crisis," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 48(1), pages 81-82, February.
    2. Atreyi Kankanhalli & Jungpil Hahn & Sharon Tan & Gordon Gao, 2016. "Big data and analytics in healthcare: Introduction to the special section," Information Systems Frontiers, Springer, vol. 18(2), pages 233-235, April.
    3. Hongqiao Yang & Weizi Li & Kecheng Liu & Junping Zhang, 2012. "Knowledge-based clinical pathway for medical quality improvement," Information Systems Frontiers, Springer, vol. 14(1), pages 105-117, March.
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