Determining health care cost drivers in older Hodgkin lymphoma survivors using interpretable machine learning methods.

Journal: Journal of managed care & specialty pharmacy
PMID: 40152796

Abstract

BACKGROUND: The cost of health care for patients with Hodgkin lymphoma (HL) is projected to rise, making it essential to understand expenditure drivers across different demographics, including the older adult population. Although older HL patients constitute a significant number of HL patients, the literature on health care expenditures in older HL patients is lacking. Predictive capabilities of machine learning (ML) methods enhance our ability to leverage a data-driven approach, which helps identify key predictors of expenditures and strategically plan future expenditures.

Authors

  • Zasim Azhar Siddiqui
    Department of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown.
  • Yves Paul Mbous
    Department of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown.
  • Sabina Nduaguba
    Department of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown.
  • Traci LeMasters
    Department of Pharmaceutical Systems and Policy, West Virginia University School of Pharmacy, Robert C. Byrd Health Sciences Center [North], P.O. Box 9510, Morgantown, WV, 26506-9510, USA. Electronic address: traci.lemasters@hsc.wvu.edu.
  • Virginia G Scott
    Department of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown.
  • Jay S Patel
    Department of Health Services Administration and Policy College of Public Health, Temple University, Philadelphia, PA.
  • Usha Sambamoorthi
    Department of Pharmacotherapy, College of Pharmacy, "Vashisht" Professor of Disparities, Health Education, Awareness & Research in Disparities (HEARD) Scholar, Texas Center for Health Disparities, University of North Texas Health Sciences Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA. Electronic address: usha.sambamoorthi@unthsc.edu.

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