Select, route and schedule: optimizing community paramedicine service delivery with mandatory visits and patient prioritization

Shima Azizi (), Özge Aygül (), Brenton Faber (), Sharon Johnson (), Renata Konrad () and Andrew C. Trapp ()
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Shima Azizi: Peter J. Tobin College of Business, St. John’s University
Özge Aygül: Worcester Polytechnic Institute
Brenton Faber: Worcester Polytechnic Institute
Sharon Johnson: Worcester Polytechnic Institute
Renata Konrad: Worcester Polytechnic Institute
Andrew C. Trapp: Worcester Polytechnic Institute

Health Care Management Science, 2023, vol. 26, issue 4, No 7, 719-746

Abstract: Abstract Healthcare delivery in the United States has been characterized as overly reactive and dependent on emergency department care for safety net coverage, with opportunity for improvement around discharge planning and high readmissions and emergency department bounce-back rates. Community paramedicine is a recent healthcare innovation that enables proactive visitation of patients at home, often shortly after emergency department and hospital discharge. We establish the first optimization-based framework to study efficiencies in the management and operation of a community paramedicine program. The collective innovations of our modeling include i) a novel hierarchical objective function with the goals of fairly increasing patient welfare, lowering hospital costs, and reducing readmissions and emergency department visits, ii) a new constraint set that ensures priority same-day visits for emergent patients, and iii) a further extension of our model to determine the minimum supplemental resources necessary to ensure feasibility in a single optimization formulation. Our medical-need based objective function prioritizes patients based on their clinical features and seeks to select and schedule patient visits and route healthcare providers to maximize overall patient welfare while favoring shorter tours. We use our methods to develop managerial insights via computational experiments on a variety of test instances based on real data from a hospital system in Upstate New York. We are able to identify optimal and nearly optimal tours that efficiently select, route, and schedule patients in reasonable timeframes. Our results lead to insights that can support managerial decisions about establishing (and improving existing) community paramedicine programs.

Keywords: Operations research; Operations management; Community paramedicine; Integer optimization; Team orienteering; Mandatory visits; Time windows (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10729-023-09646-3

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