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- W4308492039 abstract "Hospitals are struggling to maintain a balance between demand and the capacity of resources. It is difficult because demand is highly uncertain and resource capacity is limited. Among hospital resources, physicians are one of the most vital and scarce resources without whom hospitals cannot function. Along with ensuring the availability of physicians, planning on their allocation as per the hospital case mix is expected for quality care. This has motivated us to conduct a study on case-mix-based physician allocation in hospitals. Henceforth, to help hospitals in such challenging decision-making, we propose a two-stage stochastic programming approach in which decisions on regular physician allocation and their capacity adjustments (by overtime, outsourcing, and hiring) in each hospital department are a trade-off between expected cost and patient demand fulfillment. We test the allocations and adjustments with the data of a multispecialty hospital in India, finding solutions to expect a 27.44% cost reduction with patient demand fulfillment when compared with the current allocation of the case study hospital. Results from sensitivity analysis inferred that our proposed model performs well in all sets of variations prevailing in any hospital like patient demand, treatment times, and physician allocation cost parameters. To our best knowledge, this is the first paper that focuses on optimal physician allocation decisions in all the departments of a multispecialty department under uncertain demand and treatment times and the results have also indicated that our proposed model performs well compared to the current allocation model of the hospital. Hence, it is a remarkable contribution towards healthcare service delivery and hospital cost reduction." @default.
- W4308492039 created "2022-11-12" @default.
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- W4308492039 date "2022-12-01" @default.
- W4308492039 modified "2023-09-29" @default.
- W4308492039 title "Case mix-based resource allocation under uncertainty in hospitals: Physicians being the scarce resource" @default.
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- W4308492039 doi "https://doi.org/10.1016/j.cie.2022.108767" @default.
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