TY - JOUR
T1 - Surgical Case-Mix and Discharge Decisions
T2 - Does Within-Hospital Coordination Matter?
AU - Bavafa, Hessam
AU - Örmeci, Lerzan
AU - Savin, Sergei
AU - Virudachalam, Vanitha
N1 - Funding: This work was supported by Fishman-Davidson Center for Service and Operations Manage-ment at the Wharton School. Supplemental Material: The online companion is available at https://doi.org/10.1287/opre.2021.2177.
PY - 2022/3/1
Y1 - 2022/3/1
N2 - We study the problem faced by a profit-maximizing, resource-constrained hospital that controls patient inflows by designing a case-mix of its elective procedures and patient outflows via patient discharges. At the center of our analysis is the model that evaluates hospital profit for any combination of elective portfolio and patient discharge policies. Our model analyzes the impact of patient flow management decisions on the utilization of two main classes of hospital resources: “front end” (e.g., operating rooms) and “backroom” (e.g., recovery beds). We introduce a new approach for modeling the patient recovery process and use it to characterize the relationship between patient length of stay and probability of readmission. Using this modeling approach, we develop a two-moment approximation for the utilization of front-end and backroom resources. We focus on assessing the benefits associated with the hospital employing a coordinated decision-making process in which both portfolio and discharge decisions are made in tandem. Specifically, we compare the hospital’s profits in the coordinated setting to those under two decentralized approaches: a front-end approach, under which both decisions are made based exclusively on the front-end costs, and a “siloed” approach, in which discharge decisions are made based on backroom costs and the case-mix is determined as the optimal match for the discharge policy. We show that hospitals operating under the front-end policy can significantly benefit from coordination when backroom costs are sufficiently high even if they do not exceed surgical costs. On the other hand, for hospitals operating under the siloed policy, coordination brings significant benefits only when surgical costs are high and significantly dominate the cost structure.
AB - We study the problem faced by a profit-maximizing, resource-constrained hospital that controls patient inflows by designing a case-mix of its elective procedures and patient outflows via patient discharges. At the center of our analysis is the model that evaluates hospital profit for any combination of elective portfolio and patient discharge policies. Our model analyzes the impact of patient flow management decisions on the utilization of two main classes of hospital resources: “front end” (e.g., operating rooms) and “backroom” (e.g., recovery beds). We introduce a new approach for modeling the patient recovery process and use it to characterize the relationship between patient length of stay and probability of readmission. Using this modeling approach, we develop a two-moment approximation for the utilization of front-end and backroom resources. We focus on assessing the benefits associated with the hospital employing a coordinated decision-making process in which both portfolio and discharge decisions are made in tandem. Specifically, we compare the hospital’s profits in the coordinated setting to those under two decentralized approaches: a front-end approach, under which both decisions are made based exclusively on the front-end costs, and a “siloed” approach, in which discharge decisions are made based on backroom costs and the case-mix is determined as the optimal match for the discharge policy. We show that hospitals operating under the front-end policy can significantly benefit from coordination when backroom costs are sufficiently high even if they do not exceed surgical costs. On the other hand, for hospitals operating under the siloed policy, coordination brings significant benefits only when surgical costs are high and significantly dominate the cost structure.
KW - healthcare
KW - hospital capacity management
KW - inpatient flow management
KW - revenue management
KW - stochastic models
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U2 - 10.1287/OPRE.2021.2177
DO - 10.1287/OPRE.2021.2177
M3 - Article
AN - SCOPUS:85133972147
SN - 0030-364X
VL - 70
SP - 990
EP - 1007
JO - Operations Research
JF - Operations Research
IS - 2
ER -