Tactical resource allocation and elective patient admission planning in care processes

Abstract

Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to meet production targets/to serve the strategically agreed number of patients, and to use resources efficiently. This paper proposes a method to develop a tactical resource allocation and elective patient admission plan. These tactical plans allocate available resources to various care processes and determine the selection of patients to be served that are at a particular stage of their care process. Our method is developed in a Mixed Integer Linear Programming (MILP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital, thereby integrating decision making for a chain of hospital resources. Computational results indicate that our method leads to a more equitable distribution of resources and provides control of patient access times, the number of patients served and the fraction of allocated resource capacity. Our approach is generic, as the base MILP and the solution approach allow for including various extensions to both the objective criteria and the constraints. Consequently, the proposed method is applicable in various settings of tactical hospital management.

Managing urgent care in hospitals

“…We model the waiting times based on an ILP formulation that allocates resources and plans elective patients on a tactical level [115]. Herein multiple care processes are modeled, and the number of patients to treat at particular stages of their care pathway is determined taking into account the waiting time of patients at each care process.…”

Integrated decision making in healthcare : an operations research and management science perspective

“…The cost function C t (S t , x t ) related to our current state S t and decision x t can be modeled in various ways. The main objectives of tactical planning are to achieve equitable access and treatment duration for patient groups and to serve the strategically agreed number of patients [261]. The focus in developing this model is on the patient's waiting time (equitable access and treatment duration), and we assume that the strategically agreed number of patients is set in accordance with patient demand (as the model accepts all patients that arrive).…”

“…To implement a tactical planning decision, it requires integer values for the number of patients to be served from each queue. While the ADP-model can contain noninteger values for each entry (u ∈ U) in the waiting lists and the tactical planning decision, the integer restriction is on the total number of patients to be served from each queue (summed over all u ∈ U for one queue), like explained in [261]. In case only very few patients are included in the system, causing many queues to have 0 or 1 patient, developing a rounding procedure can be beneficial to ensure integer transfers between queues to obtain integer post-decisions states.…”

“…Its main objectives are to achieve equitable access and treatment duration for patient groups, to serve the strategically agreed target number of patients (i.e., production targets or quota), to maximize resource utilization and to balance workload [261]. From a clinician's perspective, tactical resource and admission plans break the clinician's time down into separate activities (e.g., consultation time and surgical time) and determine the number of patients to serve from a particular patient group at a particular stage of their care process (e.g, consultation or surgery).…”

“…Several papers have focused on tactical planning problems that span multiple departments and resources in healthcare [192,286,374] and other industries [211]. In [261], the literature and various applications is reviews and it is concluded that existing approaches to develop tactical resource and admission plans in the OR/MS literature are myopic, focus on developing long-term cyclical plans, or are not able to provide a solution for real-life instances. The authors develop a deterministic method for tactical planning over multiple departments and resources within a mathematical programming framework.…”