Admission and capacity planning for the implementation of one-stop-shop in skin cancer treatment using simulation-based optimization

Abstract

Hospitals and health care institutions are facing the challenge of improving the quality of their services while reducing their costs. The current study presents the application of operations management practices in a dermatology oncology outpatient clinic specialized in skin cancer treatment. An interesting alternative considered by the clinic is the implementation of a one-stop-shop concept for the treatment of new patients diagnosed with basal cell carcinoma. This alternative proposes a significant improvement in the average waiting time that a patient spends between the diagnosis and treatment. This study is focused on the identification of factors that influence the average throughput time of patients treated in the clinic from the logistic perspective. A two-phase approach was followed to achieve the goals stated in this study. The first phase included an integrated approach for the deterministic analysis of the capacity using a demand-supply model for the hospital processes, while the second phase involved the development of a simulation model to include variability to the activities involved in the process and to evaluate different scenarios. Results showed that by managing three factors: the admission rule, resources allocation and capacity planning in the dermato-oncology unit throughput times for treatments of new patients can be decreased with more than 90 %, even with the same resource level. Finally, a pilot study with 16 patients was also conducted to evaluate the impact of implementing the one stop shop concept from a clinical perspective. Patients turned out to be satisfied with the fast diagnosis and treatment.

How do the characteristics of breast cancer diagnostic assessment programmes influence service delivery: A mixed methods study

“…Operations management principles have been used to simulate a demand–supply model for a one‐stop skin cancer clinic and found that by managing triage criteria, resource allocation and capacity planning, the time to treatment of new patients could be reduced by 90% with the same resources (Romero et al., 2013). While modelling may be a useful first step in identifying alternative DAP designs, real‐world studies are needed to pilot the feasibility and impact of various DAP models.…”

Stochastic integer programming for multi-disciplinary outpatient clinic planning

“…Multiple authors consider the planning of flow-shop type multi-disciplinary systems, for example in oncology [23,40] and primary care practices [30]. Liang et al [23] analyze the impact of scheduling methods on the oncology clinic performance, where patients visit an oncologist and a nurse for chemotherapy treatment.…”

“…They included the effects of uncertainty in service time, but fixed the patient routing requirements. Romero et al [40] use simulation to evaluate different appointment scenarios in which appointment blocks are reserved for multi-disciplinary patients. This way, they prove the feasibility of a one-stop-shop for basal cell carcinoma.…”

“…Multi-disciplinary teams are increasingly being introduced in various medical contexts, such as in outpatient clinics and operating rooms [24,29], and in various medical disciplines, such as cancer care, rehabilitation, and neurology [15,40,47,48]. However, the coordination and control of these teams is complex, as multiple clinicians from multiple departments are involved.…”

Use of simulation to solve outpatient clinic problems: A review of the literature

“…Romero et al [73] used simulation to evaluate the implementation of a one-stop-shop in a skin cancer treatment outpatient clinic. Different scenarios of new services were analysed in the simulation model; in the best case scenario, a more than 90 per cent reduction in new patient throughput times for treatments was achievable, even at the same resource level.…”