Operating Room Planning under Surgery Type and Priority Constraints

Abedini, Amin; Ye, Honghan; Li, Wei

doi:10.1016/j.promfg.2016.08.005

Cited by 24 publications

(16 citation statements)

References 16 publications

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“…As mentioned in the introduction, much research goes into developing and improving procedures and tools for prioritybased scheduling. [21][22][23][24][25][26][27] Such efforts can bring capacity loss towards zero, and as such towards -but never past -the capacity utilisation when giving each patient the first available appointment.…”

Section: Can Our Findings Be Generalised?mentioning

confidence: 99%

“…Waiting lists and waiting times are in this study evaluated based on data from one department only. Planning profiles 37 and waiting times 1 seem to differ between specialties, and as mentioned above, much research goes into developing and improving prioritisation based policies (example papers [21][22][23][24][25][26][27] ).…”

Section: Many Variations Of Prioritisationmentioning

confidence: 99%

“…The procedures used to order waiting lists based on priority are multifold. In recent years, much research has gone into developing and improving procedures and tools for such management (example papers from recent years [21][22][23][24][25][26][27] ). All such methods, no matter how sophisticated, have in common that criteria-based priorities help define delays in access to care.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Long Waiting Times for Elective Hospital Care – Breaking the Vicious Circle by Abandoning Prioritisation

Sæther

Heggestad

Heimdal

et al. 2019

Int J Health Policy Manag

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Background: Policies assigning low-priority patients treatment delays for care, in order to make room for patients of higher priority arriving later, are common in secondary healthcare services today. Alternatively, each new patient could be granted the first available appointment. We aimed to investigate whether prioritisation can be part of the reason why waiting times for care are often long, and to describe how departments can improve their waiting situation by changing away from prioritisation. Methods: We used patient flow data from 2015 at the Department of Otorhinolaryngology, Haukeland University Hospital, Norway. In Dynaplan Smia, Dynaplan AS, dynamic simulations were used to compare how waiting time, size and shape of the waiting list, and capacity utilisation developed with and without prioritisation. Simulations were started from the actual waiting list at the beginning of 2015, and from an empty waiting list (simulating a new department with no initial patient backlog). Results: From an empty waiting list and with capacity equal to demand, waiting times were built 7 times longer when prioritising than when not. Prioritisation also led to poor resource utilisation and short-lived effects of extra capacity. Departments where prioritisation is causing long waits can improve their situation by temporarily bringing capacity above demand and introducing "first come, first served" instead of prioritisation. Conclusion: A poor appointment allocation policy can build long waiting times, even when capacity is sufficient to meet demand. By bringing waiting times down and going away from prioritisation, the waiting list size and average waiting times at the studied department could be maintained almost 90% below the current level – without requiring permanent change in the capacity/demand ratio.

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Section: Can Our Findings Be Generalised?mentioning

confidence: 99%

Section: Many Variations Of Prioritisationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Long Waiting Times for Elective Hospital Care – Breaking the Vicious Circle by Abandoning Prioritisation

Sæther

Heggestad

Heimdal

et al. 2019

Int J Health Policy Manag

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“…Other relevant approaches are: Abedini et al 2016, that developed a bin packing model with a multistep approach and a priority-type-duration rule; Molina-Pariente et al 2015, that tackled the problem of assigning an intervention date and an OR to a set of surgeries on the waiting list, minimizing the access time for patients with diverse clinical priority values; and Zhang et al 2017, that addressed the problem of OR planning with different demands from both elective patients and nonelective ones, with priorities in accordance with urgency levels and waiting times. However, bed management is not considered in these three last mentioned approaches.…”

Section: Related Workmentioning

confidence: 99%

Operating Room (Re)Scheduling with Bed Management via ASP

Dodaro¹,

Galatà²,

Khan³

et al. 2021

Theory and Practice of Logic Programming

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The Operating Room Scheduling (ORS) problem is the task of assigning patients to operating rooms (ORs), taking into account different specialties, lengths, and priority scores of each planned surgery, OR session durations, and the availability of beds for the entire length of stay (LOS) both in the Intensive Care Unit (ICU) and in the wards. A proper solution to the ORS problem is of primary importance for the healthcare service quality and the satisfaction of patients in hospital environments. In this paper we first present a solution to the problem based on Answer Set Programming (ASP). The solution is tested on benchmarks with realistic sizes and parameters, on three scenarios for the target length on 5-day scheduling, common in small–medium-sized hospitals, and results show that ASP is a suitable solving methodology for the ORS problem in such setting. Then, we also performed a scalability analysis on the schedule length up to 15 days, which still shows the suitability of our solution also on longer plan horizons. Moreover, we also present an ASP solution for the rescheduling problem, that is, when the offline schedule cannot be completed for some reason. Finally, we introduce a web framework for managing ORS problems via ASP that allows a user to insert the main parameters of the problem, solve a specific instance, and show results graphically in real time.

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“…In this study, we propose an adaptation of the Positions and Covering (P&C) methodology, used by [ 10 ] to obtain optimal solutions for the two-dimensional bin packing problem. Considering the similarity of the 2SP with other packing problems, some potential applications for the P&C methodology can be found in agricultural fields to delineate rectangular and homogeneous management zones [ 11 – 13 ], in scheduling problems applied to environmental, automotive, ferry, and manufacturing industries to ensure maximum use of materials [ 14 – 16 ], in healthcare applied to operating rooms schedules [ 17 – 19 ], in cloud computing where a set of jobs must be processed on virtual machines of physical servers with the aim of improves the energy efficiency [ 20 – 22 ], and in optimal deliveries in e-commerce where the objective is optimizing the total number of containers to integrate into several delivery trips [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Exact solutions for the 2d-strip packing problem using the positions-and-covering methodology

Cid-García

Ríos-Solís

2021

PLoS ONE

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We use the Positions and Covering methodology to obtain exact solutions for the two-dimensional, non-guillotine restricted, strip packing problem. In this classical NP-hard problem, a given set of rectangular items has to be packed into a strip of fixed weight and infinite height. The objective consists in determining the minimum height of the strip. The Positions and Covering methodology is based on a two-stage procedure. First, it is generated, in a pseudo-polynomial way, a set of valid positions in which an item can be packed into the strip. Then, by using a set-covering formulation, the best configuration of items into the strip is selected. Based on the literature benchmark, experimental results validate the quality of the solutions and method’s effectiveness for small and medium-size instances. To the best of our knowledge, this is the first approach that generates optimal solutions for some literature instances for which the optimal solution was unknown before this study.

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Operating Room Planning under Surgery Type and Priority Constraints

Cited by 24 publications

References 16 publications

Long Waiting Times for Elective Hospital Care – Breaking the Vicious Circle by Abandoning Prioritisation

Long Waiting Times for Elective Hospital Care – Breaking the Vicious Circle by Abandoning Prioritisation

Operating Room (Re)Scheduling with Bed Management via ASP

Exact solutions for the 2d-strip packing problem using the positions-and-covering methodology

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