Developing bed managers: the why and the how

Proudlove, Nathan; Boaden, Ruth; Jorgensen, Julie

doi:10.1111/j.1365-2934.2006.00632.x

Cited by 45 publications

(33 citation statements)

References 9 publications

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“…A dedicated RN bed planner, as well as the implementation of a bed management database and streamlined ED-ICU communication lowered one hospital's diversion hours by 63% (Hemphill and Nole, 2005). Deeper analysis into the use of a bed manager shows great potential, and the investment of resources into training staff for such a task may be a wise decision (Proudlove et al, 2003(Proudlove et al, , ,2007.…”

Section: Bed Planningmentioning

confidence: 98%

Operations research/management contributions to emergency department patient flow optimization: Review and research prospects

Saghafian

Austin

Traub

2015

IIE Transactions on Healthcare Systems Engineering

122

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In recent years, Operations Research/Management (OR/OM) has had a significant impact on improving the performance of hospital Emergency Departments (EDs). This includes improving a wide range of processes involving patient flow from the initial call to the ED through disposition, discharge home, or admission to the hospital. We review approximately 350 related papers to (i) demonstrate the influence of OR/OM in EDs, and (ii) assist both researchers and practitioners with the OR/OM techniques already available to optimize ED patient flow. In addition, we elaborate on some practical challenges yet to be addressed. By shedding light on some less studied aspects that can have significant impacts on ED operations, we also discuss important possibilities for future OR/OM researchers.

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Section: Bed Planningmentioning

confidence: 98%

Operations research/management contributions to emergency department patient flow optimization: Review and research prospects

Saghafian

Austin

Traub

2015

IIE Transactions on Healthcare Systems Engineering

122

View full text Add to dashboard Cite

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“…The bed manager is typically a member of the medical staff (nurse or shift manager), and his or her function may be particularly stressful and managerially complex. Nathan et al [18] developed a training program for bed managers that improved participants' knowledge, skills and subsequent behaviors. In a recent paper, Landa et al [19] built a discrete-event simulation that constituted a decision support framework to assist in determining how different bed management rules directly or indirectly affect system performance, thus enabling managers to improve the patient flow between the ED and the departments.…”

Section: Introductionmentioning

confidence: 99%

An alternative scheduling approach for improving patient-flow in emergency departments

Elalouf

Wachtel

2015

Operations Research for Health Care

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“…The challenges of bed management without computer assistance leading to special training programs for the persons in charge have been analyzed intensively by Proudlove et al [10,11]. Bed management has to solve optimization problems in a context with a high level of uncertainty: the outcome of a treatment cannot be predicted fully, and emergency patients need to be treated immediately.…”

Section: Introductionmentioning

confidence: 99%

Decision support for hospital bed management using adaptable individual length of stay estimations and shared resources

Schmidt

Geisler

Spreckelsen

2013

BMC Med Inform Decis Mak

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BackgroundElective patient admission and assignment planning is an important task of the strategic and operational management of a hospital and early on became a central topic of clinical operations research. The management of hospital beds is an important subtask. Various approaches have been proposed, involving the computation of efficient assignments with regard to the patients’ condition, the necessity of the treatment, and the patients’ preferences. However, these approaches are mostly based on static, unadaptable estimates of the length of stay and, thus, do not take into account the uncertainty of the patient’s recovery. Furthermore, the effect of aggregated bed capacities have not been investigated in this context. Computer supported bed management, combining an adaptable length of stay estimation with the treatment of shared resources (aggregated bed capacities) has not yet been sufficiently investigated. The aim of our work is: 1) to define a cost function for patient admission taking into account adaptable length of stay estimations and aggregated resources, 2) to define a mathematical program formally modeling the assignment problem and an architecture for decision support, 3) to investigate four algorithmic methodologies addressing the assignment problem and one base-line approach, and 4) to evaluate these methodologies w.r.t. cost outcome, performance, and dismissal ratio.MethodsThe expected free ward capacity is calculated based on individual length of stay estimates, introducing Bernoulli distributed random variables for the ward occupation states and approximating the probability densities. The assignment problem is represented as a binary integer program. Four strategies for solving the problem are applied and compared: an exact approach, using the mixed integer programming solver SCIP; and three heuristic strategies, namely the longest expected processing time, the shortest expected processing time, and random choice. A baseline approach serves to compare these optimization strategies with a simple model of the status quo. All the approaches are evaluated by a realistic discrete event simulation: the outcomes are the ratio of successful assignments and dismissals, the computation time, and the model’s cost factors.ResultsA discrete event simulation of 226,000 cases shows a reduction of the dismissal rate compared to the baseline by more than 30 percentage points (from a mean dismissal ratio of 74.7% to 40.06% comparing the status quo with the optimization strategies). Each of the optimization strategies leads to an improved assignment. The exact approach has only a marginal advantage over the heuristic strategies in the model’s cost factors (≤3%). Moreover,this marginal advantage was only achieved at the price of a computational time fifty times that of the heuristic models (an average computing time of 141 s using the exact method, vs. 2.6 s for the heuristic strategy).ConclusionsIn terms of its performance and the quality of its solution, the heuristic strategy RAND is the preferred method fo...

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Developing bed managers: the why and the how

Cited by 45 publications

References 9 publications

Operations research/management contributions to emergency department patient flow optimization: Review and research prospects

Operations research/management contributions to emergency department patient flow optimization: Review and research prospects

An alternative scheduling approach for improving patient-flow in emergency departments

Decision support for hospital bed management using adaptable individual length of stay estimations and shared resources

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