Optimising resource management in neurorehabilitation.

BACKGROUND: To date, little research has been published regarding the effective and efficient management of resources (beds and staff) in neurorehabilitation, despite being an expensive service in limited supply. OBJECTIVE: To demonstrate how mathematical modelling can be used to optimise service de...

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Published in:NeuroRehabilitation Vol. 35; no. 2; pp. 171 - 180
Main Authors: Wood, Richard M., Griffiths, Jeff D., Williams, Janet E., Brouwers, Jakko
Format: pictorial research tables/charts Journal Article
Published: Sage Publications Inc. 2014
Online Access:View this record in EBSCOhost
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        atl: Optimising resource management in neurorehabilitation.
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        au:
          Wood, Richard M.
          Griffiths, Jeff D.
          Williams, Janet E.
          Brouwers, Jakko
        affil: School of Mathematics, Cardiff University, Cardiff, UK
      sug:
        subj:
          Rehabilitation
          Nervous System Diseases
          Health Resource Utilization
          Computer Simulation
          Models, Statistical
          Personnel Staffing and Scheduling
          Appointment and Scheduling Information Systems
          Multidisciplinary Care Team
      ab: BACKGROUND: To date, little research has been published regarding the effective and efficient management of resources (beds and staff) in neurorehabilitation, despite being an expensive service in limited supply. OBJECTIVE: To demonstrate how mathematical modelling can be used to optimise service delivery, by way of a case study at a major 21 bed neurorehabilitation unit in the UK. METHODS: An automated computer program for assigning weekly treatment sessions is developed. Queue modelling is used to construct a mathematical model of the hospital in terms of referral submissions to a waiting list, admission and treatment, and ultimately discharge. This is used to analyse the impact of hypothetical strategic decisions on a variety of performance measures and costs. The project culminates in a hybridised model of these two approaches, since a relationship is found between the number of therapy hours received each week (scheduling output) and length of stay (queuing model input). RESULTS: The introduction of the treatment scheduling program has substantially improved timetable quality (meaning a better and fairer service to patients) and has reduced employee time expended in its creation by approximately six hours each week (freeing up time for clinical work). The queuing model has been used to assess the effect of potential strategies, such as increasing the number of beds or employing more therapists. CONCLUSIONS: The use of mathematical modelling has not only optimised resources in the short term, but has allowed the optimality of longer term strategic decisions to be assessed.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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