UCL  IRIS
Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
A mathematical modelling approach for systems where the servers are almost always busy.
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Journal Article
  • Authors:
    Pagel C, Richards DA, Utley M
  • Publication date:
    2012
  • Pagination:
    290360, ?
  • Journal:
    Comput Math Methods Med
  • Volume:
    2012
  • Status:
    Published
  • Country:
    United States
  • Language:
    eng
  • Keywords:
    Humans, Mathematical Concepts, Mental Health Services, Models, Statistical, Systems Theory, Time Factors, Waiting Lists
Abstract
The design and implementation of new configurations of mental health services to meet local needs is a challenging problem. In the UK, services for common mental health disorders such as anxiety and depression are an example of a system running near or at capacity, in that it is extremely rare for the queue size for any given mode of treatment to fall to zero. In this paper we describe a mathematical model that can be applied in such circumstances. The model provides a simple way of estimating the mean and variance of the number of patients that would be treated within a given period of time given a particular configuration of services as defined by the number of appointments allocated to different modes of treatment and the referral patterns to and between different modes of treatment. The model has been used by service planners to explore the impact of different options on throughput, clinical outcomes, queue sizes, and waiting times. We also discuss the potential for using the model in conjunction with optimisation techniques to inform service design and its applicability to other contexts.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Author
Clinical Operational Research Unit
Author
Clinical Operational Research Unit
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by