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Modelling the allocation of paediatric intensive care retrieval teams in England and Wales
  1. Madeline King1,2,
  2. Padmanabhan Ramnarayan3,
  3. Sarah E Seaton4,
  4. Christina Pagel2
  5. on behalf of the DEPICT Study Group
    1. 1Washington University, St Louis, Missouri, USA
    2. 2Clinical Operational Research Unit, University College of London, London, UK
    3. 3Children’s Acute Transport Service, London, UK
    4. 4Health Sciences, University of Leicester, Leicester, UK
    1. Correspondence to Professor Christina Pagel, Paediatric Intensive Care Unit, Great Ormond Street Hospital NHS Foundation Trust, London, UK; c.pagel{at}ucl.ac.uk

    Abstract

    Background Following centralisation of UK paediatric intensive care units in 1997, specialist paediatric intensive care retrieval teams (PICRTs) were established to transport critically ill children from district general hospitals (DGHs). The current location and catchment area of PICRTs covering England and Wales are based on historical referral patterns. National quality standards specify that PICRTs should reach the patient bedside within 3 hours of accepting a referral.

    Objective To determine what proportion of demand for PICRT services in England and Wales can be reached within 3 hours and to explore the potential coverage impact of more stringent ‘time to bedside’ standards.

    Methods We used mathematical location–allocation methods to: (1) determine the optimal allocation of DGHs to current PICRT locations to minimise road journey time and calculated the proportion of demand reachable within 3 hours, 2 hours, 90 min, 75 min and 1 hour and (2) explore the impact of changing the number and location of PICRTs on demand coverage for the different time thresholds.

    Results For current (and optimal) location of 11 PICRTs, 98% (98%) of demand is reachable within 3 hours; 86% (91%) within 2 hours; 59% (69%) within 90 min; 33% (39%) within 75 min; and 20% (20%) within 1 hour. Five hospitals were not reachable within 3 hours. For the 3-hour standard, eight optimally located PICRT locations had similar coverage as the current 11 locations.

    Conclusions If new evidence supports reduction in the time to bedside standard, many more hospitals will not be adequately covered. Location–allocation optimisation is a powerful technique for supporting evidence-based service configuration.

    • Intensive Care
    • Mathematical Modelling
    • System Configuration

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    Footnotes

    • Contributors CP and PR conceived of the study, and CP supervised MK. SES analysed historic demand and provided the list (and postcodes) of hospitals in England and Wales. MK carried out the mathematical modelling and wrote the first draft of the paper. All authors read and commented on drafts of the paper and approved the final version.

    • Funding The DEPICT project is funded by the National Institute for Health Research Health Services and Delivery Research programme (Project No: 15/136/45).

    • Disclaimer The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the NIHR HS&DR programme or the Department of Health.

    • Competing interests None declared.

    • Patient consent Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement Data of historic demand belong to PICANet and are not available. Data of the journey times between hospitals are available as an Excel spreadsheet on request from the corresponding author.

    • Collaborators Elizabeth Draper; Jo Wray; Steve Morris; Patrick Davies; Will Marriage; Fatemah Rajah; Eithne Polke; Paul Mouncey; Anna Pearce; Matthew Entwistle; Rachel Lundy.

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