TY - JOUR T1 - Modelling the allocation of paediatric intensive care retrieval teams in England and Wales JF - Archives of Disease in Childhood JO - Arch Dis Child DO - 10.1136/archdischild-2018-316056 SP - archdischild-2018-316056 AU - Madeline King AU - Padmanabhan Ramnarayan AU - Sarah E Seaton AU - Christina Pagel A2 - , Y1 - 2019/02/11 UR - http://adc.bmj.com/content/early/2019/02/11/archdischild-2018-316056.abstract N2 - 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. ER -