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Describing and predicting frequent callers to an ambulance service: analysis of 1 year call data
  1. Jason Scott1,
  2. Annette Patricia Strickland2,
  3. Karen Warner2,
  4. Pamela Dawson1
  1. 1Faculty of Health & Life Sciences, York St. John University, York, UK
  2. 2Yorkshire Ambulance Service NHS Trust, Wakefield, UK
  1. Correspondence to Dr Jason Scott, Faculty of Health & Life Sciences, York St. John University, Room 311, De Grey Court, Lord Mayor's Walk, York YO31 7EX, UK; j.scott{at}yorksj.ac.uk

Abstract

Aims Ambulance services in England receive around 8 million calls a year, and no known studies have explored characteristics of frequent callers. This study aimed to identify the characteristics of the most frequent callers to Yorkshire Ambulance Service (YAS) between April 2010 and March 2011.

Methods Top 100 frequent callers to YAS were analysed using population comparison, case control and multiple regression methods. 7808 calls were made by the frequent callers, and data were analysed to predict total number of calls made, and explore characteristics of frequent callers.

Results Six call codes were associated with a higher number of calls. Frequent callers were assigned slower response levels, or often no call code. Calls increased during the times of 4:00–9:00, 16:00–20:00 and 22:00–2:00, and in the months of December, January and February. Men and patients with all but the very highest conveyance rates had a higher number of different reasons for calling. Patients with a medical diagnosis were more likely to be conveyed, while patients with a psychiatric classification had a higher number of different reasons for calling, were older and were more likely to call for ‘assault/sexual assault’ or ‘haemorrhage/laceration’.

Conclusions Frequent callers to YAS were a heterogeneous group that differed from the overall population served, resulting in numerous implications for the delivery of services for this group of patients. Further research is required to determine if and how frequent callers differ from frequent attenders at emergency departments.

  • emergency ambulance systems
  • prehospital care
  • statistics

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