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P045 Aggregated patient journeys and no-show rates of oximetry outreach network in east anglia
  1. Kieran Lee1,
  2. Natalia Andrienko2,
  3. Gennady Andrienko2,
  4. Ibad Kureshi3,
  5. Toni Staykova4 and
  6. Ian Smith1
  1. 1Royal Papworth Hospital, Cambridge, UK
  2. 2Fraunhofer Institute, Sankt Augustin, Germany
  3. 3Inlecom Systems, Brussels, Belgium
  4. 4Cambridge Medical Academy, Cambridge, UK


Introduction Royal Papworth Hospital performs >10,000 home oximetry tests p.a. across a large area with challenging road-infrastructure. We have developed a distributed system of oximetry exchange facilities (EF’s) at outreach-clinics and GP surgeries over several years without a ‘masterplan’. As part of the Track and Know project (EU2020) we examined relationships between the distribution of patients and EF’s and no-shows.

Method Data for 5 years’ (2013–2018) of oximetry tests with patient addresses and clinic outcomes were used to reconstruct likely journeys applying a bespoke tessellation algorithm, dividing the territory into polygons enclosing clusters of patients‘ homes and at most one EF. For each pair of compartments (P&Q), we computed the number of appointments for patients in P to the clinic in Q and the% of no-shows. These were mapped (see figure 1). Data were collected for patient demographics and the travel information was enriched with weather conditions on the appointment day.

Results Data from 46,211 planned pick up’s were examined. There was a high no-show rate (15.8%) and an uneven distribution of journeys to each pick-up site. Despite the network containing 21 sites >50% of pick-ups were scheduled for the hospital. No show rates were not related to travel distance and were more likely in good weather than bad. We have recalculated that the service could be better provided from 10 EF’s.

Discussion We have re-evaluated our service using complex patient flow metrics and the results have confounded some predictions. Distance alone does not predict no-show rate and we plan to explore the impact of public transport and more sophisticated patient based factors. We plan to redesign the EF distribution network in line with our outcomes with the goal of maximising efficiency and will revisit whether we can improve accessibility and reduce our no-show rate while reducing clinic overheads.

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