Background Information regarding waiting times has been shown to be a key determinant of patient satisfaction. This study aimed to examine the potential accuracy of predicted waiting times determined on the patient's arrival in the Emergency Department (ED).
Methods A retrospective study of 50 000 consecutive patients attending a single ED was undertaken. A linear regression model was developed to predict waiting times, assessing a number of different measures derived from the waiting times of patients seen immediately prior to an individual patient's time of arrival. To assess the fit of the model, the mean absolute difference between the patient's actual and predicted waiting times was determined.
Results 6726 patients had incomplete data and were excluded from the analysis. The mean waiting time across all streams was 64.6 (SD 43.7) min. The best performing linear regression model used two variables to predict a patient's waiting time, calculated across the entire sample of patients. This model predicted 27% of the variability in waiting time. The mean absolute difference between actual and predicted waiting times across all streams was 29.0 (SD 23.5) min. The mean absolute difference in waiting times was similar across the streams.
Conclusions There is a considerable difference between predicted and actual waiting times using this method. Further investigation is required to determine whether such a degree of inaccuracy is acceptable to patients and improves satisfaction more than the provision of no information regarding waiting times.
- Emergency care systems
- emergency departments
- emergency department management
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Competing interests Barnsley Hospital NHS Foundation Trusts is currently in negotiations with Extramed to license to them a piece of software developed in the Trust. Thomas Locker was involved in the development of this software. Extramed had no part in the decision to undertake the study, the analysis or the decision to publish the results.
Provenance and peer review Not commissioned; externally peer reviewed.
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