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Related Experiment Videos

Are EMS call volume predictions based on demand pattern analysis accurate?

Lawrence H Brown1, E Brooke Lerner, Baxter Larmon

  • 1Department of Emergency Medicine, SUNY Upstate Medical University, Syracuse, NY, USA.

Prehospital Emergency Care
|April 25, 2007
PubMed
Summary
This summary is machine-generated.

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Demand pattern analysis accurately predicts ambulance call volume trends but often overestimates exact numbers. EMS systems should assess if the 4-7% underestimation rate is acceptable for resource allocation.

Area of Science:

  • Emergency Medical Services (EMS)
  • Operations Research
  • Healthcare Management

Background:

  • EMS systems rely on accurate call volume predictions for crew deployment and scheduling.
  • Demand pattern analysis, using historical data, is a common method for predicting future call volumes.

Purpose of the Study:

  • To evaluate the predictive accuracy of demand pattern analysis for EMS call volumes.
  • To compare the performance of three common demand pattern analysis constructs: average peak demand (AP), smoothed average peak demand (SAP), and 90th percentile rank (90%R).

Main Methods:

  • Seven EMS systems provided 73 weeks of hourly call volume data.
  • Three demand pattern analysis constructs (AP, SAP, 90%R) were calculated using the first 20 weeks of data.
  • Actual call volumes over the subsequent 52 weeks were compared to predictions using descriptive statistics.

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Main Results:

  • All three constructs accurately predicted call volume peaks and troughs but not exact volumes.
  • Predictions were accurate to within +/-1 call only 10-19% of the time.
  • Call volumes were overestimated 74-86% of the time, by a median of 3-4 calls.
  • Underestimation occurred 4-7% of the time, with a median excess of 1-2 calls.

Conclusions:

  • Demand pattern analysis is a reasonable predictor for ambulance staffing, generally estimating or overestimating call volumes.
  • EMS systems must consider the implications of 4-7% underestimation when allocating resources.
  • The accuracy of these prediction methods did not vary significantly between the participating EMS systems.