1 / 21

Optimizing Ambulance Response Times in Dynamic Management Systems

This study focuses on enhancing ambulance response times through a dynamic management model. By analyzing various phases in the ambulance lifecycle and integrating actions based on real-time scenarios, the model aims to minimize the average response time and cost associated with waiting patients. Key elements include the dispatch of the nearest ambulance, consideration of all potential scenarios, and an evaluation of service time and destinations. The findings leverage historical data to improve efficiency in emergency service operations, benefiting both hospitals and patients.

efrem
Télécharger la présentation

Optimizing Ambulance Response Times in Dynamic Management Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Minimizing Average Response Times in a Dynamic Ambulance Management Model Thije van Barneveld, CWI, Amsterdam

  2. Region • Equidistant graph • Blue: Demand locations • Yellow: Hospitals • Red: Additional nodes

  3. Ambulance Phases

  4. “Life Cycle” of a Request

  5. State components

  6. State components • Elapsed service time of ambulances in phase 4 • Destinations and remaining driving times of phase 3 ambulances

  7. Actions • Dispatch nearest ambulance • Change in ambulance configuration

  8. Objective • Cost in a state: number of patients waiting • Minimize costs: minimize the average number of patients waiting • Minimize the average response time Cost 0 Cost 1 Cost 0

  9. Heuristic Solution - Idea • Observe state • Consider all actions • Consider possible scenarios • Combine each action with each scenario • Classify each action and optimize

  10. Scenarios • Possible next state • One new request • Ambulances that finish service

  11. Scenarios • Possible next state • One new request • Ambulances that finish service

  12. Scenarios • Possible next state • One new request • Ambulances that finish service

  13. Scenarios • Possible next state • One new request • Ambulances that finish service

  14. Scenarios • Possible next state • One new request • Ambulances that finish service

  15. Eligible ambulances Eligibleforrespondingto new request: • Nearestidleunassigned ambulance • Nearest busy ambulance at hospital • Nearest busy ambulance on scene, notrequiredto transport Expectedshortest response time

  16. Example Classify action: • Scenario probabilityExpectedshortest response time torequest • Sum over scenarios • Take best classified action

  17. Results • ’s estimatedusinghistorical data • No hospitals • 4 ambulances

  18. Results

  19. Results • ’s as before • 2 hospitals: • 6 ambulances

  20. Results

  21. Questions?

More Related