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Hospital Bed Simulation for Driving Best Practice

This simulation tool aims to improve hospital bed occupancy, wait times, and discharge processes through scenario testing using default and uploaded data. It allows users to assess impacts of various improvement scenarios and optimize bed management strategies. The model includes parameters for admissions, length of stay, discharge profiles, and bed utilization. Users can explore scenarios like earlier GP referrals and reducing length of stay for elderly patients to determine the most impactful changes. The tool also addresses complexities of 7-day working schedules and their impact on capacity and discharge patterns. Currently being tested for usability and will be presented at a 7-Day Working event for further feedback and dissemination. Future plans include informing national emergency care debates, collaborating with hospitals, and aligning with research interests.

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Hospital Bed Simulation for Driving Best Practice

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  1. Acute Bed Simulation Russell Emeny, Fiona Lindsay, Claire Cordeaux Thanks to Terry Young, Sally Brailsford and Joe Viana

  2. Our Aim - Driving Best Practice • Key improvement messages • Demonstrated using simulation • Uses default data for immediate testing • Local hospital data can be uploaded

  3. Answering Questions • What is my bed occupancy %? • How many beds am I using? • What are my wait times for beds? • How do improvement scenarios impact on these results?

  4. Simulation Model

  5. Parameter 1 - Admissions

  6. Parameter 2 – Length of Stay Number of midnight stays by hour and day of the week

  7. Parameter 3 – Discharge profile

  8. Parameter 4 - Beds

  9. Improvement Scenario 1 What if GP referrals arrived earlier in the day?

  10. Improvement Scenario 2 What if our ambulatory care patients were treated elsewhere? • Select a percentage of admissions classed as “ambulatory” (default 25%) • Select likely impact on number of midnight stays

  11. Improvement Scenario 3 Patients who stay for less than 2 midnights • Research suggests 65% of patients

  12. Improvement Scenario 4 Move patient discharges forward to earlier in the day

  13. Improvement Scenario 5 Reduce 14 night length of stay for over 75s

  14. Which scenario has the most impact? • GP referrals earlier? • Ambulatory care treated elsewhere? (25% of admissions) • Increase proportion of stays that are less than 2 midnights? • Move 50% of discharges earlier in the day? • Reduce 14 night stays for over 75s? (25% of admissions)

  15. Results are in… Which would you implement first?

  16. 7 Day Working – Current Question • How to model this? • Staff available 7 days a week to make discharge decisions • Use a Monday profile (furthest from the weekend) • What would you expect to see?

  17. 7 Day Working – Current Question Actually increases capacity required

  18. Why? Looking at 0-7 midnight stays – around 75% of admissions

  19. Impact of the weekend Number of midnight stays appear to be driven by a push to discharge on Friday

  20. 7 day compared to Monday profile • Patients are more likely to be discharged at the weekend • Have a longer length of stay during the week

  21. What next? • Currently being tested with 3 hospitals for usability • Presenting a poster at 7 Day Working event November 16th

  22. Continuing the Work • More questions emerging • Informing national debate on emergency care and 7 day working • Disseminate to hospitals • Seeking support • Link with research interests?

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