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Warning signals and transition points across the whole system

Warning signals and transition points across the whole system. Dr Dan Beckett Consultant Acute Physician NHS Forth Valley. Overview. Warning signals Four hour emergency access standard ED LoS - time profiles Boarding (Cancelled elective activity) (Delayed discharges)

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Warning signals and transition points across the whole system

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  1. Warning signals and transition points across the whole system Dr Dan Beckett Consultant Acute Physician NHS Forth Valley

  2. Overview • Warning signals • Four hour emergency access standard • ED LoS - time profiles • Boarding • (Cancelled elective activity) • (Delayed discharges) • Whole system overview • NHSFV capacity and flow dashboard • Elective vs Emergency imbalance • Optimising patient flow by reducing its variability

  3. Warning signals • Four hour emergency access standard • Useful as an indicator of whole system pressure • Poor compliance indicates with ED overcrowding • Associated with an increase in mortality both in patients admitted and patients discharged from the ED • Limited usefulness as an early indicator of pressure to trigger escalation

  4. Warning signals • ED LoS distribution • Can demonstrate pressure in the system that is not evident when just looking at compliance with the four hour emergency access standard • ‘Crisis spike’

  5. Warning signals • ED time curve • Useful for retrospective analysis • Crisis spike correlates with poor performance • Useful for proactive escalation? • Dynamic monitoring of the proportion of patients leaving the ED after 210 minutes?

  6. BUT STILL 97% COMPLIANT AT THIS STAGE 27%

  7. 91% 86%

  8. 79% 77%

  9. Warning signals • Boarders • Different models of boarding exist • Exclusively ‘front door’ • Exclusively ‘back door’ • Mixed model • Irrespective of model, increasing numbers of boarders indicates system pressure and should be monitored/controlled • Boarded patients have poor outcomes

  10. Monitoring whole system pressure • NHSFV capacity dashboard • Real time information • Pressure vs Capacity • Admissions vs Discharges • Emergency vs Elective • Predicted vs Observed activity • Whole system vs Individual patient • Warning signals across the whole system as a trigger to escalation

  11. Elective vs Emergency flow • Competition between emergency and elective flow ‘silos’ can directly lead to ED overcrowding • Perceived conflict between the 18 week RTT target and the 4 hour emergency access standard • Significant variation in numbers of patients admitted over the week

  12. 131%

  13. 54%

  14. 131% BUT YOU CAN’T COMPARE WEEKENDS AND WEEKDAYS! 54% 3288%

  15. 46% 16% 237%

  16. Elective vs Emergency flow • Elective admissions display more variability (artificial variability) than emergency admissions (natural variability) • Counter-intuitive!

  17. Elective vs Emergency Flow Imbalance • Difficult to plan staffing levels for such high levels of variation (largely artificial variation) • Invariably staffed for ‘average’ levels of activity resulting in periods of demand > capacity (leading to ED overcrowding and poor outcomes) and capacity > demand (waste of resources)

  18. Queue Capacity Demand time Average demand = Average capacity Variation mismatch = queue Can’t pass unused capacity forward to next week Reducing waiting times in the NHS: is lack of capacity the problem? Bevan et al Clinician in Management (2004) 12:

  19. Elective vs Emergency Flow • Need to eliminate artificial variation and manage natural variation

  20. 14%

  21. Eliminating artificial variation • Reduces overall variation • Reduces ED overcrowding • Less waste • Reduces patient boarding • In 2006 the IOM published a report asking hospitals to use operational management tools (queuing theory) to address patient flow issues that lead to ED overcrowding

  22. Operational management of flow • Boston Medical Centre • Significant problems with ED overcrowding 2003 • Emergency work more predictable and less varied than elective work • Reprofiled elective cases Monday-Friday • Subsequently eliminated all block scheduling • Split elective and emergency surgical work • Used queuing theory to guide resources for emergency work

  23. Operational management of flow • Boston Medical Centre • Reduced variability in demand for surgical HDU beds by 55% • Reduced nursing hours – saving $130K per annum • Reduced cancelled/delayed surgery from 334 to 3 (99.5%) for the same time periods April-September 2003/2004 (pre- and post-implementation) • Reduced ED waiting time by 50% and improved ED throughput by 45 minutes per patient

  24. Operational management of flow • Now many examples of successful implementation • Cincinatti Childrens Hospital • Weekday OR waiting time reduced by 28% (despite an increase in case volume of 24%) • Weekend OR waiting time decreased by 34% despite an increase in volume of 37%) • Capacity boosted by equivalent of 100 bed expansion • Great Ormond Street Hospital

  25. Operational management of flow • Assign responsibility for the patient flow problem • Chief Operations Officer or Vice President • Establish a multidisciplinary team • Collect and analyze data on bottlenecks • Eliminate or smooth artificial variation • Manage natural variation (queuing theory) • www.ihoptimize.org

  26. References • Managing Capacity and Demand across the patient journey. Clinical Medicine 2010. 10:1 13-15 • Winter Pressures in NHS Scotland 2008-2009. A report for the Emergency Access Team, Scottish Government

  27. Acknowledgements • Professor Derek Bell, Imperial College • Professor Eugene Litvak, Institute for Healthcare Optimisation • Dr Claire Gordon, NHS Lothian • Bas Gough, Scottish Government • Guy Blackburn, NHSFV • Thanks for listening...

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