Gary Thompson Policy Lead for Emergency Care Trent Strategic Health Authority

1. Unscheduled Care Collaborative Programme27th January 2006Understanding Demand & Planning Appropriate Capacity Gary Thompson Policy Lead for Emergency Care Trent Strategic Health Authority

2. Why do queues form? • because demand exceeds capacity? • mismatch between demand & capacity? • Do we want queues to keep us busy - utilised?

3. Mismatch between demand and capacity • Variation in demand + variation in capacity = queue • Occasionally demand > capacity

4. Queue Demand Capacity time Variation mismatch = queue Can’t pass unused capacity forward to next week

5. Demand Waste More Capacity Capacity time How do we work out required capacity?

6. 2. Setaverage capacityat80% of variation in demand 1. Why iscapacity varying? Queue Queue Capacity Capacity Demand Demand time time Lean Thinking I

7. 4. Reduce variation in demand 3. Why isdemand varying? Queue Queue Capacity Capacity Demand Demand time time Lean Thinking II

8. Manage constraints • Manage and match variability • Reduce variation in capacity • reduce carve outs • (demand) • Increase capacity • redesign (releasing resources) • actual increase • Reduce demand ? • reduce variation in demand • agree thresholds and protocols

9. Are you a Purist or a Pragmatist?

10. As a pragmatist, it’s most useful to think of Beds as our capacity

11. A Trust Near You ? “It’s chaos now ! 15 DTA’s in A&E & no free beds - we need to get the wards to discharge ASAP” Bed Occupancy “I think we have it all under control now -lets hope next week is better” “We need more beds” “20 free beds this morning but lots of electives TCI” “Just about got them all in by the end of the day - well done!” 800 780 760 740 720 Beds Occupied 700 680 660 640 620 600 Mo Mo Mo Mo Tu Tu Tu Tu We We We We Th Th Th Th Fr 0 Fr 6 Fr Fr Sa Sa Sa Sa Su Su Su Su 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 12 18 0 6 12 18 0 6 12 18 Day/hour Of Week occupied beds estimated beds available

12. Demand v Capacity

16. For this trust Monday was a bad day: they ran out of beds before lunchtime Bed occupancy reached 100% in the middle of Monday

17. With hourly information on arrival and discharges, we can see why Arrivals and discharges by hour: Monday only Elective admissions and discharges are poorly co-ordinated with arrivals starting early morning and discharges not peaking until mid afternoon. 30 25 20 number of arrivals or discharges per hour 15 10 5 0 Mo 0 Mo 6 Mo 12 Mo 18 24 hour of week Emer Adm A&E Emer Adm direct Elec Adm Disch

18. We can use the hourly information to calculate the change in the number of occupied beds across the day This trust needs about 35 more beds at midday than it did at midnight

19. Variation in Discharge - By time of day - By day of week - Seasonal variations Variation in patient pathways and processes. E.g. in Length of Stay Variation in Admission Patterns - particularly for Elective Care Bed Availability: A problem of variation ADMISSION IN-PATIENT STAY DISCHARGE

20. Variation in Discharge - By time of day - By day of week - Seasonal variations Variation in Admission Patterns - particularly for Elective Care “We always bring our hips in on Tuesday !” ADMISSION IN-PATIENT STAY DISCHARGE Variation in patient pathways and processes. E.g. in Length of Stay

21. Variation in Discharge - By time of day - By day of week - Seasonal variations Variation in patient pathways and processes. Variation in Length of Stay Variation in Admission Patterns - particularly for Elective Care “Mr Smith’s TURP patients always stay five days but Mr Jones only keeps them in for three days ADMISSION IN-PATIENT STAY DISCHARGE

22. Variation in Discharge - By time of day - By day of week - Seasonal variations Variation in patient pathways and processes. E.g. in Length of Stay Variation in Admission Patterns - particularly for Elective Care “We’re too busy in the morning and haven’t time to think about discharges. They all get done in the afternoon. ADMISSION IN-PATIENT STAY DISCHARGE

23. Where do you start? Where there is greatest variation

24. In patient variation Usually indicated by Length of stay (LOS)

25. Total Admissions & Discharges May 2002 - December 2002 120 Admission Discharges 100 80 60 40 20 0 21/08/2002 01/05/2002 29/05/2002 04/09/2002 18/09/2002 02/10/2002 11/12/2002 15/05/2002 12/06/2002 26/06/2002 10/07/2002 24/07/2002 07/08/2002 16/10/2002 30/10/2002 13/11/2002 27/11/2002 25/12/2002

26. Length of stay by day of admission 9 7.8 7.6 8 7.1 7.0 6.5 7 6.1 6.2 6 Average length of stay (days) 5 4 3 2 1 0 Monday Tuesday Wednesday Thursday Friday Saturday Sunday Variation in in-patient LOS

27. Length of stay by day of admission 9 8 6.5 6.5 6.5 6.5 6.5 7 6.1 6.2 6 5 Average length of stay (days) 4 3 2 1 0 Monday Tuesday Wednesday Thursday Friday Saturday Sunday

28. Greatest impact will be seen by concentrating on shorter LOS - usually simple discharges Length of stay 250 200 150 Number of patients 100 50 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 Length of stay (days)

29. Solutions • Estimated Date of Discharge Every patient has an EDD that drives their patient pathway. Patient pathways are actively managed

30. Solutions • Earlier in Day Discharge Morning discharge should be the default position Patients are discharged in the afternoon only as the exception

31. With hourly information on arrival and discharges, we can see why Arrivals and discharges by hour: Monday only Elective admissions and discharges are poorly co-ordinated with arrivals starting early morning and discharges not peaking until mid afternoon. 30 25 20 number of arrivals or discharges per hour 15 10 5 0 Mo 0 Mo 6 Mo 12 Mo 18 24 hour of week Emer Adm A&E Emer Adm direct Elec Adm Disch

32. We moved 35 (out of 123) discharges from the afternoon to the morning But what would their situation have looked like with a different pattern of discharges? discharges: before and after 30 25 20 15 10 5 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 before after

33. The arrivals and discharges are now much better balanced... Arrivals and discharges by hour: monday only 30 25 20 number of arrivals or discharges per hour 15 10 5 0 Mo 0 Mo 6 Mo 12 Mo 18 Tu 0 hour of week Emer Adm A&E Emer Adm direct Elec Adm Disch

34. And, as a result the peak in bed use is only about 10 and occurs much earlier in the day

35. Mismatches by day of week

36. Emergency & Elective Admissions April-November 2002 60 50 40 Emergency Number of Admissions 30 Admissions 20 Elective Admissions 10 0 10/06/2002 08/07/2002 16/09/2002 14/10/2002 11/11/2002 01/04/2002 15/04/2002 29/04/2002 13/05/2002 27/05/2002 24/06/2002 22/07/2002 05/08/2002 19/08/2002 02/09/2002 30/09/2002 28/10/2002

37. Elective / emergency profile Note the high elective demand peaks Mon - Wednesday.

38. Short-Term Improvements • Gain operational control of beds • Identify the system variations causing problems with bed availability • Redesign systems and processes to reduce variation, thereby improving flow • Implement the Wait for a Bed Checklist

39. Medium-Term Improvements • Address variation in elective flows • Develop predictive and scheduling tools to manage patient flows across the whole Trust • Segment patient flows to maximise the use of capacity

40. Long-Term Improvements • Gain strategic control of bed management • Bed configuration • Integrate service improvement work into strategic planning