Unscheduled Care Collaborative Programme 27 th January 2006

Unscheduled Care Collaborative Programme 27 th January 2006 Understanding Demand & Planning Appropriate Capacity Gary Thompson Policy Lead for Emergency Care Trent Strategic Health Authority

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

Mismatch between demand capacity ➤ Variation in demand + variation in capacity = queue ➤ Occasionally demand > capacity

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

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

Lean Thinking I 1. Why is capacity varying? Queue 2. Set average capacity at 80% of variation in demand Queue Capacity Demand time

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

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

Are you a Purist or a Pragmatist?

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

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

Demand v Capacity

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

With hourly information on arrival and discharges, we can see why number of arrivals or discharges per hour 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 15 10 5 0 Mo 6 Emer Adm A&E Mo 12 hour of week Emer Adm direct Mo 18 Elec Adm 24 Disch

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

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

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

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

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

Where do you start? Where there is greatest variation

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

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

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

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

Length of stay Greatest impact will be seen by concentrating on shorter LOS - usually simple discharges Number of patients 250 200 150 100 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)

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

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

With hourly information on arrival and discharges, we can see why number of arrivals or discharges per hour 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 15 10 5 0 Mo 6 Emer Adm A&E Mo 12 hour of week Emer Adm direct Mo 18 Elec Adm 24 Disch

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

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

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

Mismatches by day of week

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

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

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

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

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