Scotland January 2006 Final Version

Unscheduled Care Collaborative Programme27th January 2006Understanding Demand & Planning Appropriate Capacity: 

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

Why do queues form?: 

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

Mismatch between demand and capacity : 

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

Variation mismatch = queue: 

Variation mismatch = queue Can’t pass unused capacity forward to next week

Slide5: 

How do we work out required capacity?

Lean Thinking I: 

Lean Thinking I

Lean Thinking II: 

Lean Thinking II

Manage constraints: 

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?: 

Are you a Purist or a Pragmatist?

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

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

Slide11: 

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

Demand v Capacity: 

Demand v Capacity

For this trust Monday was a bad day: they ran out of beds before lunchtime: 

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: 

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

We can use the hourly information to calculate the change in the number of occupied beds across the day: 

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

Slide19: 

Bed Availability: A problem of variation IN-PATIENT STAY ADMISSION DISCHARGE

Slide20: 

IN-PATIENT STAY ADMISSION DISCHARGE Variation in patient pathways and processes. E.g. in Length of Stay “We always bring our hips in on Tuesday !”

Slide21: 

IN-PATIENT STAY ADMISSION DISCHARGE “Mr Smith’s TURP patients always stay five days but Mr Jones only keeps them in for three days

Slide22: 

IN-PATIENT STAY ADMISSION DISCHARGE “We’re too busy in the morning and haven’t time to think about discharges. They all get done in the afternoon.

Slide23: 

Where do you start? Where there is greatest variation

Slide24: 

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

Slide25: 

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

Slide26: 

Variation in in-patient LOS

Slide27: 

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

Slide28: 

Length of stay 0 50 100 150 200 250 0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 Length of stay (days) Number of patients

Solutions: 

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

Solutions: 

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: 

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

But what would their situation have looked like with a different pattern of discharges?: 

But what would their situation have looked like with a different pattern of discharges? discharges: before and after 0 5 10 15 20 25 30 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

The arrivals and discharges are now much better balanced...: 

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

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

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: 

Mismatches by day of week

Elective / emergency profile: 

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

Slide39: 

Daily bed requirement reduced from 78 to 68

Short-Term Improvements: 

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: 

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: 

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