Impact of Hospital targets such as NEAT on Discharge
Planning
Discharge Planning Conference
24-25 July 2014 | Novotel on C...
Content
• Introduction
• Impact of early discharge & Data to
forecast discharge
• Strategies for early discharge: 11am
dis...
Where are we
Gold Coast
Southport
70,000 presentation
Carrara
Hospital
Gold Coast Robina
55,000 presentations
Who are we?
• James Lind
• FACEM GCUH
Emergency
• Brett Sellars
• Service Director
Division of
Medicine
So why do we care about Early
Discharge…..
So what is it really about?
Optimise
hospital
capacity
Early
discharge
Hospital
avoidance
Better
scheduling
of elective
pa...
And if we Overcrowding a system it is related to
adverse outcomes
Source GCH data 2013
The regression curve show
that once...
The How: The science behind early
discharge
• Early discharge is probably the most
tangible way of creating capacity
• The...
NEAT is strongly related to cases per hour ie the more
cases, the more likely the breach. Therefore, any
potential solutio...
The when: Time of of initial presentation
to ED set the time of discharge
2014
2013
Source EDDIS
1200
600
0
V
o
L
u
m
e
Ti...
Science of bed management
Key insights
Occupancy typically runs over
90% making it difficult to flex in
periods of high de...
The science of Occupancy and
capacity
40%
50%
60%
70%
80%
90%
100%
110%
120%
130%
140%
0
200
400
600
800
1000
1200
Occupan...
The science of Occupancy and
capacity
40%
50%
60%
70%
80%
90%
100%
110%
120%
130%
140%
0
200
400
600
800
1000
1200
Occupan...
Mathematics of access block
Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) EDPr...
Mathematics of access block
Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) EDPr...
Mathematics of access block
Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) EDPr...
Mathematics of access block
Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) EDPr...
What is the relationship between access
block and occupancy
Occupancy
A
“capacity
strategies”
B
ED over
flow
C
Hospital
Ov...
What is the relationship between access
block and LOS?
5 hours
Admissions
Discharges
‘d1’
5 hours
Discharges
‘d2’
Category...
So what does it mean?
0
50
100
150
200
250
300
350
400
450
55
60
65
70
75
80
85
90
95
100
105
0 1 2 3 4 5 6 7 8 9 10 11 12...
Is it a linear relationship?
?
Evidence based
optimal early
discharge time of
2.15hrs
What is the relationship between occupancy
and early discharge
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2 Hours Early 1...
Occupancy and Access block
0
50
100
150
200
250
75%
80%
85%
90%
95%
100%
105%
110%
115%
1 2 3 4 5
AccessBlockCasesperday
O...
So what about the patient?
Occupancy
Patient A
LOS 5.5hrs
Patient A
LOS 8 hr.
Admission/discharge
processes
90% 95% 105%
The Annual plan
Winter looks bad!
Strategies to execute Early
discharge
Strategies for Early safe Discharge
• EDD
• Planned predicted discharge
• Increased scope of transit longue
• Increased sc...
How to monitor EDD
The EDD on a ward level
The Data To Forecast Discharge
• Use of predictive software to look at
– Discharges
– Admission
– Net variance between the...
The One Stop Shop for Discharge
The EDDI Nurse In Emergency
• Emergency department Discharge Initiative Nurse
• Part of the integrated care team based in ...
The Stranded Patient
• What is the stranded patient
• How to manage them
– Multidisciplinary rounds
• Is this bang for buc...
Does it work?
With a little help from other process redesign
work !!!
Access and
Flow Unit
commence
s
Access and
flow
director
appointed...
Thank you
?
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Dr James Lind & Brett Sellars, Gold Coast University Hospital - The Impact of Hospital Targets such as NEAT on the Discharge Planning Process

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Dr James Lind & Brett Sellars, Gold Coast University Hospital delivered the presentation at the 2014 Discharge Planning Conference.

The 2014 Discharge Planning Conference - Assisting health services to adopt an integrated and consumer directed approach to discharge planning.

For more information about the event, please visit: http://bit.ly/dischargeplan14

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Dr James Lind & Brett Sellars, Gold Coast University Hospital - The Impact of Hospital Targets such as NEAT on the Discharge Planning Process

  1. 1. Impact of Hospital targets such as NEAT on Discharge Planning Discharge Planning Conference 24-25 July 2014 | Novotel on Collins Melbourne Brett Sellars: Service Director Division of Medicine and Integrated care. James Lind: Emergency Department FACEM
  2. 2. Content • Introduction • Impact of early discharge & Data to forecast discharge • Strategies for early discharge: 11am discharge • One stop shop for discharge • The EDDI nurse in ED • The stranded patient
  3. 3. Where are we Gold Coast Southport 70,000 presentation Carrara Hospital Gold Coast Robina 55,000 presentations
  4. 4. Who are we? • James Lind • FACEM GCUH Emergency • Brett Sellars • Service Director Division of Medicine
  5. 5. So why do we care about Early Discharge…..
  6. 6. So what is it really about? Optimise hospital capacity Early discharge Hospital avoidance Better scheduling of elective patients Predictive modeling Aberrant monitoring Bed demand modeling Frequent flyer Readmission Smart bed configuration
  7. 7. And if we Overcrowding a system it is related to adverse outcomes Source GCH data 2013 The regression curve show that once you reach a critical capacity, SAC events dramatically increase Occupancy 1=100% Insight Over occupancy of a system is associated with increased SAC events
  8. 8. The How: The science behind early discharge • Early discharge is probably the most tangible way of creating capacity • There needs to be an understanding of Neat ED Bed management Early discharge Occupancy Math's of patient flow
  9. 9. NEAT is strongly related to cases per hour ie the more cases, the more likely the breach. Therefore, any potential solution must effect this parameter. Access block is minimally effected by cases per hour, but more strongly effected by occupancy of the hospital An interesting relationship appears to exist between occupancy and NEAT breaches. Any increase or decrease in hospital occupancy outside the shaded zone will worsen breaches, ie if the system is too busy or quiet, NEAT will get worse not better. It suggests activity needs to be tightly regulated to achieve optimal NEAT compliance Data from AEHRC 2012 Science of NEAT Insight Access block is related to occupancy
  10. 10. The when: Time of of initial presentation to ED set the time of discharge 2014 2013 Source EDDIS 1200 600 0 V o L u m e Time of day ED surge occurs at 0900-1100 Ie beds needed from 11am. Elective surgery need beds form 10am Key insight Bed needed at 11am
  11. 11. Science of bed management Key insights Occupancy typically runs over 90% making it difficult to flex in periods of high demand Day time occupancy levels are impacted by both elective and emergency patients presenting to the system High occupancy adds complexity to the management of patient flow and beds Source: QEII Key Activity and HBCIS Hospital Occupancy peaks at 102% at 9am Hospital Occupancy nadir at 82%% at 16:00 Hospital Occupancy per hour 100% 0% Occupancy Hour of day Midnight =90%
  12. 12. The science of Occupancy and capacity 40% 50% 60% 70% 80% 90% 100% 110% 120% 130% 140% 0 200 400 600 800 1000 1200 Occupancy(%) Capacity(NumberofBeds) Capacity Occupancy
  13. 13. The science of Occupancy and capacity 40% 50% 60% 70% 80% 90% 100% 110% 120% 130% 140% 0 200 400 600 800 1000 1200 Occupancy(%) Capacity(NumberofBeds) Capacity Occupancy But our “big hospital are least occupied and have the worst NEAT Insight More complex than number of beds
  14. 14. Mathematics of access block Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) EDPresentations (patients/hr) (Y1 axis) EDDischarges (patients/hr) (Y1 axis) Inpatient Admissions from ED (patients/hr) (Y1 axis) Inpatient Length of Stay(days) (Y2 axis) ED Length of Stay(inpatients) (hours) (Y2 axis) EDLength of Stay(others) (hours) (Y2 axis) EDAccess Block Cases (inpatients) (patients/hr) (Y2 axis) 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 75% 80% 85% 90% 95% 100% 105% 110% 115% OCCUPANCY GROUP3 A B C 300 >= Beds 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 75% 80% 85% 90% 95% 100% 105% 110% OCCUPANCY GROUP2 A B C900 >= Beds > 300 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 70% 75% 80% 85% 90% 95% 100% OCCUPANCY GROUP 1 A B C Beds > 900
  15. 15. Mathematics of access block Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) EDPresentations (patients/hr) (Y1 axis) EDDischarges (patients/hr) (Y1 axis) Inpatient Admissions from ED (patients/hr) (Y1 axis) Inpatient Length of Stay(days) (Y2 axis) ED Length of Stay(inpatients) (hours) (Y2 axis) EDLength of Stay(others) (hours) (Y2 axis) EDAccess Block Cases (inpatients) (patients/hr) (Y2 axis) 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 75% 80% 85% 90% 95% 100% 105% 110% 115% OCCUPANCY GROUP3 A B C 300 >= Beds 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 75% 80% 85% 90% 95% 100% 105% 110% OCCUPANCY GROUP2 A B C900 >= Beds > 300 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 70% 75% 80% 85% 90% 95% 100% OCCUPANCY GROUP 1 A B C Beds > 900
  16. 16. Mathematics of access block Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) EDPresentations (patients/hr) (Y1 axis) EDDischarges (patients/hr) (Y1 axis) Inpatient Admissions from ED (patients/hr) (Y1 axis) Inpatient Length of Stay(days) (Y2 axis) ED Length of Stay(inpatients) (hours) (Y2 axis) EDLength of Stay(others) (hours) (Y2 axis) EDAccess Block Cases (inpatients) (patients/hr) (Y2 axis) 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 75% 80% 85% 90% 95% 100% 105% 110% 115% OCCUPANCY GROUP3 A B C 300 >= Beds 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 75% 80% 85% 90% 95% 100% 105% 110% OCCUPANCY GROUP2 A B C900 >= Beds > 300 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 70% 75% 80% 85% 90% 95% 100% OCCUPANCY GROUP 1 A B C Beds > 900
  17. 17. Mathematics of access block Inpatient Admissions (patients/hr) (Y1 axis) Inpatient Discharges (patients/hr) (Y1 axis) EDPresentations (patients/hr) (Y1 axis) EDDischarges (patients/hr) (Y1 axis) Inpatient Admissions from ED (patients/hr) (Y1 axis) Inpatient Length of Stay(days) (Y2 axis) ED Length of Stay(inpatients) (hours) (Y2 axis) EDLength of Stay(others) (hours) (Y2 axis) EDAccess Block Cases (inpatients) (patients/hr) (Y2 axis) 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 75% 80% 85% 90% 95% 100% 105% 110% 115% OCCUPANCY GROUP3 A B C 300 >= Beds 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 75% 80% 85% 90% 95% 100% 105% 110% OCCUPANCY GROUP2 A B C900 >= Beds > 300 0 5 10 15 20 25 30 35 40 45 0 10 20 30 40 50 60 70 80 90 70% 75% 80% 85% 90% 95% 100% OCCUPANCY GROUP 1 A B C Beds > 900
  18. 18. What is the relationship between access block and occupancy Occupancy A “capacity strategies” B ED over flow C Hospital Overflow Admission/discharge processes 90% 95% 105%
  19. 19. What is the relationship between access block and LOS? 5 hours Admissions Discharges ‘d1’ 5 hours Discharges ‘d2’ Category 1 Category 2 Category 4 Category 5 Category 3 Hour of Day NumberofPatients
  20. 20. So what does it mean? 0 50 100 150 200 250 300 350 400 450 55 60 65 70 75 80 85 90 95 100 105 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Discharges/hour Occupancy(%) Time of Day (hour) 2 Hours Early 1 Hour Early Actual 1 Hour Late 2 Hours Late 2 Hour Early Discharge (all 23 Hospitals) : Average Occupancy reduced from 93.7% to 91.6%. Maximum Occupancy reduced from 110.8% to 106.1%. Time spent above 95% occupancy reduced from 34.7% to 21.5%. 2 Hour Late Discharge (all 23 Hospitals) : Average Occupancy increased from 93.7% to 95.8%. Maximum Occupancy increased from 110.8% to 115.6%. Time spent above 95% occupancy increased from 34.7% to 45%.
  21. 21. Is it a linear relationship? ? Evidence based optimal early discharge time of 2.15hrs
  22. 22. What is the relationship between occupancy and early discharge 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2 Hours Early 1 Hour Early Actual 1 Hour Late 2 Hours Late Time(%) Discharge Timing Occupancy > 80% Occupancy > 85% Occupancy > 90% Occupancy > 95% Occupancy > 100% Occupancy > 105% Insight The more occupied a system becomes, The more critical is early discharge
  23. 23. Occupancy and Access block 0 50 100 150 200 250 75% 80% 85% 90% 95% 100% 105% 110% 115% 1 2 3 4 5 AccessBlockCasesperday Occupancy(%) Category 23 Hospitals Mean Occupancy (Y1 Axis) Mean PeakOccupancy (Y1 Axis) Mean AB Cases (Y2 Axis) 5 hours Admissions Discharges ‘d1’ 5 hours Discharges ‘d2’ Category 1 Category 2 Category 4 Category 5 Category 3 Hour of Day NumberofPatients
  24. 24. So what about the patient? Occupancy Patient A LOS 5.5hrs Patient A LOS 8 hr. Admission/discharge processes 90% 95% 105%
  25. 25. The Annual plan Winter looks bad!
  26. 26. Strategies to execute Early discharge
  27. 27. Strategies for Early safe Discharge • EDD • Planned predicted discharge • Increased scope of transit longue • Increased scope SSU • Use of HITH • Use of pathways • Nurse initiated discharge • Advance care allied health • Integrated care
  28. 28. How to monitor EDD
  29. 29. The EDD on a ward level
  30. 30. The Data To Forecast Discharge • Use of predictive software to look at – Discharges – Admission – Net variance between the 2 with respect to the last 2 days of data
  31. 31. The One Stop Shop for Discharge
  32. 32. The EDDI Nurse In Emergency • Emergency department Discharge Initiative Nurse • Part of the integrated care team based in Emergency • EDDI under 65 yr. Chip over 65 yd. • Advanced practice emergency nurse • Knowledge of chronic diseases, soft tissue injuries, wound care, minor head injuries, medication advice, alcohol and drug dependence advice and a specialist on community services and referrals. • Provide consultation to emergency patients and free up time for medical staff • Provide on going education for the patient and for clinical staff with in the Emergency department. • Development of data base to provide electronic and hard copy advise and education for patients Wallis, M., Hooper, J., Kerr, D., Lind, J. & Bost, N. (2009). Effectiveness of an advanced practice emergency nurse role on discharge processes in a minor injuries unit. Australian Journal of Advanced Nursing 27 (1), 21-29
  33. 33. The Stranded Patient • What is the stranded patient • How to manage them – Multidisciplinary rounds • Is this bang for buck – Very difficult to move
  34. 34. Does it work?
  35. 35. With a little help from other process redesign work !!! Access and Flow Unit commence s Access and flow director appointed Medical Assessmen t Unit opens Southport 24 hour CNC coverage 5 days a week BPIO commenced full time Robina and Southport ED Restructure of staffing to accommodat e early decision making in ED Business Practice Improvement officer role commenced Extra FTE in medical, nursing and admin Current management CNC to work on floor to increase coverage Reconfigure of current FTE to accommodat e new model of care Increase in Short Stay Unit capacity from 10 beds to 6 beds and 7 chairs PIT model commence d at Southport Emergency Process People ADON patient flow and extra bed managers Refinement of ward based care model Re- deployment of medical staff to clinics Rapid access clinics for medicine commence d Full time BPIO appointed New process in bed management Macro NEAT Project •Slack box process redesign •Early decision making •Education to staff on NEAT •Performance feed back •Definition on purpose and function of ED Appointment of new CE Additional nursing resources for bed management • Reconfigure bed meeting •* Additional Afternoon bed meeting •Rescheduling of ICU radiology , cardiac and HODU PT •Opening of additional HDU over winter Redesign of bed manage ment Executive rounding in ED Surge plans for all sub- specialities and new Capacity alert process Ward based porterage and refinement of bed cleaning
  36. 36. Thank you ?

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