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IMPROVING OUTCOMES FOR SICK CHILDRENNHS Tayside
Sick Children – Our Journey in Tayside
• 7000 acutely unwell children referred annually– ~30% admitted
• ICU admissions ~ 7 per 1000 admissions– Tayside accounts for 10% of all inpatient paediatric admissions
per annum in Scotland, only 5% of PICU admissions
• How many patients deteriorate in our care?• How many ICU admissions/deaths are preventable?• Can we improve?
Team ‘buy in’ - What is your Project 1?• What really drives the team nuts – what is the biggest
waste, safety, inefficiency issue that annoys all staff
• Start there
• Consult all staff re the process and empower all staff to test changes
• Don’t dismiss ideas until you have tried them
• Credit the team with team success
Tayside “Project 1”
• 5/12 old boy• Presented at 10 am to SSAA• Unwell for 3-4 hours with pyrexia and runny nose, still
feeding and babbling and smiling• Known to unit – complicated neonatal course• Thought to be well but not discharged due to parental
concern – first febrile illness since discharge• Sudden collapse in unit and died with meningococcal
sepsis by 6pm
Case review• Non recognition of the sick child• Then late recognition and failure to act promptly• Failure to escalate• Once escalated senior multidisciplinary team involved in
simultaneous resuscitation
• Team invested in this patient as well known to unit • huge division in team ensued with a blame culture
• How do we turn this around and restore faith in each other and our team? We do our best to ensure we provide the appropriate and timely care to all our patients.
Improvement Aim – ambitious or naïve
Outcome Primary DriversSecondary Drivers (change concepts)
Appropriate, timely and
reliable recognition and management of
sick children
Infrastructure and culture to
promote safety
Effective communication
Zero preventable readmissions,
crash calls,HDU/ PICU
admissions. In-ward deaths
by June 2013
Empower all staff to voice concernsSafety walkroundsLearning from adverse events (case note reviews, IR1, PTT)Sharing all data with whole team +/- patients and carersCapability and capacity
Early recognition (PEWS, watcher criteria)Appropriate escalation (PEWS escalation flow chart)Appropriately trained staff (life support courses, senior review, up skilling, regular updates)Testing theory in real time real place (emergency simulation)
Guidelines for common emergencies updated and immediately accessible (review dates and website updating)
Functioning appropriate equipment (bedspace checks, resus trolley)
Appropriate medicines ( in date, algorithms, remove unused)
Timely ( teaching re timelines, process change)
SBAR – handover, escalationSafety BriefingMultidisciplinary roundingDaily goalsEffective discharge planningEffective readmission planning /CYADM, anticipatory care plansMultiagency
Can we predict who will deteriorate? Can we prevent it?
% acute admissions to HDU Tayside Childrens Hospital Nov 2011 - April 2012
05
101520253035
0 1 2 3 4 5 6 7
PEWS score
%
80% of acute admissions to HDU have a PEWS <3
Why admit to HDU?
What causes concern & doesn’t score in PEWS?
Watchers
Gut Feelings.......“Researchers explain that intuition represents one of the ways our brains store, process
and retrieve information........ The researchers .... concluded that intuition - a feeling that something is right or wrong - is the brain drawing on past
experiences and current external cues to make a decision; a process so rapid that the reaction is subconscious.”
British Journal of Psychology (April 2008)
How do we know a change is an improvement?
• Outcome measures– Crash call rate, HDU & ICU admission rates, In ward mortality
rate– Prediction of Watchers
• Process Measures– PEWS, SBAR, MDR, DG, safety brief, equipment checks,
guideline checks, simulations, time to first dose of antibiotics,
adherence to specific guidelines • Balancing measures
– HDU admission rate, staff feedback (simulation), time invested in measuring v delivering service
How to move towards Safety Culture of recognising deteriorating children?
Com
mun
icat
ion
– M
DR
– S
afet
y B
riefin
gs
Equi
pmen
t, M
edic
ines
Emer
genc
y Si
mul
atio
nC
ase
note
revi
ews
PEW
S
Safety Brief – shared mental model
MULTIDISCIPLINARY SAFETY BRIEFING WARD 29 DATE: TIME:
EMPTY BEDS (bays/SR) /
ANTICIPATED DISCHARGES
PLANNED ADMISSIONS
WARD ISSUES PROBLEM DETAILS (including bed number)
YES NO
PATIENTS WITH SIMILAR NAMES
HIGH PEWS / WATCHERS
PATIENTS WITH INDIVIDUALISED PROTOCOLS (eg CYPADM)
Results: process measures
Reaching >98% compliance with process measures summer 2011
Balancing measure: HDU admission rate
Ward 29, Ninewells HospitalHDU Admission Rate
0102030405060708090
100110120130140150160170180190200
Ward 29, Ninewells HospitalHDU Admission Rate
Outcome measure – PICU admission rate
Ward 29, Ninewells HospitalICU Admission Rate
0
5
10
15
20
Ward 29, Ninewells HospitalPICU Admission Rate
Outcome measure: Crash Calls
Ward 29,HDU, SSAA Ninewells HospitalCrash Call Rate
0
10
20
Ward 29, Ninewells HospitalCrash Call Rate
Outcome measure: In-Ward Mortality
Ward 29, Ninewells HospitalIn Ward Mortality Rate
0
10
Ward 29, Ninewells HospitalIn-Ward Mortality Rate
Outcome measure: combined outcome Potential for national Serious Harm Index?
Ward 29 Ninewells Hospital total significant events rate (total mortality + crash calls + ICU admissions)
0
5
10
15
20
25
30
35
40
Jan-
10
Feb-
10
Mar
-10
Apr
-10
May
-10
Jun-
10
Jul-1
0
Aug
-10
Sep-
10
Oct
-10
Nov
-10
Dec
-10
Jan-
11
Feb-
11
Mar
-11
Apr
-11
May
-11
Jun-
11
Jul-1
1
Aug
-11
Sep-
11
Oct
-11
Nov
-11
Dec
-11
Jan-
12
Feb-
12
Mar
-12
Apr
-12
May
-12
Simulation started
New PEWS charts and reliability for multiple process measures across whole unit
Who is the sickest patient on the ward?
May 2011
• 16 different responses• Little overlap• No agreement with attending
Consultant
May 2012
• Agreement• Theory: Early recognition
and shared mental model increases number of reviews, decreases time to treatment and prevents deterioration
Tayside “Project 1” outcomes
• Tayside team believe in themselves as individuals and as a team
• We know we are providing high quality care (and have the data to show it)
• We may be improving outcomes for children but it is early days
• We know we have improved staff morale (and have data to prove it!)
• We now we have a team who “knows how to improve” • We are now on project 40+
Learning / Challenges – developing a Safety Culture
• Data is everything:– Baseline– And accurate, appropriate measurement
• Person dependence & improvement fatigue• Capability and capacity• Culture – transparency about “bad data”• Running before we could walk – especially simulation• “spread control”• What do we not know? Should we be worried about it?