Embedded Research Quality Improvement Initiative€¦ · Research to Evidence based practice –...
Transcript of Embedded Research Quality Improvement Initiative€¦ · Research to Evidence based practice –...
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Embedded Research Quality Improvement Initiative
Amith Shetty
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Objectives
Embedded research
Shoe stringing
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Background
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Background
Research to Evidence based practice – delays
Capturing the effects of practice change – are we really doing better
Quality initiatives –
Usually very focused
System targets
Intended and unintended consquences
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SEPSIS KILLS program: reduce preventable harm to patients with sepsis RECOGNISE: Risk factors, signs and symptoms of sepsis and inform senior clinician RESUSCITATE: With rapid antibiotics and IV fluids within one hour REFER: To specialist care and initiate retrieval if needed
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Sepsis Bundle
– Oxygen
– Lactate
– Monitor
– Empirical Antibiotics
– Blood Cultures
– Intravenous Fluids
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Sepsis Kills
Embedded research
Shoe stringing
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Sepsis Pathways Pathways guide clinicians to THINK about sepsis NOT prescriptive ……clinical judgement is KEY
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SEPSIS KILLS results
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NSW hospital sepsis mortality
10
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2009-2011 2012 2013 2014 2015
Deat
hs w
ith a
nd w
ithou
t Aut
opsy
(%)
Principal only P+4 Comor P+5 Comor P+25 Comor P+50 Comor MJA - Comor 1-5
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SMEDSA
– Sydney Multicentre Emergency Department Sepsis Archive
– Retrospective chart review populated sepsis registry approved at 5 Western Sydney EDs patients placed on the sepsis pathway
– Patients identified through clinician reported EMR alert for sepsis based on CEC SIRS criteria or senior clinician suspicion
– Collects all SIRS, investigative and in-hospital outcome data for identified patients
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What we can already do!
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Track and trigger
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Self reported Time to antibiotics
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Data reports
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Research outcomes
At state level – CEC sepsis register – Broad coarse system level data
At district level – Multicentre data-rich Sepsis archive
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Lactate in Suspected sepsis – CEC sepsis register
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ED Lactate levels risk stratification Lactate group (mmol/L) Age median (IQR) Total, n (Died n/%)
[p]* AE n (%) [p]*
0 to <1 66.7 (48.1-79.4) 847 (37/4.37) [NA]
54 (6.38) [NA]
1 to <2 72.1 (57-82.1) 3531 (181/5.13) [0.36]
244 (6.91) [0.58]
2 to <3 73.1 (60.3-83) 1922 (145/7.54) [0.0003]
198 (10.3) [<0.0001]
3 to <4 74.3 (61.9-83.5) 897 (105/11.71) [0.0003]
135 (15.05) [0.0003]
≥ 4 74.1 (60.9-84) 1113 (283/25.43) [<0.0002]
352 (31.63) [<0.0002]
Total 72.6 (58.1-82.6) 8310 (751/9.04) 983 (11.83)
*p-values calculated for proportion difference against group below lactate group
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Data learning to guideline translation State Level
– Time to antibiotics target extended to 120 minutes
– Lactate trigger for high degree of adverse outcome risk ≥ 2 mmol/L included
Registry data
– SIRS algorithms performance
– Broad spectrum antibiotic usage and AMS initiatives
– Multicentre data validation of qSOFA and SOFA sepsis definitions
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Why do QI Research
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Lessons learnt
– Clinician leadership locally critical
– Engagement carrots!
– Sustainability crucial
– Reproducibility
– DATA DATA DATA
– Implementation science – guidelines, knowledge generation, reflection, adaptation and reimplementation + monitoring