Embedded Research Quality Improvement Initiative

Amith Shetty

Objectives

Embedded research

Shoe stringing

Background

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

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

Sepsis Bundle

– Oxygen

– Lactate

– Monitor

– Empirical Antibiotics

– Blood Cultures

– Intravenous Fluids

Sepsis Kills

Embedded research

Shoe stringing

Sepsis Pathways Pathways guide clinicians to THINK about sepsis NOT prescriptive ……clinical judgement is KEY

SEPSIS KILLS results

NSW hospital sepsis mortality

10

12

14

16

18

20

22

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

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

What we can already do!

Track and trigger

Self reported Time to antibiotics

Data reports

Research outcomes

At state level – CEC sepsis register – Broad coarse system level data

At district level – Multicentre data-rich Sepsis archive

Lactate in Suspected sepsis – CEC sepsis register

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

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

Why do QI Research

Lessons learnt

– Clinician leadership locally critical

– Engagement carrots!

– Sustainability crucial

– Reproducibility

– DATA DATA DATA

– Implementation science – guidelines, knowledge generation, reflection, adaptation and reimplementation + monitoring