listen, learn, improve: using advanced data analytics to embed … · 2020. 4. 1. · listen,...
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Listen, Learn, Improve: Using advanced data analytics to embed patient experience feedback as a
near real-time quality improvement initiative
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Clinical Effectiveness Patient Safety
Patient Experience
Quality Trifecta
• Fixated on scores• Focus on response rates• Free text-comments not
analysed
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Staff appreciate feedback in the patients’ own words as this makes the comments seem more ‘real’
Frontline staff do not have access to this data, only used by at divisional/directorate level (given little priority)
High volume of free-text comments – lack of time
Need innovative method to analyse free-text data
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• Period: January – July 2017
• Inpatient, Outpatient, A&E, Maternity
– “What did we do well? & “What could we do better?”
• Total – 65,973 (x2)
Hopper et al, 895
Greaves et al, 6,412
Maramba et al, 3,426, avg. 43.98 words
Doing-Harris et al, 51,234
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5%
Manual Classification
(PExF Domain and Sentiment) MK
Manual Classification
SHW
Manual Classification
DM
Total comments January -July (IP, OP, A&E, Mat)
>60,000 10%
Train different learners
SVM (Support Vector Machine)
Blind classification
(stratified sample 500)
Inpatient
Outpatient
Prediction (PExF Domain
and Sentiment)
A&E
Maternity
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• Encouraging early dialogue in Transition and Continuity in Inpatients
• Facilitating better Access to Care in Accident and Emergency
• Improving Physical Comfort in Outpatients
Early Outcomes
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Staff Perspectives
• Technical efficiencies through reduction in labour costs and relocating staff time supporting QI projects
• Time spent on manual processing 6,000 responses was four days compared to 15 minutes using the NLP/ML algorithm, p<0.001
• Weak correlation 0.45 with average sentiment and FFT score
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Applying analytics and QI in parallel
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