Transcript Royal College of Surgeons in Ireland Coláiste Ríoga na Máinleá in

Royal College of Surgeons in Ireland
Coláiste Ríoga na Máinleá in Éirinn
Clinical Prediction Rules as a basis for Clinical Decision Support
HISI Conference, Dublin, 18th November 2010
Derek Corrigan, Borislav D. Dimitrov, Tom Fahey
PHS / Department of General Practice
Overview
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Brief overview of work HRB Centre for Primary Care Research
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What is a Clinical Prediction Rule (CPR)?
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What is a Clinical Decision Support System (CDSS)?
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What role can Clinical Predication Rules play in a CDSS?
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What form might a state of the art CPR based system look like?
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What are the challenges to achieving this state of the art?
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HRB Centre for Primary Care Research
•
On-Going Work
– Clinical and health informatics staff working on compiling a
definitive register of Clinical Prediction Rules (CPRs) for use in
Primary Care based on systematic reviews of clinical literature
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Ultimate Aim – e-Register
– Provide an electronic register of CPRs suitable for Primary Care
– Fully searchable
– Fully documented
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Definitions – Clinical Prediction Rule
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Clinical Prediction Rule
– Formalised clinical tools that quantify the contribution of
• Patient History – e.g. History of high blood pressure
• Physical Examination – e.g. Fever
• Diagnostic Tests – e.g. Blood count tests
– Stratify patients diagnosis
• Probability of having target disorder based on scoring system
– Outcome can be in terms of diagnosis, prognosis, referral or treatment
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An Example – CRB 65 Rule - Pneumonia
Confusion,
Respiratory Rate >= 30/min,
BP : SBP<90 mm Hg or DSP <= 60 mm Hg,
Age >= 65 years
Rule Criteria
CRB Score
Risk
Decision
0
1 OR 2
3 OR 4
Mortality Low
Mortality
Intermediate
Mortality High
Likely Home
Treatment
Likely Hospital referral
and assessment
Urgent
Hospital
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Definitions - Clinical Decision Support
System
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Clinical decision support system (CDSS)
– I.T. based systems that are designed to improve clinical decision
making by suggesting possible clinical actions/interventions based
on an underlying clinical evidence base
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CDSS Types
– Diagnostic systems – diagnose appendicitis
– Reminder systems – generate patient letters
– Disease management systems – diabetes management
– Drug dosing/prescribing – insulin, warfarin
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CDSS – The Electronic Patient Record
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The Electronic Patient Record (EPR) has long been viewed as a holy grail in
Health Informatics
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Some conflicting debate about what the quantifiable benefits of the EPR are, if
any
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Tend to view EPR in the context of a single patient
•
Doesn’t always take into account the potential when EPRs are looked at
collectively from a research perspective – this may be their real power!
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CDSS – Maintaining the Evidence Base
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Huge potential evidence base in EHRs in primary care e.g. General Practice
Research Database in UK (GPRD)
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Create clinical trials/ epidemiological studies from primary care data
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May be used to amend an existing CPR i.e. the inclusion of additional
symptoms/signs identified by data analysis as potential diagnostic cues
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May be used to create new CPR’s based on new diagnostic cue combinations
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Evidence base becomes “self-learning” and adds or refines the list of CPR’s used
as the evidence base
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Implementation of Research Evidence
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The TRANSFoRm Project
• “Translational Research and Patient Safety in Europe”
• 5 Year EU funded research project – just started
• 17 Participant bodies including the HRB Centre
• Leading Work Package 4 – “Decision Rules and Evidence”
• Bridge clinical research and primary care practice – will
involve validation in Irish GP sites
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TRANSFoRm Work Packages
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The TRANSFoRm Project
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TRANSFoRm
Services
1 CPR Repository
Clinical Prediction
Rules Service
2 Distributed
GP EHRs
With CDSS
3 Research Study Designer
Study Criteria
Design
CP Rules
Manager
CP Classifier
5 CPR Data Mining
and Analysis
CPR Analysis &
Extraction Tool
Find Eligible Patient
4 Research Study Management
Recruit Eligible Patient
Study Data Management
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Define Study Eligibility Criteria – Electronic Primary
Care Research Network (Epcrn)
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Gather Study Data - Case Report Forms ePCRN
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How can this improve Patient Safety?
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Diagnostic error is the major threat to patient safety in the context of
the primary care setting
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TRANSFoRm uses CPRs to broaden the evidence base considered by GPs
to support inclusion / exclusion of diagnostic hypotheses for any
particular case – not just previous patient history
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By implication, decreasing the possibility of diagnostic error will
improve patient safety
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Bridges the gap between implementing evidence based care research in
the primary care setting
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TRANSFoRm Challenges
The EPR
– Still a huge amount of work to be done just to create usable EPRs
System Interoperability – consistent representation of clinical data using
technologies
– Health Level 7 (HL7), OpenEHR – pool and share clinical data by
allowing systems to ‘talk together’
Semantic Interoperability – being able to interpret clinical concepts
contained within data in a consistent way
– Clinical Coding Terminologies such as SNOMED-CT, ICPC, ICD
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In Summary
• CPRs have huge potential as a form of evidence in CDSS
• A number of technical challenges exist – system/semantic
interoperability
• Future directions - develop the Electronic Patient Record
and incorporate research tools to generate and update the
evidence base – “self-learning”
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Thank You
Discuss!
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