Improving care of people with mental health problems using the Galatean Risk and Safety Tool
(GRiST)
Christopher BuckinghamComputer Science, Aston University
Ann AdamsMedical School, University of Warwick
September 26th, 2012
The potential for IAPT services
www.egrist.org
Wolfson College Cambridge
Risks associated with mental health problems
• Suicide• Self harm• Harm to others and damage to property• Self neglect• Vulnerability• Risk to dependents
Our research is about better understanding, detection, and management
It is aimed at both clinicians and service usersIt feeds into the clinical tool and improved services
Some of the Research Team
Ann Adams,& Christopher MaceUniversity of Warwick
Christopher Buckingham,Ashish Kumar, Abu AhmedUniversity of Aston
Evidence about mental-health risksRisk
independent cues
Risk
cue clusters
Risk
cue interactions
specific cue valuesoccurring together
particular cuecombinations
We know quite a lot We know a little
We hardly know anything
No explicit integration
RISKASSESSMENT
Risk tool
Clinical judgement
Need to connect the information sources
RISKASSESSMENT
Risk tool
Clinical judgement
HOLISTIC
Data hard to extract
Electronic documents: little structure, information buried
Yes, this really is an NHS decision support document
Data not shared
RISKASSESSMENT
RISKASSESSMENT
Mon
Tue
Fri
RISKASSESSMENT
or exploitthe semanticweb
The solution: GRiST• Explicitly models structured clinical judgements• Underpinned by a database with sophisticated statistical
and pattern recognition tools.– linked with empirical evidence
• Developed from the start to exploit the semantic web– universally available– ordinary web browsers
• Designed as an interactive tool with sophisticated interface functionality
• Provides a common risk language with multiple interfaces
– collecting information– providing advice
• Supports shared decision making and self-assessment
The solution: GRiST• Versions for different populations
– older, working age, child and adolescent– specialist services (e.g. learning disability, forensic)
• A whole (health and social care) system approach to risk assessment
www.egrist.org
Wisdom
Expertise
Dissemination
Eliciting expertiseKnowledge bottleneck
– Extracting expertise– Representational language experts understand– Gain agreement between multiple experts– Lowest common denominator ……
Unstructured Interview
• What factors would you consider important to evaluate in an assessment of someone presenting with mental health difficulties?– prompts or probes to explore further
• 46 multidisciplinary mental-health practitioners
Mind map with total numbers of expertsresults of integrating interview data
12 experts
• identifies relevant service-user data• “tree” relates data to risk concepts and top-level risks• information profile for service user
Interview transcripts
Qs & layers
XSLT
Different riskscreeningtools for varying circumstancesand assessors
Coding
Lisp
Lisp or XSLT
Mind map
Tree for pruning
Pruned tree
Data gathering treeData gathering treewith questions and layers
that organise question priority
Fully annotatedpruned tree
mark up
XS
LT
All trees are implemented as XML
Hanging notes on the tree
• Instructions to the computer
• What tools to produce
• What target users
IAPT demoIf the person says yes
IAPT versionof Gristjust 6 screeningquestions
Opens up four subsidiary questions for IAPT
If the person says yes
Two more IAPT questions are asked.
Comments and management information can be added to any
questions
An overall risk judgement is made along with supporting comments
and risk management information
Risk reports are generated immediately and can be downloaded
as a pdf.This shows a summary
just for suicide
Each risk has a detailed information profile that explains where the risk judgement came
from.
commentaction/intervention
gold padlock
silver padlock
red means filled
Interface functionality
Manage patient assessments
Service audit data (i)
Service audit data (ii)
Vision for myGRiST
• A tool to help service users:– Self-monitor and self-manage risk– Understand factors in their lives that influence risk– Make decisions about how and when to intervene to
reduce risk– Own their own history and risk profile– Communicate with clinicians and others about risk– Share in risk management decisions
myGRiST
myGRiST
GRiST DSS in the community
• Service users use myGRiST for self assessment– with carers– reports sent to clinicians prior to consultations
• Clinicians use GRiST for own assessment– compare with consumers– support shared assessment and personal safety
planning• Monitoring in the community
– service users continue to use myGRiST– alerts sent to clinicians for high-risk issues
Community
Primary care
IAPT
Secondary care Recovery in the community
• social care– housing– police
• education• occupational
health• general public
• mental health services– acute– specialist– OATS
myGRiST myGRiST
• social care– housing– police
• education• occupational
health• general public
Communication
• GRiST Cloud– common data
PHQ-9 et alGAD-7
GPs
IAPT myGRiST MH trusts
Private hospitals
Non-health orgs:education, work,
community
Data sharingData exchangeData integration
social services
Current GRiST database• 96,040 cases of patient data linked to clinical
risk judgements• Different risks• Different age ranges• Precise quantitative input linked with
qualitative free text
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How we do itTransparentKnowledge and reasoning can be understood
• Black box• Can’t see how
answer derived
input data
Risk data
output judgement
Risk evaluation
input
data
judgement
input data
GRiST cognitive modelClear explanation for risk judgementIdentifies important risk conceptsInforms interventions
judgemen
t
Mathematical modelsOptimal prediction of judgementValidation of cognitive modelEvidence base for cues and relationship with risks
RBFNBBNneural netPCA
securetrusted
risks
Remote monitoring and support
myGRiST assessmentsby the service userRaised risks raise alerts
www.egrist.org
