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www.egrist.org. Improving care of people with mental health problems using the Galatean Risk and Safety Tool ( GRiST ). The potential for IAPT services. LUFC. Elland Road. April 10 th , 2013. Christopher Buckingham, Computer Science, Aston University
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www.egrist.org Improving care of people with mental health problems using the Galatean Risk and Safety Tool (GRiST) The potential for IAPT services LUFC Elland Road April10th, 2013 Christopher Buckingham, Computer Science, Aston University Ann Adams, Medical School, University of Warwick
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 users It feeds into the GRiST clinical tool and improved services
Some of the Research Team Christopher Buckingham, Ashish Kumar, Abu Ahmed University of Aston Ann Adams, & Christopher Mace University of Warwick
Evidence about mental-health risks Risk particular cue combinations cue clusters Risk We know a little Risk We know quite a lot independent cues cue interactions specific cue values occurring together We hardly know anything
No explicit integration Clinical judgement Risk tool RISK ASSESSMENT
Need to connect the information sources Clinical judgement Risk tool holistic RISK ASSESSMENT
Electronic documents: little structure, information buried Yes, this really is an NHS decision support document
Data not shared Mon RISK ASSESSMENT Tue RISK ASSESSMENT or exploit the semantic web Fri RISK ASSESSMENT
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
Eliciting expertise Knowledge 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 • experts • identifies relevant service-user data • “tree” relates data to risk concepts and top-level risks • information profile for service user
Different risk screening tools for varying circumstances and assessors XSLT Tree for pruning Lisp or XSLT Lisp Pruned tree Mind map mark up Interview transcripts Coding Fully annotated pruned tree XSLT Qs & layers Data gathering tree with questions and layers that organise question priority Data gathering tree All trees are implemented as XML
Multiple populations handled by instructions in the tree • Work on specifying different models done by XML attributes • End-users access their own simple tree • What is XML? <family> <brother “john”/> <sister “mary”/> <daddy “long legs”/> </family>
Complete “universal” tree: multiple overlays working age
Complete “universal” tree: multiple overlays Older Adults
Complete “universal” tree: multiple overlays Service users
Multiple services • Same idea as populations • Customise service requirements • Difference is that they cover all populations • Services so far: • IAPT • Primary Care • Forensic
How not to design and develop • Must be able to meet end-user’s changing and varied requirements
Iterative development for implementing research results into evolving GRiST and myGRiST Agile software engineering
IAPT demo If the person says yes IAPT version of Grist just 6 screening questions
Opens up four subsidiary questions for IAPT If the person says yes
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.
Interface functionality comment gold padlock silver padlock red means filled action/intervention
Communication • GRiST Cloud • common data Data sharing Data exchange Data integration IAPT MH trusts myGRiST PHQ-9 et al Non-health orgs: education, work, community GAD-7 social services GPs Private hospitals
Current GRiST database (now twice as big) • 96,040 cases of patient data linked to clinical risk judgements • Different risks • Different age ranges • Precise quantitative input linked with qualitative free text
Dissemination Expertise Wisdom
How we do it Transparent Knowledge and reasoning can be understood Risk evaluation Risk data f(data) output judgement input data • Black box • Can’t see how answer derived