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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. Wolfson College. Cambridge. September 26 th , 2012. Christopher Buckingham Computer Science, Aston University Ann Adams

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Christopher buckingham computer science aston university ann adams

www.egrist.org

Improving care of people with mental health problems using the Galatean Risk and Safety Tool (GRiST)

The potential for IAPT services

Wolfson College

Cambridge

September 26th, 2012

Christopher Buckingham

Computer Science, Aston University

Ann Adams

Medical School, University of Warwick


Risks associated with mental health problems

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 clinical tool and improved services


Some of the research team

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

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

No explicit integration

Clinical judgement

Risk tool

RISK

ASSESSMENT


Need to connect the information sources

Need to connect the information sources

Clinical judgement

Risk tool

holistic

RISK

ASSESSMENT


Data hard to extract

Data hard to extract


Electronic documents little structure information buried

Electronic documents: little structure, information buried

Yes, this really is an NHS decision support document


Data not shared

Data not shared

Mon

RISK

ASSESSMENT

Tue

RISK

ASSESSMENT

or exploit

the semantic

web

Fri

RISK

ASSESSMENT


The solution grist

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 grist1

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


Christopher buckingham computer science aston university ann adams

www.egrist.org


Christopher buckingham computer science aston university ann adams

Dissemination

Expertise

Wisdom


Eliciting expertise

Eliciting expertise

Knowledge bottleneck

  • Extracting expertise

  • Representational language experts understand

  • Gain agreement between multiple experts

  • Lowest common denominator ……


Unstructured interview

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 experts results of integrating interview data

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


Christopher buckingham computer science aston university ann adams

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


Hanging notes on the tree

Hanging notes on the tree

  • Instructions to the computer

  • What tools to produce

  • What target users


Iapt demo

IAPT demo

If the person says yes

IAPT version

of Grist

just 6 screening

questions


Opens up four subsidiary questions for iapt

Opens up four subsidiary questions for IAPT

If the person says yes


Christopher buckingham computer science aston university ann adams

Two more IAPT questions are asked.


Christopher buckingham computer science aston university ann adams

Comments and management information can be added to any questions


Christopher buckingham computer science aston university ann adams

An overall risk judgement is made along with supporting comments and risk management information


Christopher buckingham computer science aston university ann adams

Risk reports are generated immediately and can be downloaded as a pdf.

This shows a summary just for suicide


Christopher buckingham computer science aston university ann adams

Each risk has a detailed information profile that explains where the risk judgement came from.


Christopher buckingham computer science aston university ann adams

Interface functionality

comment

gold padlock

silver padlock

red means filled

action/intervention


Manage patient assessments

Manage patient assessments


Service audit data i

Service audit data (i)


Service audit data ii

Service audit data (ii)


Vision for mygrist

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


Christopher buckingham computer science aston university ann adams

myGRiST


Christopher buckingham computer science aston university ann adams

myGRiST


Grist dss in the community

GRiST DSS in the community

  • Service usersuse 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 userscontinue to use myGRiST

    • alerts sent to clinicians for high-risk issues


Christopher buckingham computer science aston university ann adams

Primary care

Recovery in

the community

Secondary care

Community

IAPT

myGRiST

myGRiST

  • social care

    • housing

    • police

  • education

  • occupational health

  • general public

  • social care

    • housing

    • police

  • education

  • occupational health

  • general public

  • mental health services

    • acute

    • specialist

    • OATS


Communication

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

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


Christopher buckingham computer science aston university ann adams

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


Christopher buckingham computer science aston university ann adams

GRiST cognitive model

Clear explanation for risk judgement

Identifies important risk concepts

Informs interventions

input data

judgement

secure

trusted

risks

RBFN

BBN

neural net

PCA

judgement

input data

Mathematical models

Optimal prediction of judgement

Validation of cognitive model

Evidence base for cues and relationship with risks


Remote monitoring and support

Remote monitoring and support

myGRiST assessments

by the service user

Raised risks raise alerts


Christopher buckingham computer science aston university ann adams

www.egrist.org


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