Christopher Buckingham Computer Science, Aston University Ann Adams

1. 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

2. 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

3. Some of the Research Team Christopher Buckingham, Ashish Kumar, Abu Ahmed University of Aston Ann Adams, & Christopher Mace University of Warwick

4. 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

5. No explicit integration Clinical judgement Risk tool RISK ASSESSMENT

6. Need to connect the information sources Clinical judgement Risk tool holistic RISK ASSESSMENT

7. Data hard to extract

8. Electronic documents: little structure, information buried Yes, this really is an NHS decision support document

9. Data not shared Mon RISK ASSESSMENT Tue RISK ASSESSMENT or exploit the semantic web Fri RISK ASSESSMENT

10. 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

11. 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

12. www.egrist.org

13. Dissemination Expertise Wisdom

14. Eliciting expertise Knowledge bottleneck • Extracting expertise • Representational language experts understand • Gain agreement between multiple experts • Lowest common denominator ……

15. 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

19. 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

20. 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

21. Hanging notes on the tree • Instructions to the computer • What tools to produce • What target users

24. IAPT demo If the person says yes IAPT version of Grist just 6 screening questions

25. Opens up four subsidiary questions for IAPT If the person says yes

26. Two more IAPT questions are asked.

27. Comments and management information can be added to any questions

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

29. Risk reports are generated immediately and can be downloaded as a pdf. This shows a summary just for suicide

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

31. Interface functionality comment gold padlock silver padlock red means filled action/intervention

32. Manage patient assessments

33. Service audit data (i)

34. Service audit data (ii)

35. 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

36. myGRiST

37. myGRiST

38. 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

39. 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

40. 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

41. 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

42. 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

43. 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

44. Remote monitoring and support myGRiST assessments by the service user Raised risks raise alerts

45. www.egrist.org