APPLEMH

Adaptive Planning and raPid LEarning in Mental Health

Helen Brooks (Co-PI, Health Service Research, Manchester University)

John Fox (Co-PI, Cognitive scientist, OpenClinical knowledge sharing project)

Catriona Kennedy, Computer scientist, OpenClinical knowledge sharing project)

Tom Foley, Psychiatrist (Newcastle) and health informatics (NHS Digital)

Alex Casson (Engineering, Manchester)

Service user panel (Manchester)

Unmet need

Service users are insufficiently involved in the planning and management of their care

Needs:

Collaborative decision-making and care planning

Change plans dynamically in response to changing circumstances.

Solution:

Patient centred monitoring and decision support

… for both healthcare professionals and service users

APPLEMH - Vision

Collaborative planning and monitoring of care - with active re-planning in response to changing circumstances

Decision support with multiple perspectives (healthcare professionals, patients, their carers and families)

A learning health system, based on data captured during the care of many service users using analytics and machine learning to improve outcomes

US Institute of medicine 2015 “Science, informatics, incentives, and culture are aligned for continuous improvement and innovation, with best practices seamlessly embedded in the delivery process and new knowledge captured as an integral by-product of the delivery experience.”

APPLEMH: technical background

PROforma: a symbolic language for formalising clinical processes (J Amer. Medical Informatics Association, 2003)

Grounded in cognitive theory (Frontiers in Cog. Science, 2013)

CREDO: a mature software stack for building and testing PROforma applications (J Biomed Informatics, 2017)

OpenClinical: a platform for crowd sourcing and sharing PROforma models of clinical practice (Computers in industry, 2013).

Repository currently includes 50+ models across healthcare

www.openclinical.net

APPLE MH Roadmap

1. Phase 1 (current funding): feasibility of APPLE concepts in mental health

2. Phase 2: Implementation

1. Pilot evaluation on specific mental health challenge (depression)

2. Active support for rapid learning health system

Phase 1 has completed two studies

Technical and user requirements

for developing and deploying mental health services

three service user consultation meetings.

Prototype service models using PROforma and OpenClinical.net as a test platform.

used to explore requirements and functionality

usability important but not addressed in phase 1

design blueprint for a real application – not a final implementation.

simplified decision-making and plan management (not clinical details)

Phase 1 prototypes

Illustrative scenario

“Jane, 45, has until recently worked as an agency nurse. Six months ago she gave up her job because of fatigue and pain, and was diagnosed with Type 2 diabetes. She is now on disability and her partner has now left her. She has two adult children (18 and 20), but they are mostly away from home. In recent months, she has had serious depression symptoms as well as fatigue and poor sleep. She has just registered with the APPLEMH app.”

Clinical view: workflow and decision support

Service user consultation meetings

First Meeting: 13 March 2017 (5 SUs, 1 carer, 1 SU/carer):

Intro to OpenClinical in non-technical language

Result: initial requirements

Second Meeting: 25 April 2017 (5 SUs, 1 SU/carer, 2 carers):

Presented use cases

Result: refined requirements

Third Meeting: 1 August 2017 (7 SU/carers):

Presented prototype demo using web enactment

Result: action points for phase 2

Main Findings 1: service user requirements

R1: Decisions and treatment plans need to be transparent and accessible by service users. R2: allow SU to challenge decisions and to request changes. R3: infrastructure must enable collaboration and information sharing (avoiding silos) R4: SUs need opportunity to express preferences and concerns about treatment.

Patient-view: initial encounter

Patient view: engagement & services

Patient-view: initial encounter

Patient view: engagement & services

Main Findings 2: modelling

Pathway model must satisfy two main conditions: Compliance with current NICE guidelines

Requirements elicited from service users

Technical capabilities demonstrated in depression pathway Alerts, reminders, messaging, inference

Monitoring, plan updating, decision-making (options, arguments, viewpoints)

Appropriate services for different roles: Clinical-view – focus on NICE guidelines

Patient-view - focus on SU requirements

Integrated view: multiple perspectives on plan (SU, carer, GP, MH specialists...)

Main findings 3: design patterns

A key conclusion is that the required service is not just an “app” for individual users, but a distributed set of interoperable services embedded in a larger multidisciplinary professional network supporting service users and carers.

Demonstrated potential for developing a library of re-usable patterns that can simplify other mental health applications e.g:

Real-time monitoring of care; active alerts and reminders

Collaborative decision-making.

We hope to validate these patterns in other mental health applications, and in patient-centred multidisciplinary care more generally.

Deliverables from APPLE phase 1

D1: Study and report on clinical need, current state of the art and roadmap for achieving longer term vision – close to completion

D2: Mental health use cases to guide prototype development and evaluation - completed

D3: Clinical data model based on NICE guideline - completed

D4: Executable pathways based on NICE guidance – completed

D5: Documentation of models – in progress

D6: Final report and proposal for phase 2 – in progress

APPLE MH Roadmap

1. Phase 1 (current funding): evaluate feasibility of APPLE concepts in mental health

2. Phase 2 Implementation:

1. Pilot evaluation on specific mental health challenge (depression)

2. Support for rapid learning health system

Thanks