Post on 17-Jul-2020
Greater Manchester CHC Care Pathways
Building Rapid Interventions to reduce antimicrobial resistance & over-prescribing of antibiotics (BRIT)
Potential for Scalability
Ownership – what level? CCGs, GP, STP, NHS Eng??
- Yes – but need the data
What services and knowledge is available
Communication
Feedback Points
1. Patient and industry education and support
2. Communication and continuity
3.
Group Members
Craig Wood - cwood@fdbhealth.com - Hearst Health
Graham Death - graham.death@dhaca.co.uk - Digital Health & Care Alliance
Tjeerd Van Staa - tjeerd.vanstaa@manchester.ac.uk - UoM
Opportunities
Pressure
(OptimiseRx)
Clinical decision support at the point of care
Patient compliance
Patient education
- Targetted
- Pre-consultation
Barriers
Education – Vicious cycle
Data
Fragmented
Time
Tariffs/funding – business model
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Greater Manchester CHC Care Pathways
Building Rapid Interventions to reduce antimicrobial resistance & over-prescribing of antibiotics (BRIT)
Potential for Scalability
Blockchain technology for dynamic permissions
Feedback Points
1. Open API across systems would enable wider opportunities for the project
2. Use incentives to GPs to reduce prescription rates supported by educational programme for GPs
3. More radically – re ove GP’s a ility to pres ri e a ti ioti s
Group Members
Jo Hobbs - georgina.hobbs@manchester.ac.uk - GM Connected Health Cities
Carmel Dickinson - carmel.dickinson@manchester.ac.uk - Mi
Mark Claydon - mark.claydon@trustech.nhs.uk - Trustech
Peter Jenkinson - peter@middleforthgreen.co.uk - Middleforth Green Consultin Ltd.
Tim Meehan - tim.meehan@horizonscitech.co.uk - Horizon SciTech
Peter Harrison - peter.harrison@nokia.com - Nokia Technologies
Opportunities
People more tech-savvy and so probably
more likely to engage in projects like this.
E.g. collecting own data on wearable apps.
Take patient generated data to health
professionals to upload and join their official
data.
Standardisation of API will improve the
potential for scalability
Barriers
Interoperability between systems
Bad press and association with care.data
Public perceptions
NHS gave google access to health data and
that caused public mistrust
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Greater Manchester CHC Care Pathways
Building Rapid Interventions to reduce antimicrobial resistance & over-prescribing of antibiotics (BRIT)
Potential for Scalability
National problem – prescribing issues/expectations/data capture
Better use of community pharmacy
Identification of demographics/cohorts – need for targeted messages
- How could this be replicated nationally
Needs to be adaptable to different demographics e.g. age/ethnicity
- People in the care homes
Using the wider CHC network to learn/spread/disseminate information
- Cross pathway learning
Feedback Points
1. Change in behaviour and expectations – GPs and patients
2. Partnership opportunities – public and private – communications, testing, spin out
3. Connected data environment is essential – GM and beyond
Group Members
Ian McKenna - iMcKenna@galen-research.com - Galen Research
Catherine Headley - Catherine.Headley@manchester.ac.uk - UoM
Mike Burrows - mike.burrows@gmahsn.org - GMAHSN
Azad Dehghan - a.dehghan@manchester.ac.uk - UoM
Sarah Rikard - sarah.rickard@srft.nhs.uk - GM Stroke ODN
William Welfare - william.welfare@phe.gov.uk - Public Health England
Stephen Lee - steve.p.lee@philips.com - Phillips
Anna Jenkins - anna.jenkins@liverpool.ac.uk - Uni of Liverpool
Opportunities
Changing patient flow/footfall
Patient interface
Big data analytics
Measure effectiveness of medication
Harnessing industry expertise
Innovative use of social media in public
health campaigns
GP electronic systems provide good
interface
Improving captive systems in hospital
prescribing
Barriers
Changing GP behaviours (barriers create
opportunities)
Changing patient expectations decision
point - do you need to see GP
Investment general
Investment towards behaviour change and
expectations – patient & on NHS
Are findings generalisable
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Page 54 of 78
Greater Manchester CHC Care Pathways
Building Rapid Interventions to reduce antimicrobial resistance & over-prescribing of antibiotics (BRIT)
Potential for Scalability
Process should be common across economotion
Sta dardised data see hat’s orki g a d ot orki g
Interoperability (or integration with existing systems)
Driven by the CCG – funding, resource, analytics
Feedback Points
1. CCG Focus (collaboration)
2. Technology/standardisation
3. Collaboration
Group Members
Adrian Owen - Adrian.Owen@insource.co.uk - Insource
Paul Hanmer - paul.hanmer@cmft.nhs.uk - Trustech
Grant Churnin-Ritchie - grant.churnin-ritchie@sas.com - SAS
Matt Fairley - matthew.fairley@systemc.com - SystemC
Andy Jeans - andy.jeans@orcha.co.uk - Orca
John Farenden - john.farenden@mac.com - EY
Sarah Barnes - EY
Lewis Pickles - lewis.pickles@tiani-spirit.com - Tiani Spirit
Charlotte McCowley - TBC
Sam Aspinall - sam.aspinall@vitalpac.com - SystemC
Neil Walbran - neil.walbran@healthwatchmanchester.co.uk - Health Watch Manchester
Opportunities
Use of technology to address the barriers (Apps)
E.g. Hubs – reception, clinical/NSE Pract
Ne odels of care Thi k Differe tly
Registering arrivals, capture older clinical
info. Already available.
Organisations to work collaboratively
GP sites – staff busy
Point of care testing – triage/self manage
(sputum sample score)
Personalisation of feedback e.g. app,
email, text, call
Barriers
1. Better Triage and points of contact
better info for patients
Standardisation of triage approach
Triage does ’t ide tify se erity increase £
risk risk management
2. Support for GP – pressure (time)
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Greater Manchester CHC Care Pathways
Building Rapid Interventions to reduce antimicrobial resistance & over-prescribing of antibiotics (BRIT)
Potential for Scalability
Fits with 5y forward – new models, feds, neighbourhoods
Needs strong leadership, change in culture and effective stewardship
Data/results to move
Consider multiple entry points v single access point
Needs public engagement
Feedback Points
1. P.O.C testing – feasible, effective, economic, acceptable
2. culture (clinicians/pts)
3. Changes in clinical pathway – need adopting, need accepting + using
Group Members
Stephen Melia - stephen.melia@manchester.ac.uk - UoM
Jane Macdonald - jane.macdonald@gmahsn.org - GMAHSN
Sarah Knowles - Sarah.Knowles@manchester.ac.uk - UoM
David Park - david.park@cisco.com - Cisco
Matthew Machin - matthew.machin@manchester.ac.uk - UoM
Chris Etchells - chris.etchells@kmswristband.com - KMS Solutions
Keli Shipley - keli.shipley@adi-uk.com - ADI Health
Opportunities
Prescribing by microbiology result
(Stewardship)
P.O.C testing?
CHC predictive data + P.O.C (confidence) +
‘ology results i a ti ely a er P.O.C multi-professional (pre-visit) i.e.
screening
Barriers
No one site testing
No scalable history
Need to communicate system effectively
Wide access to single pt. record
System adoption and individual GP
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Greater Manchester CHC Care Pathways
Building Rapid Interventions to reduce antimicrobial resistance & over-prescribing of antibiotics (BRIT)
Potential for Scalability
Feedback Points
1. Smartphone/wearable tech variability in access to technology
2. Data visualisation
3.
Group Members
Ruth Norris - ruth.norris@manchester.ac.uk - UoM
Niels Peek - niels.peek@manchester.ac.uk - UoM
Kieran O'Malley - kieran.omalley@manchester.ac.uk - UoM
Gary Clarke - gary.clarke@manxtelecom.com - Manx Telecom
Paul Turner - p.turner@wigan.gov.uk - Wigan Council
Chris Hart - christopher.hart@astrazeneca.com 0 AstraZeneca
Steve Hilton - steve@libertyapps.co.uk - Liberty Apps
Lisa Bennet - Lisabennett.work@gmail.com - Quintiles
Opportunities
Personalised medicine
Visualising the data
Reliable/coordinated/useful
Breaking the cultural/learnt norms
(antibiotics) through public engagement
GP as a nexus for change in patient
Knowing the baseline for comparability
Barriers
Cultural norm – over-prescribing
NHS digital – datasets
Information overload
Tools to clinicians
Limitations of algorithms
Over-reliance of the information – false
belief
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Greater Manchester CHC Care Pathways
Building Rapid Interventions to reduce antimicrobial resistance & over-prescribing of antibiotics (BRIT)
Potential for Scalability
Feedback Points
1. Who’s eha iour are e tryi g to ha ge (e d user/GP/health pra titioner)
2. Who is the driver (CCG/commissioner/pharmacist/consultant)
Definition of what a pathway is
3. Data governance (relevance) - transparency/interoperability
Group Members
Zoher Kapacee - zoher.kapacee@manchester.ac.uk - UoM
Zabeda Ali-Fogarty - zabeda@esp-it-consultancy.com - ESP IT Consultancy
Roger Wallhouse - roger@healthsys.com - Health System Solutions Ltd.
Reg Tabb - reginald.tabb@bms.com - Bristol-Myers Squibb Pharmaceuticals
John King - john.king@ethos-partnership.com - Ethos Partnership
Joanna Balderstone - joanna.balderstone@bms.com - Bristol-Meyers Squibb Pharmaceuticals
Adam Slawson - adam.slawson@fluxx.uk.com - Fluxx
Ken Hsu - ken.hsu@healthwatchmanchester.co.uk - Health Watch Manchester
Ben Waterhouse - bwaterhouse@caci.co.uk - CACI Ltd
Opportunities
Shared experiences
Definition of care pathways (knowledge)
Portal to allow patients to input symptoms
(decision tree)
Identify variability in antimicrobial
infections
Research into individual prescribing
practices
Knowledge bank specifically for patients
- Monitoring outcomes
Educating practitioners (convert know how
into defined process)
Set up a test GP – a place to test ideas and
collect data from real patients
Artificial intelligence
- ANI = now
- What about AGI and ASI – 30 – 45 years
from now
Barriers
Identify buyers (payer evidence)
True understanding of cost/benefit
Data governance – privacy/security
- How can data on an individual level be
used
Change in behaviour = practitioners and
patients
What are emotional nudges we can text? E.g.
? e.g.?
Who are the people along the prescription
journey and what are their journeys/needs?
Why are patients asking for antibiotics?
What’s the patie t/GPs e otio al jour ey?
Analysis into information delivery e.g. letters
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Greater Manchester CHC Care Pathways
Building Rapid Interventions to reduce antimicrobial resistance & over-prescribing of antibiotics (BRIT)
Potential for Scalability
Self-monitoring
- Benchmarking peers
- Access to ring fenced appointments – coughs and colds – (capacity freed from reduced prescribing)
- Generates research data
Feedback Points
1. Need comprehensive data to see impact of problem moving through health system
- patient reported
- 1 °/2 °/social care/community
Group Members
Lisa Dutton - Lisa.Dutton@srft.nhs.uk - NIHR CLAHRC Greater Manchester
Rosemary McCann - rosemary.mccann@phe.gov.uk - Public Health England
William Dixon - Will.Dixon@manchester.ac.uk - UoM
Andrew Dodgson - andrew.dodgson@cmft.nhs.uk - Public Health England
Adrian Parry-Jones - adrian.parry-jones@manchester.ac.uk - UoM
Chris Ashton - christopher.ashton@srft.nhs.uk - GM Stroke ODN
Opportunities
Mass education e.g. viral disease
Understanding neutral (untreated) history.
Self-reported daily symptoms –
benchmarking
Breadth of data in CHC
- 1 °/2 °/social care/community
Barriers
Strap beliefs + traditions in clinical practice
Self-interest > greater good
Consultation time
Risk of shifting problem acute care e.g.
age
Concerns about missing infection and not
treating
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Greater Manchester CHC Care Pathways
A Learning Health System for stroke care in Greater Manchester
Potential for Scalability
Algorithm built in to detect long term >130 mm/Hg systolic BP
Gameification – success rate
Use tech to plan and coordinate patient journey better
Lea a d uild o lesso s f o ig usi ess that is u i uitous i life to o st u t a ette e-2-e pathway –
etickets etc
Importance of linking data and patient interface i.e. pharmacy/secondary care appointments/social care
portal
Feedback Points
1. Retrospective review of all mimics should be 25% currently 50%
2. Transmission of data from Paramedic/NWAS to stroke
3. Collaboration with industry to develop app for workstream 2
Group Members
Ruth Norris - ruth.norris@manchester.ac.uk - UoM
Kieran O'Malley - kieran.omalley@manchester.ac.uk - UoM
Chris Hart - christopher.hart@astrazeneca.com - Astra Zeneca
Lisa Bennet - Lisabennett.work@gmail.com - Quintiles
Steve Hilton - steve@libertyapps.co.uk- Liberty Apps
Gary Clarke - gary.clarke@manxtelecom.com - Manx Telecom
Opportunities
Triage – Facial recognition software
Transmission of data
NWAS – stroke unit. Divert en-route if
necessary
Retrospective review of all stroke patients.
Comorbidities?
HER in ambulance
Barriers
Collecting FAST criteria
Feeling of being audited
Real time data transmission remote areas
Security/encryption
Time pressures/morbidity action
Cost
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Page 66 of 78
Greater Manchester CHC Care Pathways
A Learning Health System for stroke care in Greater Manchester
Potential for Scalability
Large potential to scale nationally
Feedback Points
1. Potential to extend to outside the hospital
2. Include to ambulance/GP/community
3. Information is stored as rapidly as possible
Group Members
Zabeda Ali-Fogarty - zabeda@esp-it-consultancy.com - ESP IT Consultancy
Roger Wallhouse - roger@healthsys.com - Healthcare Systems Solutions Ltd.
Paul Turner - p.turner@wigan.gov.uk - Wigan Council
John King - john.king@ethos-partnership.com - Ethos Partnership
Ken Hsu - ken.hsu@healthwatchmanchester.co.uk - Health Watch Manchester
Niels Peek - niels.peek@manchester.ac.uk -UoM
Opportunities
Protection and prevention e.g AF
Connecting from different locations in multi-
disciplinary environments
Getting the ambulance service involved
Emergency services training telemonitoring
Transfers
Barriers
Technologies – mobile tech variation
Behaviours – patient, - staff
Stakeholders for cost/investors/buyers
Adapting to changes
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Greater Manchester CHC Care Pathways
A Learning Health System for stroke care in Greater Manchester
Potential for Scalability
Focus care on these people most at need via traffic light system
Feedback Points
1. Video triage in ambulance?
2. improved self-monitoring/adherence
3. Machine to machine data management traffic light system (for recurrence in primary care)
Group Members
Matthew Machin - matthew.machin@manchester.ac.uk - UoM
Stephen Melia - stephen.melia@manchester.ac.uk - UoM
Sarah Knowles - Sarah.Knowles@manchester.ac.uk - UoM
Christopher Etchells - chris.etchells@kmswristband.com - KSI Solutions
Keli Shipley - keli.shipley@adi-uk.com - ADI Health
David Park - david.park@cisco.com - Cisco Systems
Opportunities
Video triage in ambulance
Patient self-management/self-tests
Improve adherence using wearable tech etc
Link specialist/primary care data
Improve monitoring via tech – i.e. patients
at risk to reduce load on primary care
Barriers
Does it help diagnosis?
Time for professionals e.g. GPs
Nobody accountable for overall care
pathway
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Greater Manchester CHC Care Pathways
A Learning Health System for stroke care in Greater Manchester
Potential for Scalability
Paramedics - Specialist advice centre
Feedback Points
1. Potential to extend to outside the hospital
2. Include to ambulance/GP/community
3. Information is stored as rapidly as possible
Group Members
Opportunities
Electronic transfer of information directly
into GP work flow (LPRES example)
Wearable technology
Monitoring apps – practice nurses
- Practice nurses
- Algorithms?
- Decision support
Telehealth e.g. Liverpool CCG
Family involvement
Careplan
Barriers
Stroke prevention - Poor sharing of
information between hospital and primary
care
Ambulance – poor decision support for
paramedics on scene: consequences of
getting it wrong
- Decision support
- Asking a clinician
- Doctors working differently – tariffs, job
plans, availability
- Paramedic – specialist advice centre who
have patient data, video, vital signs,
decision, health records
–
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Greater Manchester CHC Care Pathways
A Learning Health System for stroke care in Greater Manchester
Potential for Scalability
Use of technology to assist decision making in ambulance service beyond stroke
Use of interventions beyond GM
Feedback Points
1. Use of technology: patients, paramedics – streamline processed – improve outcomes, and hospitals
PREDICTION
2. Changing culture and behaviour
3. Accessing data from diverse datasets
Group Members
Ian McKenna - iMcKenna@galen-research.com - Galen Research
Catherine Headley - Catherine.Headley@manchester.ac.uk – UoM
Mike Burrows - mike.burrows@gmahsn.org – GMAHSN
Azad Dehghan - a.dehghan@manchester.ac.uk – UoM
Sarah Rikard - sarah.rickard@srft.nhs.uk - GM Stroke ODN
William Welfare - william.welfare@phe.gov.uk - Public Health England
Stephen Lee - steve.p.lee@philips.com – Phillips
Anna Jenkins - anna.jenkins@liverpool.ac.uk - Uni of Liverpool
Opportunities
1. - Training + understanding
- technology used to feedback from
paramedic to expert
- using other things than FAST
- use of a tablet/app to record information
2. – Cultural change with approach to
intervention
- Flow of information between departments
+ decision points/makers
3. – Blood pressure management – overlap
with many other conditions
- use of wearables in high risk groups –
warning system algorithm, - large benefits
for relatively small group
Barriers
Accessing and using data from diverse range of
sources
1. How ambulance crew operate
Changing behaviours – paramedics, -
patients
2. Cultural assumption that there will be a
poor outcome
- diverse sources of data – ambulance,
A&E, stroke unit, neurosurgery
3. Timescales for flow of information and
action within 1 month risk period of
recurrence
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Greater Manchester CHC Care Pathways
A Learning Health System for stroke care in Greater Manchester
Potential for Scalability
Missing people
False -
False +
Acute in they’re in the right place
Feedback Points
1.
2.
3.
Group Members
Opportunities
Decision support to identify ~genuine” strokes
Point of care testing? In ambulance better
communication
Machine learning to identify exceptions
Barriers
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Greater Manchester CHC Care Pathways
A Learning Health System for stroke care in Greater Manchester
Potential for Scalability
Patient empowerment; apps to monitor and record BP – integrate this into NHS primary and secondary care
record
Test bed of NHS or patients/prototyping, stroke association app
Cross learning between RA and CVA
Feedback Points
1. Develop a repository for patient derived data that can be accessed by clinical staff with as low a barrier as possible
2. Set a vision
Group Members
Chris Ashton - christopher.ashton@srft.nhs.uk - GM Stroke ODN
Lisa Dutton - Lisa.Dutton@srft.nhs.uk -NIHR CLAHRC Greater Manchester
Adam Slawson - adam.slawson@fluxx.uk.com - Fluxx
Adrian Parry-Jones - adrian.parry-jones@manchester.ac.uk - UoM
Graham DeAth - graham.death@ethos-partnership.com- Ethos Partnership
Rosemary McCann - rosemary.mccann@phe.gov.uk - Public Health England.
Opportunities
Apps already available
Patient and priorities – fatigue
RTW; emotional support
Motivate people – BP: AF
Impact of AI in next 25 years
Setting an ideal for the experience of
pathway
Evaluate interventions at each stage of
pathway and how each affects outcome
Simulation solutions population level
Barriers
Inability to integrate data from monitoring
app in ESR
Changing culture of clinicians and NHS
system
Busyness versus Business
Patient preference for local hospital
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