health north: connected health cities · what will the outcomes be? validated methodology,...

The Need

Despite huge advances in in knowledge and technologies,

chronic disease burdens are increasing with longevity and lifestyles;

care costs are escalating; and new threats such as anti-microbial

resistance are met with few countermeasures.

The UK’s National Health Service (NHS) is required to deliver

£20 billion of efficiency savings in an economic climate that predicts

little or no growth.

40-50% of NHS Trusts overspent in 2014/15, and the 2016 projected

deficit is £2.3 billion.1

Manchester, Blackpool, Liverpool and Salford all located in the North

of England have the highest early mortality rates in England, and

overall the chance of dying under age 75 is >20% higher in the North

of England compared with the South.23

Health North

Health North is a Government initiative operating across North England (15 million population) to generate

innovations that can deliver more effective and efficient health and social care.

The foundations of Health North are to:

establish a social contract with citizens that gives license to use health data for public good;

produce timely and actionable information from patient and population data;

use new intelligence sources to understand pathways of care across different provider organisations and

to target resources to needs in much more agile and specific ways than at present; and

to accelerate business growth in the digital health sector in North England.

Connected Health Cities

Connected Health Cities will be piloted in four city regions in its first phase, with the common principles of:

Engaging and involving the public to build public trust and civic partnerships.

Working with data custodians and existing infrastructure at local, regional and national level to create

linked-data critical masses for deeper understanding of health in defined populations.

Developing at the heart of each city region an Ark – a secure, combinatorial data analytics facility, with

state-of-the-art data management and analysis tools, underpinned by research, education and training.

Bringing people from academia, NHS and industry into deep collaboration in the Ark, working in

partnership to create new knowledge that will inform decision-making at levels.

The aim is to pilot data-intensive health service optimisation methodology and understand how it can work

efficiently in city regions, then to network those regions so they can ‘borrow strength’.

1 King’s Fund report on NHS Trusts’ deficit: www.kingsfund.org.uk/press/press-releases/nhs-trusts-deficit. 2 Hacking JM, Muller S, Buchan IE. Trends in mortality from 1965 to 2008 across the English north-south divide: comparative observational study. BMJ. 2011;342:d508. 3 Mortality Rankings, Public Health England: http://healthierlives.phe.org.uk/topic/mortality/comparisons.

Health North: Connected Health Cities

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http://www.kingsfund.org.uk/press/press-releases/nhs-trusts-deficit

http://healthierlives.phe.org.uk/topic/mortality/comparisons

What will the outcomes be?

Validated methodology, delivering actionable information to health, social care and citizens, reducing the

time lag between data being available and appropriate actions being taken (data-action latency).

A new model for civic partnership, where trust is built and sustained through on-going public engagement

and the use of data is open and transparent.

Platform technology and tools, delivering actionable information to healthcare, social care and citizens,

reducing data-action latency.

New economic development in the North of England in/around the digital health innovations of the

Connected Health Cities.

Greater engagement and empowerment of citizens to take control of their healthcare, contributing to

health system optimisation.

Digital health innovation network building across the Health North partnership – sharing knowledge and

multiplying assets.

Increased capacity and capability of the data scientist workforce.

How will Health North work with Industry?

Industry partnership is essential and integral to Health North, especially with the following sectors:

enterprise IT; health IT; medical therapies and medical devices; digital health; and SME’s.

Health North, with industry partners, aims to fundamentally change the way data, information and knowledge

are produced, collected, analysed and acted upon in health and social care.

The goal is to enable continuous improvement and optimisation with the following benefits:

Health and social care providers will benefit from improved outcomes and greater efficiency in service

delivery and management.

Academia will generate deeper and timelier outputs with more impact.

For industry, Health North will establish the conditions in which data-rich healthcare innovation is

required thus opening new markets.

Citizens and communities will receive more personalised care, optimised to their needs that delivers

improved health outcomes.

Governance

The Health North pilot project is funded by the UK’s Department of Health and delivered by the Northern

Health Science Alliance (www.thenhsa.co.uk).

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http://www.thenhsa.co.uk/

Greater Manchester CHC Care Pathways

Antibiotics are used to kill bacteria when we get an infection or to protect us when our immune systems are vulnerable.

At the moment we are facing a crisis in public health. The bacteria are becoming more resistant to the antibiotics and as a result they are becoming less effective, in the future there’s a chance they might stop working completely.

One of the reasons for this is over-prescription. Antibiotics are being given out too often and the bacteria are becoming immune to them. This project, delivered by the Greater Manchester CHC, is developing a tech savvy solution to help understand and tackle the problem.

By making better use of health data and presenting this in a more powerful way the researchers working on this project believe they can start to reduce the UK’s reliance on antibiotics.

By accessing anonymous GP records, A&E departments and out-of-hours clinics the team will be able to understand which services are prescribing the most antibiotics and also understand the consequences of these prescriptions. All of this data is kept in the medical records and by applying the latest computer programming the information can be sent to a secure environment to be analysed.

The results of these analyses can then be displayed in easy-to-understand and visual ways so that GPs can understand how their surgery compares to others in the same city. The system will also allow GP’s to access more detailed information about symptoms and guidance to ensure they only prescribe antibiotics when they are required by the patient.

@Man_Inf @CHCNorth @GM_AHSN #McrEcosystem www.manchesterecosystem.org.uk

Building Rapid Interventions to reduce antimicrobial resisTance & over-prescribing of antibiotics (BRIT)

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Greater Manchester CHC Care Pathways

The signs of a stroke can begin suddenly. Often, it’s a paramedic that is the first person to assess a patient suffering from stroke and depending on how severe their symptoms are they may be taken to a specialist stroke unit or to their local hospital.

There is a lot of support available for people that have had a stroke. This support can come from GPs, doctors working in specialist units, from local hospitals and out in the community. Each of these services record information in their databases but there isn’t any way for doctors, health professionals and researchers to get an overview of how patients flow through and in-between services.

Researchers working on this project will analyse data from different stroke services to develop a comprehensive overview of how stroke patients pass between primary, secondary and community care in Manchester and Salford. Not only will they better understand the patient journey, they will also be able to spot gaps in the care that is offered and suggest improvements to support stroke patients and ensure services are efficient and well-coordinated.

This project will look at four specific aspects of the existing stroke care pathway.

1. Improving the recognition of stroke by paramedics to maximise the proportion of acute stroke patients taken directly to a specialist stroke centre for timely expert care and minimising the number of non-stroke patients entering the stroke pathway.

2. Providing timely and focused referral to neurosurgery for patients in Greater Manchester with stroke caused by brain haemorrhage.

3. Ensuring that all patients get all the right treatments that they need to reduce the risk of another stroke when they are discharged from hospital.

4. Making sure those patients who are ready to be discharged to the community do not have unnecessary and expensive delays in hospital beds.


A Learning Health System for stroke care in Greater Manchester

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0900 - 0930 Tea, Coffee & Registration

0930 - 0935 Welcome & Introduction Update on the Manchester Ecosystem

Dan Morley (Business Development Manager, Manchester Ecosystem)

0935 - 0955 Health North & Connected Health Cities: Developing a Learning Health System

Dr Niels Peek (Director, GMConnected Health Cities)

0955 - 1020

Building Rapid Interventions to reduce antimicrobial resisTance & over-prescribing of antibiotics (BRIT)(inc. Q & A)

Prof Tjeerd van Staa (Professor of Health Informatics, Health eResearch Centre)

1020 - 1055 Workshop Discussion Groups - opportunities for engagement All

1055 - 1110 Discussion Group Feedback All

1110 - 1120 Refreshment Break

1120 - 1145

A Learning Health System for stroke care in Greater Manchester

(inc Q&A)

Dr Adrian Parry-Jones (NIHR Clinician Scientist, UoM & Honorary Consultant Neurologist, Salford Royal FT)

1145 - 1220 Workshop Discussion Groups - opportunities for engagement All

1220 - 1240 Discussion Group Feedback & Further Questions All

1240 - 1250 Next Steps Dr Niels Peek

1250 - 1300Informatic for Health 2017 & other upcoming events

Ruth Norris (Research Programme Manager, HeRC) & Dan Morley

1300 - 1345 Lunch & further networking


Meeting Agenda

GM Connected Health Cities Care Pathways Roadmap & Opportunities to Engage

Thursday 3rd November 2016The Hive, 51 Lever Street, Manchester

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GM Connected Health Cities Care Pathways Roadmap & Opportunities to Engage

Today’s Delegates


Keli Shipley ADI HealthCatherine Armshaw Armshaw AssociatesChristopher Hart AstraZeneca Paul Booth BEAJoanna Balderstone Bristol-Myers Squibb PharmaceuticalsReg Tabb Bristol-Myers Squibb PharmaceuticalsBarry Whittaker BT PlcGraham James CACI LtdDave Prime CACI LtdBen Waterhouse CACI LtdAndrew Michaelson Care Innovation LimitedJulie Harrison Central Manchester Foundation Trust Steve Leggett Cerner UKDavid Park Cisco SystemsZoher Kapacee Connected Health CitiesClaire Smith Connected Health CitiesNeil Murphy Converging DataBrian Bishop Data Performance Consultancy LtdChris Haynes Data Performance Consultancy LtdKeith Miller Department for International TradeRob Halhead Docobo LtdZabeda Ali-Fogarty ESP IT Consultancy LtdGraham DeAth Ethos PartnershipJohn King Ethos PartnershipHelen Beaumont-Kellner EuroKing Maternity Software Sarah Barnes EYJohn Farenden EYIan McKenna Galen ResearchMike Burrows GM AHSNLauren Constable GM AHSNGary Leeming GM AHSNJane Macdonald GM AHSNDai Roberts GM AHSN

Thursday 3rd November 2016The Hive, 51 Lever Street, Manchester

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Sarah Thew GM AHSNJo Hobbs GM Connected Health Cities Niels Peek GM Connected Health Cities Chris Ashton GM Stroke ODNSarah Rickard GM Stroke ODNTjeerd van Staa Health eResearch Centre Roger Wallhouse Health Systems Solutions LtdKen Hsu Healthwatch ManchesterSimon Radcliffe Hearst Health InternationalTony Bowden Helicon HealthTim Meehan Horizon SciTech LimitedDebbie Parkinson Innovation Agency North West CoastAdrian Owen Insource LtdChris Etchells KMS SolutionsSteve Hilton Liberty AppsRosy Leo LumiraDxSumit Nagpal LumiraDxDan Morley Manchester EcosystemMia Belfield Manchester Ecosystem Isabel Fisher Manchester Ecosystem Michael Daw Manchester Metropolitan UniversityGary Clarke Manx TelecomCraig Wood Map of MedicineAndrew Holland MaywoodsPeter Jenkinson Middleforth Green Consulting LtdMaria Gonzalez New EconomyLisa Dutton NIHR CLAHRC Greater ManchesterKaty Rothwell NIHR CLAHRC Greater ManchesterPeter Harrison Nokia TechnologiesMarie Kane NWEHLiz Ashall-Payne ORCHAAndy Jeans ORCHASteven Lee PhilipsPhil Sinclair PhilipsAndrew Dodgson Public Health EnglandAlex Keenan Public Health EnglandWilliam Welfare Public Health EnglandRosemary Mc Cann Public Health England John McGovern Quaenam LtdLisa Bennett QuintilesLu Rahman Rapid NewsNawar Bakerly Salford Royal NHS Foundation Trust


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Rachel Dunscombe Salford Royal NHS Foundation TrustKyriaki Paroutoglou Salford Royal NHS Foundation TrustGrant Churnin-Ritchie SASDarren Buckley SiemensChris Larkin Stroke AssociationSamantha Aspinall System CMatt Fairley System CAnna Jenkins University of LiverpoolJason Kennedy The Christie NHS Foundation TrustMatt Cope The Improvement NetworkCarmel Dickinson The University of ManchesterWilliam Dixon The University of ManchesterRoger Harrison The University of ManchesterCatherine Headley The University of ManchesterSarah Knowles The University of ManchesterMatthew Machin The University of ManchesterStephen Melia The University of ManchesterRuth Norris The University of ManchesterKieran O’Malley The University of ManchesterAdrian Parry-Jones The University of ManchesterCharlotte Stockton-Powdrell The University of ManchesterPhilippa Tyrrell The University of ManchesterSavvas Neophytou Torafugu techPaul Hanmer TRUSTECHMark Claydon TRUSTECH Manoj Ranaweera UnifiedVUPaul Turner Wigan Council


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03-11-16

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The Greater Manchester Connected Health City

Niels Peek Director, Greater Manchester Connected Health City

Health e-Research Centre Farr Institute of Health Informatics Research

The University of Manchester

GM Connected Health Ecosystem meeting, 3rd November 2016

1.  What is “Connected Health Cities”?

2.  What are the elements of the programme?

3.  What is specific to Greater Manchester?

4.  What are the opportunities for business engagement?

Menu

Objectives:

•  social license to use health data for service redesign

•  produce actionable information from health data

•  accelerate business growth in the digital health sector

Health North

Health North

Powering UK Health and Wealth Transformation

A proposal from the Northern Health Science Alliance

•  2016 – 2019

•  £20m

•  Four regions –  Greater Manchester

–  North West Coast –  Yorkshire and the Humber –  North East and North Cumbria

•  One coordinating centre

•  ~2 pathways per region

•  Arks for clustering intelligence

Population densities: North England 2012

Connected Health Cities

An integrated healthcare system which harnesses the power of data and analytics to learn from every patient, and feed the knowledge of “what works best” back to clinicians, public health professionals, patients, and other stakeholders to create cycles of continuous improvement.

Key metric: data–action latency

What is a learning healthcare system?

Charles P. Friedman

Friedman C et al. Sci Trans Med 2010 Nov;2(57):57cm29.

How to learn: “virtuous cycles”


a problem of interest

collect data

analyse data

interpret results

decision support

take action

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03-11-16

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The LHS infrastructure is the platform that supports learning


LHS Infrastructure: A Single Platform Supports Multiple Simultaneous Learning

Cycles

13

Different Problems

Rapid Cycle

Slower Cycle

SUPPORTING PLATFORM

1.  What is “Connected Health Cities”?




Menu

1.  Civic partnerships

2.  Care pathway redesign projects

3.  "Arks” for clustering intelligence

4.  Learning health system methodology

5.  Growth of the digital health economy

CHC Programme elements Civic partnerships

Informa(onGovernance

Privacy Impact Assessment"Data sharing Agreements"

PublicEngagement#datasaveslives"

Citizen Juries"Data Donation"

Ci(zensPortal

Dynamic consent"Data feedback"

Social Licence"for re-use of health data"

North West Coast •  Alcohol misuse •  Preventing unscheduled

care in COPD

Yorkshire and the Humber •  Urgent and emergency care •  Healthier child growth

•  Self-management care for frail older people

Care pathway redesign projects

North East & North Cumbria •  Dementia and frailty •  Troubled families

•  Forecasting emergency unplanned care

Greater Manchester •  Antibiotic stewardship •  Stroke

•  Community wound care

For details see www.connectedhealthcities.org

2015:Dilute,DuplicatedDataProcessing 2020:ArkIntegratedDataProcessing

NHSCommissioning

ResearchandInnovation

PublicHealthIntelligence

SocialCareManagement

RawData

NHSQualityIntelligence

Extract,clean,describex5

Onesizefitsall

Ark

PublicInvolvementNHSCommissioning

NHSQualityIntelligencePublicHealthIntelligenceSocialCareManagement

Self-careandPersonalHealth

RawData

Extract,clean,describex1

CombinatorialResearchandInnovation

Literature

Policies

Literature

Policies

TargetingSystem

TransparentInterface

withIndustry

“Arks” for clustering intelligence

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03-11-16

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1.  What is “Connected Health Cites”?




Menu •  2.7M people with low life

expectancy and high inequalities

•  £56 billion GVA (fasted growing city region)

•  £6 billion annual care budget

•  moved out of England’s economic control from April 2016 (“DevoManc”)

•  Farr Institute / HeRC

•  existing and emerging infrastructures for data sharing (Datawell, GM Connect)

•  Internet of Things demonstrator (CityVerve)

Greater Manchester

GM-CHC Ark

3""

practices seamlessly embedded in the delivery process and new knowledge captured as a by-product of delivering care. Our CHC will bring together key stakeholders: health and social care commissioners and providers, public health professionals, academics and local government, with a shared commitment to improve health and care. At the core is the Ark that will aggregate data from different sources and produce timely, actionable intelligence, which the partners and citizens of GM will use to implement change. Importantly, the GM identity of the Ark will help to gain the public trust needed for the CHC to exploit its data fully to improve health and care, drive public sector reform, and accelerate economic growth. The GM CHC will build a civic partnership with a combination of public engagement events, mass participation experiments and targeted communications. Studies of the general public consistently show enthusiasm to donate data for health and social care research, yet the models currently employed for consent fail to build public trust and are counter-productive. We will develop the architecture for a dynamic consent system, where citizens are in control of how their health and social care data are shared and used, with feedback about the recipients of their data and the results of analysis. Our aim is to use this technology to enable us to establish a long-term partnership built on trust. The GM CHC will reuse the HeRC Trustworthy Research Environment (TRE) facility that is located within Vaughan House on the main University of Manchester campus. This provides the compute, storage and networking required by the CHC. The HeRC TRE has a direct connection to the NHS N3 network to enable secure data transfers between the Ark and NHS partners. The compute and storage is in excess of 450 cores with 150Tb of storage delivered through an openStack private cloud. Additional compute is provided with a high assurance link to the N8 HPC, specifically a 256core/4Tb RAM SGI UV200. The facility is also connected to the Farr Institute centres. Remote access to virtual machines is provided with two-factor authentication. The facility has NHS IGTK level 2 and is in the process of certification to ISO 27001. The GM CHC will contribute resource in kind to the HeRC TRE to administer the facility. The HeRC TRE will be added to the GM AHSN’s DataWell infrastructure as a research node, this will enable integration of the GM Ark into the GM Data sharing and integration infrastructure which will evolve over time in line with the Health Innovation Manchester informatics strategy.

Figure 1 Schematic of the GM CHC Ark

Data analytics capability will build on best of breed open source technologies such as Hadoop, Hbase, Zookeeper, Spark, Oryx and MlLib, or where appropriate by partnering with industry to bring in domain specific capability and expertise. Digital assets produced

ARK

ArkOffices,PublicEngagementSpace-CityLabs

SecureDataAnaly?csHeRCTRE

SecureRemoteAccess

GovernanceBoard

TRE:ISO27001ISMS

NHS:NHSIGTK

DataStorage

VirtualMachines

NHS

eLab

VirtualMachines eLab

2factorauth 2factorauth

DataStorageArchive

AAAI

N8HPCJanetHANN3

Ops,Admin,Mngmnt

Spin–inspace,Industryco-lab-CityLabs

DSCRO,HSCIC

Datawell

PSN

1.  What is “Connected Health Cites”?




Menu •  Pre-competitive collaborative consortium

•  Spin-in lab

•  Enrichment of care pathway redesign projects [today]

Opportunities for business engagement

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03-11-16

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•  Pre-competitive collaborative consortium

–  Led by the CHC coordinating centre

–  E.g., interoperability / standard messaging knowledge exchange distributed ledger technology



•  Spin-in lab

–  Specific to GM

–  Controlled access to health data

–  Focus on product development and validation


IMO-Salford Automation of Clinical Coding

WilliamDixon

HospitalNo.0123456

Date/TimeofAppt:28thJuly2015at09:00

Clinic:RHEUMATOLOGY

TypeofAppt:Follow_Up

RheumatologicalDiagnoses: Osteoarthritis

Fibromyalgia

Anxietyanddepression

PreviousvitaminDdeficiencyFracturedRhumerus2010SymptomsofCTS:NCS–veNosignofinflammatorychangeonMRspine2014ANA+ve1:1000

Non-RheumatologicalDiagnoses:

IschemicheartdiseaseleadingtoSTelevationMI2006

TypeIIdiabetes

Migraine

Restlesslegs

PreviouslyelevatedLFTs?cause

Medication: Naproxen Bisoprolol Simvastatin Amitriptyline30mg AdcalD3forte

MrDixonattendedtheclinictodaywithongoingsymptomsoffatigue….

Aim: To automatically extract clinical codes from semi-structured and unstructured clinical texts

Organisations involved: Intelligent Medical Objects Salford Royal NHS Foundation Trust The University of Manchester

Pilot study: •  100 outpatient letters from rheumatology unit

•  semi-structured lists of diagnoses •  comparison with manual coding by clinical experts •  narrative will follow later

IMO-Salford Automation of Clinical Coding


•  Spin-in lab

•  Enrichment of care pathway redesign projects [today]

–  Specific innovations within selected care pathways

–  Focus on marketable/commissionable products

–  Should extend scope of projects

–  Will require investment from industry partner

–  Soft procurement


What you get from us:

•  Funded development of infrastructure to support learning health system

•  Expertise in health informatics (data flow)

•  Expertise in data analytics

•  Expertise is decision support technologies

•  Shared interests in digital health to support care +/- NHS partnership

Partnership (or: Why bother?)

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03-11-16

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Thank you

Niels Peek GM Connected Health City The University of Manchester, UK

[email protected]

@NielsPeek

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Building Rapid Interventions to

reduce antimicrobial

resisTance and over-

prescribing of antibiotics (BRIT)

TP van Staa UoM

Andrew White NHS

William Welfare PHE

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Overuse of antibiotics: what to do?

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Antibiotic prescriptions in England in 2015

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Are London practices better than the rest?

0

2

4

6

8

10

12

0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+

% o

f r

eg

iste

re

d p

atie

nts

Age range (years)

Male

Greater London

England without London

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Variability in prescribing in respiratory tract infections [Gulliford BMJ Open. 2014 Oct 27]

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https://www.ncbi.nlm.nih.gov/pubmed/25348424

Figure 2

The Lancet 2016 387, 1743-1752DOI: (10.1016/S0140-6736(16)00215-4) Copyright © 2016 Hallsworth et al. Open Access article distributed under the terms of CC BY-NC-ND

Terms and Conditions of 78

http://www.elsevier.com/termsandconditions



What does this mean?

• Prescribing variation suggests practice ranging from sub-optimal to potentially unsafe

• Clinical risks of prescribing?

– Over - Side effects, interactions, wasteful, harm

Law of diminishing returns?

– Under – missed opportunity, unnecessary harm,

• Financial impact is considerable

– Not ‘Best value, Best care or Best Health’

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Antibiotic prescriptions in Greater Manchester in 2015

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What if current prescribing rates are reduced?

Target

Required reduction in number of prescriptions per year to achieve target

Greater Manchester (no. of GP practices=476)

England (no. of GP practices=7854)

46 antibiotic prescr. per 1000 patients (1st quartile)

467 826 7 949 105

55 antibiotic prescr. per 1000 patients (Median)

238 484 3 895 117

64 antibiotic prescr. per 1000 patients (3rd quartile)

91 288 1 605 832

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Date of download: 11/2/2016 Copyright © 2016 American Medical

Association. All rights reserved.

From: Frequency of First-line Antibiotic Selection Among US Ambulatory Care Visits for Otitis Media, Sinusitis,

and Pharyngitis

JAMA Intern Med. Published online October 24, 2016. doi:10.1001/jamainternmed.2016.6625

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Aims of BRIT

• Improve actionable data analytics

• Increase use of actionable data analytics by NHS staff

• Implement interventions to reduce antibiotic prescribing

• Develop the capabilities to target right antibiotic to right patient

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Data selection flowchart

Total number of

prescriptions in CPRD

database

1 468 651 812

Number of incidental

antibiotic

prescriptions

42 671 744

Number of antibiotic

prescriptions

meeting QA criteria

32 793 768

Number of diagnostic

read codes associated

with prescriptions

12 650 333

Number of read codes

with more than one code

per patient per day

1 944 607

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Improve actionable data analytics

• Drivers of antibiotic prescribing: do they explain variability? => expected probability score for antibiotic prescribing in practice versus observed

• Risks of prescribing antibiotics

– Side-effects => Risk in patient aged 40-49 etc – Medicalisation of simple infections => e.g. doubling in GP visits when prescribed an antibiotic

• Futility of prescribing antibiotics – More prescribing, better outcomes? – Effects of co-morbid conditions => e.g. risk of infection-related hospital admissions

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Identification of clusters with different

clinical codes Find patients with similar clinical characteristics/codes: then, why do

some get antibiotics and others not (drivers) and what cluster with

largest variations in prescribing (these to target for interventions)?

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Increase use of actionable data analytics by NHS staff: e-Lab

… a web-based software application bringing together people, data and methods

People with relevant expertise and authorisation

State-of-the-art algorithms

Dashboards

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Implement interventions to reduce antibiotic prescribing

• Simple targeted interventions

• Tailored behaviour change interventions / social influence

• targeted at prescribers • targeted at patients (e.g. in patients with previous

unnecessary antibiotic prescribing or at communities with higher expectations of antibiotic prescriptions

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Develop the capabilities to target right antibiotic to right patient (longer-term)

• ‘Green button’ in EHR: – Risk of complication based on patient’s history

– Variability between GPs

– Guideline and antimicrobial advice (based on local resistance)

• Digital capture of patients’ symptoms – After booking appointment

– Access to information material

• Integration of patient and EHR data – Real-time analytics and interpretation

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Opportunities with BRIT

• Data analytics and visualisation: how and what to present

• Communication to patients (e.g. what is natural course of disease) using alternative approaches

• Better capture of symptoms by patients (iPads/web based) => actionable information!

• Dynamic prediction algorithms (based on on EHRs/patient data) to guide prescribing based on local resistance data / risks of adverse outcomes / guidelines

• And probably much more!

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A Learning Health System for stroke care in Greater

Manchester

Adrian Parry-Jones MRCP PhD

NIHR Clinician Scientist & Honorary Consultant Neurologist

Manchester Academic Health Sciences Centre

Salford Royal NHS Foundation Trust, Salford, UK

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Stroke: a common problem

In the UK:

• 152,000 strokes/year

• 1.2 million stroke survivors

• £9 billion in economic costs

(£4.38 billion health/social)

Poor outcomes:

• 1 in 8 die by 30 days

• Survivors:

• ½ have a disability

• ⅓ dependent

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Stroke: causes

Ischaemic stroke:

• 80-85% of strokes

• Occlusion of artery

• Clots from heart and neck

arteries

Intracerebral haemorrhage:

• 10-15% of strokes

• Rupture of artery with

bleeding in to brain

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Stroke: treatments

Ischaemic stroke (80-85%):

• Acute care: Stroke unit, reperfusion (thrombolysis/ clot retrieval),

prevention of complications (DVT, infections)

• Secondary prevention: antiplatelets, statins, blood pressure, AF –

anticoagulation, carotid surgery

Intracerebral haemorrhage (10-15%):

• Acute care: Stroke unit, reverse anticoagulation, blood pressure

control, neurosurgery

• Secondary prevention: blood pressure, review antithrombotics,

identify vascular malformations

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Greater Manchester stroke pathway

Illustration courtesy of Greater Manchester Stroke Operational Delivery Network of 78

Stroke Units in Greater Manchester

• Hyperacute Stroke

Units (HASUs):

Salford, Bury,

Stockport

• All other acute

hospitals are District

Stroke Centres

(DSCs)

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Greater Manchester stroke pathway

Illustration courtesy of Greater Manchester Stroke Operational Delivery Network

1 2

3

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Workstream 1: Stroke mimics

• GM Stroke ODN Audit Jan

2016:

• 480 of 969 patients

assessed were strokes

(49.5%)

• 79% of patients arrived by

ambulance

• 70% of mimics arrived by

ambulance

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Workstream 1: Stroke mimics

• Aims:

1. Describe patient flow and understand predictors for

stroke mimics using existing health data

• North West Ambulance Service (Stroke database, C3

dispatch system)

• DataWell (Salford, Central, South)

2. Test changes to improve system

• Individual feedback, telephone access to on-call stroke

teams, decision support systems

• Rapid assessment of impact via established data flows

(once NWAS EPR in place)

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Workstream 2: ICH care bundle & pathway

• Common health problem

‒ Causes 10-15% of strokes

‒ More common in southeast Asian

populations

• Poor patient outcomes

‒ Case fatality up to 40% at 1 month

‒ Causes 5.8% of all global deaths (vs.

6.0% for ischaemic stroke)

‒ Only 20% regain independence

‒ Little improvement in outcomes over

last 30 years

GBD Study 2013 collaborators(2015) Lancet 386:743–800; van Asch et al.(2014) Lancet Neurol 9:167-176 of 78


ABC Care bundle:

A – anticoagulant reversal

B – blood pressure control

C – care pathway

Salford QI project:

30-day case-fatality

• 34.3% before

• 25.1% after

Fall of 9.2% N=216 before (May 2014 – May 2015) N=311 after (Jun 2015 – Jul 2016)

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Aim: Reduce death and severe disability after intracerebral

haemorrhage in Greater Manchester by 10% by April 2018

Objectives:

1. Analysis of historic dataset to refine care pathway

2. Automated GM intracerebral haemorrhage registry

3. Development of app and dashboard to deliver bundle

4. Planed bundle launch April 2017

Funded by the Heath Foundation: Innovating for Improvement

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Workstream 3: Secondary prevention

• Blood pressure:

• Causes 50% of ischaemic strokes

• Principal risk factor for intracerebral haemorrhage

• Guidelines suggest lowering to below 130 mmHg

• Atrial Fibrillation:

• Accounts for up to 15-20% of strokes

• Caries high risk of further stroke ~ 12% p.a.

• Anticoagulation prevents 65-70% of strokes

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Amarenco et al, N Eng J Med 2016, 374: 1533-42

Recurrent events:

• Happen early

• Some preventable

Possible problems?

• AF detection

• Anticoagulation

• Control of blood

pressure

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Aim: Reduce the rate of recurrent strokes by rapid delivery

of secondary prevention

Objectives:

1. Describe AF and hypertension detection and

management using existing health data

• SIR & SSNAP

• DataWell (Salford & Central acute trusts and CCGs)

2. Test changes to improve system

• Enhanced role for ESD nurses, pharmacists

• Technology for patient self monitoring and detection

• Extended role for Stroke Association Co-ordinators

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• University of Manchester: Adrian Parry-Jones, Goran Nenadic

• Salford Royal: Pippa Tyrrell, Hiren Patel, Kyri Paroutoglou, Amit

Kishore, Luca Cecchini

• NIHR CLAHRC Greater Manchester: Ruth Boaden, Katy Rothwell,

Lisa Dutton

• GM Stroke ODN: Sarah Rickard, Chris Ashton, Jane Molloy

• Stroke Association: Chris Larkin

• North West Ambulance Service

• Pennine Acute Hospital Trust: Khalil Kawafi

• Stockport NHS Foundation Trust: Appu Suman, Shivakumar

Krishnamoorthy

CHC: Stroke Project team & collaborators

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health north: connected health cities · what will the outcomes be? validated methodology,...

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