digital healthcare and mhealth apps: promoters or barriers ... · 1. digital healthcare and mhealth...
TRANSCRIPT
Yorkshire Centre for
Health Informatics
Digital healthcare and mHealth apps:
promoters or barriers to integrated
care ?
Jeremy Wyatt DM FRCP ACMI Fellow
Leadership chair in eHealth research, University of Leeds
Clinical Adviser on New Technologies, Royal College of Physicians, London
Digital healthcare
“Supplementing or substituting interactive digital tools for
clinical, self management or health promotion activities”
Primary users can be health professionals, patients or
members of the public
Secondary users: those analysing the data captured for CQI,
research & other purposes
Why digital ?
• Convenience – the 24hr society – fix your
symptoms any time, any place
• The promise of unified health records [access
digital information anywhere]
• Opportunity for automated analysis, audit, decision
support, case finding, reminders…
• Never lose your records – on the cloud
• Efficiency of the digital channel…
£8.60
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£2.83
£0.15 £0
£1
£2
£3
£4
£5
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£9
£10
Face to face Letter Telephone Digital
Co
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in £
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co
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ter
Mean public sector cost per completed encounter across 120 councils
Source: Cabinet Office Digital efficiency report, 2013
The wide range of digital
healthcare tools
Tools for professionals:
• Electronic health records, ePrescribing...
• Tablets and apps to support bedside / mobile working
Tools for patients with LTCs:
• Skype consultations, txt msgs for reminders & test results…
• Apps, home monitoring, websites, social media etc. for self
management
Tools for the public:
• Phone / online triage tools for acute illness
• Apps, serious games etc. for health promotion…
Potential drawbacks of digital
• Equity of access – “cyberdivide”
• Getting people to use it
• Safety issues:
– Bad programming inside: miscoded algorithms / risk
scores
– Bad programming on the human interface
– Leakage of confidential clinical data
– Failure to share clinical data, leading to fragmented
records
• So, does it actually reduce resource use & save
money ?
Impact of pt. access to their record
on healthcare resource use
US cohort study comparing office visits per month in those who
did and did not take up online access to their records
Results: a significant increase in:
• The number of office visits (0.7 per member pa.)
• Phone calls (0.3 per member pa.)
• OOH visits (19 per 1000 members pa)
• ER visits (11 per 1000 members pa.)
• Hospitalisations (20 per 1000 members pa.)
Source: Palen, JAMA 2012
What does “Integrated care”
require ?
Integration across specialist services within same
organisation:
• Unique pt. identifier
• Coordination & sharing of data definitions, data capture &
data access
• Trust of users in data, software etc.
Integration across organisations:
• Exchange of pt. data, clinical protocols, service information
across organisational boundaries
• Even greater trust in “foreign” data, software, care protocols
Case study:
Building trust in mHealth apps
Apps: supportive evidence
Recent randomised trials of apps themselves:
• Self management by people with diabetes [Kirwan, JMIR 2013]
• “My Meal Mate” for reducing BMI [Carter, JMIR 2013]
Systematic reviews of mHealth in general:
• Computer based self-management in diabetes
[Pal, CDSR 2013]
• mHealth for HIV Treatment & Prevention
[Catalani, Open AIDS J 2013]
• mHealth technologies for service delivery
[Free, PloS Med 2013]
The variable quality of health apps
Developers publish apps: • with no named source of content (95%)
• after no apparent clinical contact (86%)
• with no evaluation to support their claims (100%)
Study of 112 chronic pain apps for public use: Rosser & Eccleston 2011
So, apps: 1. Raise privacy issues (10% of 600 popular health apps had privacy policy)
2. Can be expensive for clinician, consumer & health system
3. Give bad advice (eg. opioid drug dose converter - Haffey 2013;
melanoma risk tools - Wolf 2013; Leeds study on cardiovascular risk
apps)
Leeds study of CVD risk apps
19 cardiovascular risk prediction iPhone
apps (paid or free) for public use
15 scenarios, true 10 year risk varied from
1% to 75%
Results:
• Some apps limited age to 74, ignored diabetes
• Estimated risk on scenario with correct risk of
75% varied from 19% to 137% !
Heart Health App With Hannah Cullumbine & Sophie
Moriarty, Leeds medical students
Study on App privacy risks
All Apps ask for “permissions” at
installation:
• Some are legitimate, eg. access to
internet
• Many are not: access to contacts,
phone calls, browsing history…
Median of 4 privacy risks for lifestyle
Apps, 1 for medical Apps (p<0.001)
Heart rate App –
Cardiograph
With Hannah Panayiotou & Anam Noel,
Leeds medical students
How to promote higher quality Apps ?
Traditional strategies:
• Expert reviews by eg. iMedicalApps.com
• NHS review & branding
• Self-certification using eg. Health on the Net criteria
• User ratings and reviews (“wisdom of the crowd”)
• Regulation by MHRA, FDA etc.
New strategy: develop & promote app quality
criteria based on Donabedian’s model
Avedis Donabedian, Lebanese
physician, 1919-2000
User ratings: app display rank versus
adherence to evidence
Study of 47
smoking
cessation
apps (Abroms
et al, 2013)
Regulation of medical apps by FDA, FCC
If classified as a medical device by FDA a product must
demonstrate efficacy, but:
• Only 100 apps so far classified as a medical device
• Decision to exercise “enforcement discretion” on most medical apps
• So, FDA has not actually banned any apps, yet
However, the Federal Communication Commission has
banned some apps with misleading claims, eg. “Acne Cure”
(no evidence of claimed benefit of iPhone screen backlight)
Sharpe, New England Center for Investigative Reporting, Many health apps are based on
flimsy science at best, and often do not work. Washington Post, November 12th 2012
We need to think differently…
Old think New Think Paternalism: we know & determine what
is best for users
Self determination: users decide what is
best for them
Regulation will eliminate harmful Apps
after release
Prevent bad Apps - help App developers
understand safety & quality
The NHS must control Apps, apply rules
and safety checks
Self regulation by developer community
Consumer choice informed by truth in
labelling
App developers are in control Aristotle’s civil society* is in control
Quality is best achieved by laws and
regulations
Quality is best achieved by consensus
and culture change
The aim of Apps is innovation
(sometimes above other considerations)
App innovation must balance benefits
and risks
An Apps market driven by viral
campaigns, unfounded claims of benefit
An Apps market driven by fitness for
purpose (ISO) & evidence of benefit
• The elements that make up a democratic society, such as freedom of speech, an independent
judiciary, collaborating for common wellbeing
Our draft quality criteria for apps
based on Donabedian 1966
Structure = the app development team, the
evidence base, use of an appropriate CPD / health
promotion etc. model…
Processes = app functions: usability, accuracy etc.
Outcomes = app impacts on users (knowledge,
problem solving…), patient outcomes, NHS
resource use
Wyatt JC, Curtis K, Brown K, Michie S,. Submitted to Lancet
Summary for apps
3. The Royal College of Physicians, NHS
Trusts, BSI and other bodies are
exploring this approach, eg.
“Patients, health professionals and
system developers would benefit from
publication of an agreed set of quality
criteria for clinical and health promotion
systems and for apps.”
RCP Future Hospital Commission report 2013, p. 93
1. App rating, self-certification and regulation are not enough
2. To reduce “apptimism”, we must evaluate apps against
quality criteria & label them
Semantic interoperability
Disclaimer:
I am not omnipotent, just a doctor
mHealth as both challenge and
opportunity
Challenges:
• Patchwork of incompatible, small scale apps from cottage
industry of developers
• Silos of data
• Much software is not reusable (some OS apps)
• Poor IG: only 10% of 600 most popular H&LS apps had
privacy policy – recent US/ German study
Opportunities:
• Little NHS investment so far in infrastructure
• Shake down coming once EU DP Regulation agreed
• Open mHealth initiative
Open mHealth initiative
Reusable health
data &
knowledge
services
Analysis, feedback
Processing
Data storage
Data transport
Data capture
Apple’s
Healthkit ?
App1 App2 App3 Based on Estrin & Sim, Science 2012
Stovepipe model Open model
We have the necessary standards
in the NHS
• Patient identity standards – NHS number
• Health-specific syntactic and semantic data
standards – SNOMED CT, HL-7, CDA…
• Data stores that enable selective, patient-controlled
sharing - eg. MyDex, Patients Know Best…
• Core data processing functions eg. feature
extraction and analytics - ??
So, let’s do NHS Open mHealth !
Conclusions
1. Digital healthcare and mHealth apps have much
to offer the NHS and global health
2. However, they could be barriers to integrated care
3. Integrated care requires both human trust and
technical standards
a) Agreed quality criteria for eg. apps will help build trust
b) Approaches like Open mHealth will help address
technical / data exchange issues
4. The NHS is very well placed to adopt both these
approaches
Transforming health care
Old model of care New model
Focus on acute conditions Focus on long term conditions
Reactive management Prevention & continuing care
Hospital centred Embedded in homes & communities
Disjointed episodes Integrated with people’s lives
Doctor dependent Team based, shared record
Patient as passive recipient Patient as partner
Self care infrequent Self care encouraged & supported
Use of ICT rare Dependent on ICT & devices
The potential of mobile health
apps
Apps offer clinicians just-in-time knowledge & reminders;
patients personalised support for self-management
Once developed, they are easy to disseminate (“massively
scalable”)
Smart phones can help NHS access hard-to-reach populations
Apps technology allows:
• Tailoring to user profile and location (via GPS, wifi zones, scanned QR
codes on patient label, equipment, hospital walls…)
• Linkage to large knowledge bases (eg. ePrescribing tool, Map of
Medicine, My Meal Mate details of 60k foods)
• Access to data held securely on remote EPR, not device
Powell et al. In search of a few good apps. JAMA 2014
Expert reviews: iMedicalApps process
Acquire App
Review existing literature
Use App in simulated
environment
Use App in clinical practice
Draft assessment according to
template
Further peer review by senior
editorial staff
Slide from Tom Lewis,
Warwick Uni / iMedicalApps
Self-certification of web sites using
Health on Net criteria
The process:
1. Check “Health on the Net” criteria www.hon.ch:
• Authoritative, attributed material; date of revision
• Website states: purpose, intended user; if for patients, that
it is no substitute for medical advice
• Policy on confidentiality of patient data
• Justification of claims with scientific evidence
• Contact details, funding sources, advertising policy
2. Download HON logo & attach to site
No sanctions for misuse of HON logo:
NHS Health Apps library criteria
• Relevant to people living in England
• Complies with data protection laws
• Complies with trusted sources of information, such
as NHS Choices.
• Could it potentially cause harm to a person’s health
or condition. “Eg. is it limited to providing
information from a trusted source – or might it go
on to provide personalised medical
recommendations or treatment options?”
http://apps.nhs.uk/review-process/#transcript