SlideShare uma empresa Scribd logo
1 de 27
Baixar para ler offline
Commercial access
to health data
Key findings
April 2016
2
Recap of methodology
16 qualitative
workshops
across GB, 246
individuals
Quantitative
survey of 2,017
GB adults
8 x general public
3 x GPs and hospital doctors
4 x long-term health conditions
1 x cohort members
Quantitative research run as
follow-up to qualitative work
Face-to-face interviews
Qualitative context
4
Lots of initial uncertainty and wariness
Lack of understanding around
current data-use and sharing
Most haven’t thought about
private
sector/academic/charities’
involvement in NHS
Individual-level data thought of as
‘my data’. Aggregate data as
‘statistics’ (instinctively more benign)
Little knowledge of safeguards and
how datasets are handled
Most assume rules are in place
?!?Future
communication
challenges
5
It’s a one-way mirror: they
know everything about you –
but we don’t know what
they’re doing with that
6
Two traditional mindsets for data sharing
1. Commercial transactions: ‘My data has financial value’
Buying
Doing
Data is given as part
of a deal: consumer
gets something in
return
Expectation it will
be used and shared
for financial gain by
the collector
Actively given
Passively taken
Wary mindset
7
2. Social contract mindset: ‘We’re all helping each other’
Service using
Being
Data is given in confidence
in exchange for a service,
assumption it will be used
for that purpose only
Assumption that only high-
level data is collected and
for health purposes
Actively given
Passively taken
Open, vulnerable mindset
Two traditional mindsets for data sharing
8
Commercial access to health data constitutes ‘context collapse’
Should I be a
helpful citizen?
Being
Is it being passively taken?
Am I actively giving it?
Doing
Buying Service
using
Should I be wary?
?
Concern for
vulnerable
groups, risk of
exploitation
Tendency to revert
to assumptions and
prejudices e.g.
‘private companies
cannot be trusted’
9
What drives acceptability: four key tests
More acceptable Less acceptable/red lines
1. WHY
2. WHO
3. WHAT
4. HOW
Clear public
benefit
Public health
providers
Aggregate
data, passively
collected
Secure storage & regulation is assumed
Solely private
benefit
No link to
improving
public health
Identifiable
personal details
with real world
implications
Mix of public
and private
benefit
For profit
but in health
sector
Aggregate
but risk of
jigsaw ID
Uncertain
future
users – e.g.
‘sharing on‘
with third
party
Genetic
data;
uncertain
future uses
10
The public can see opportunities
1. WHY
2. WHO
3. WHAT
4. HOW
Clear public
benefit
Public
health
providers
Aggregate
data
Secure storage
& regulation is
assumed
Primary driver: without this, majority say
data shouldn’t be shared
NHS, Charities, Academic researchers
and partnerships involving them
Aggregate data, passively collected (i.e.
no personal details ever attached) less
risky
Transparency, independent scrutiny,
sanctions and fines for misuse reassure
11
But they also have concerns
1. WHY
2. WHO
3. WHAT
4. HOW
Mix of
public and
private
benefit
For profit
but in health
sector
Aggregate
but risk of
jigsaw ID
Secure storage
& regulation is
assumed
For some acceptable: WHO becomes
more important – is the organisation
trusted?
e.g. analytics company working with
NHS. Some fears about ‘big pharma’ &
retail – makes regulation more important
If originally taken from identifiable data
- potential risk to the individual
Doubts generally linked to WHO is
handling the data and whether they are
trusted; regulation helps reassure
12
…and some red lines
1. WHY
2. WHO
3. WHAT
4. HOW
Solely private
benefit
No link to
improving
public health
Identifiable
personal details
with real world
implications
Secure storage &
regulation is
assumed
If no clear public benefit, sharing is
unacceptable to most
Insurance companies, marketing
companies; never benefit public,
motivated by profit
Concerns about impact on employment
prospects, insurance premiums etc.
Uncertain future users – e.g. ‘sharing on‘
with third party
Genetic data; uncertain future uses
No regulation/scrutiny to ensure data is
used for intended purpose and not
passed on
13
Seven mindsets influence views
Pragmatic
Concerned with impact of privacy
at personal level
Abstract
Concern for human rights, social
goods, and impact on everyone
Open to commercial interest
Accepting of private sector involvement in
general
Wary of commercial interest
Sceptical of private sector involvement
Commercial access necessary for social
development; public benefits worth risk to
personal privacy. Duty to share health data?
Less concerned with public benefit, risks to society;
neutral stance towards commercial orgs (including
marketing and insurance). Not worried/haven’t
really thought about security risks.
Fear large-scale negative impact on all society:
do not trust commercial orgs. ‘Big Brother’
society where commercial use of data worsens
social inequality.
Sceptical of commercial motives and coexistence
of public and private benefit. Lack faith in
systems. Recognise benefits but commercial
involvement is imperfect solution. Pro opt out.
Quantitative
context
15
5
5
12
13
11
21
25
25
29
25
27
21
31
31
16
1
1
1
Academics
researchers
Commercial
organisations
NHS
A great deal
A fair amount
Just a little
Heard of, know
nothing about
Never heard of
Don’t know
Awareness is an initial stumbling block to understanding
Source: Ipsos MORI/Wellcome Trust
Base: 2,017 GB adults, aged 16+
How much, if anything, would you say you know about how the following organisations
use health data for these purposes?*
33% 21%
*See report for full question wording
56%18%
16% 58%
16
But more support than oppose health data sharing for research
18
3519
13
13
2
Strongly support
Tend to support
Neither support nor
oppose
Tend to oppose
Strongly oppose
Don't know
Source: Ipsos MORI/Wellcome Trust
Base: 2,017 GB adults, aged 16+
To what extent, if at all, would you support your health data being accessed
by commercial organisations if they are undertaking health research?*
54%
26%
*See report for full question wording
Educational
attainment:
Degree (59%)
A-level (57%)
GCSE (52%)
No qualifications
(43%)
Knowledge factors
influence support
Social grade:
AB (62%)
C1 (53%)
C2 (53%)
DE (46%)
Data usage
awareness:
Aware (56%-59%)
Not aware (45%-
47%)
Internet access:
Daily users (56%)
Less frequent (52%)
No access (39%)
17
30
32
23
22
24
30
9
7
10
7
2
2
Drug company
Public health
regulator
5 - completely acceptable 4 3 2 1 - completely unacceptable Don't know
Drug companies aren’t deal-breakers…
Source: Ipsos MORI/Wellcome Trust
Base: split sample, bases on chart
[INTRODUCTION about public health regulator OR drug company running tests on a
new drug] …On a scale of 1-5, how acceptable, if at all, do you find this use of data?*
*See report for full question wording
(997)
(1,020)
18
10
5
28
21
26
27
18
21
18
24
1
3
Marketing
Insurance
Strongly agree
Tend to agree
Neither agree nor
disagree
Tend to disagree
Strongly disagree
…but insurance and marketing purposes might be
Source: Ipsos MORI/Wellcome Trust
Base: split sample, bases on chart
To what extent, if at all, would you support insurance companies using health data collected in the
NHS to further develop their health insurance prices?*
To what extent, if at all, would you support companies using health data collected in the NHS to help
target health products at different groups of people?*
26% 44%
37% 36%
*See report for full question wording
(992)
(1,025)
19
Support for commercial access if research at risk
31
31
14
12
13
2
Agree much more with
B than with A
Agree a little more with
B than with A
Agree equally with
both / don't agree with
either
Agree a little more with
A than with B
Source: Ipsos MORI/Wellcome Trust
Base: 974 GB adults, aged 16+
Which of the following statements comes closest to your view of health data being shared
with commercial organisations?*
61%
25%
*See report for full question wording
B. The research should be
conducted by commercial
organisations if there is a
possibility of new
treatments for diseases
being developed
A. I would not want
commercial
organisations to have
access to anonymised
health data, even if this
means the research
does not take place
20
Differences within differences – not all sceptics the same
Source: Ipsos MORI/Wellcome Trust
Base: All those who do not want commercial organisations to have access to health data under any circumstances (356)
Which of the following views, if any, comes closest to why you do not want commercial organisations to have
access to health data under any circumstances?*
*See report for full question wording
4
2
2
2
2
6
8
8
13
16
18
20They cannot be trusted to store the data safely
I don't agree profit should be made from NHS data, even if
there are benefits
Commercial orgs cannot be trusted to put society before profit
They might sell data onto another commercial org and you
cannot control where it ends up
If commercial orgs access the data, they could manipulate it
and this is unfair
They may try and market products and services to me
There might be negative consequences for me or my family
They may re-identify me even though names and personal
information might be removed from the data
There might be negative consequences for the community
Even if they misuse the data they won't be punished
Don’t know
Other
49% of people asked this
question aligned with
reasons related to things
that could harm them or
their family
46% aligned themselves
with social reasons; that
commercial orgs having
health data could
negatively impact
society
Implications for
communications and
public engagement
22
We need a shared understanding of value
Aggregate
Recognised as a national resource,
but with conditions
Long-term value to society, not just
private interest/financial gain
Support for public goods e.g. NHS
Fair process – data shared when
vulnerable ‘service use mind set’ so
should not be exploited
Individual
Harder to grasp, questions of
ownership and perverse incentives
Health data as currency – potential
benefits for those without money
But worries over unintended
consequences – What if the wealthier
opt out leading to bad datasets? Will
vulnerable groups be exploited for their
data?
Communications need to take into account how the
public conceive of different types of data
23
And a new social contract
Public question if commercial access is
consistent with ‘promotion of health’
Care Act 2014 – data can be shared for
provision of care or promotion of health
Scepticism towards commercial interest
leading to socially beneficial outcomes
Even the more pragmatic lack awareness of
the role commercial interests play in health
(e.g. provide essential services/drug trials)
New innovations mean
new challenges
Rise of wearables, passive
data collection without full
consent (e.g. small print Ts
and Cs) links to questions of
ownership and ethics
Individuals unaware of
potential autonomy to shape
own care
Communications need to:
• Tackle scepticism and low awareness of commercial access
• Signal potential benefits and risks of data and tech innovations
24
Currently, “no job description for being a citizen”
 Public don’t currently know enough to be guardians of their own
health data
They have low awareness of the “quantified self”, many expect
practitioners to make decisions for them
And low understanding of consent models, implications of ‘opt-out’
on accuracy
 There is space for a further conversation about future healthcare
delivery: role of state, commerce, big data and individual citizens
 Shared learnings will be key: Academy of Medical Sciences, ‘Exploring
a new social contract for medical innovation’, Royal Society’s work on
Machine Learning, Cabinet Office on Data Science Ethics
25
What next?
Think about how commercial access is managed not just how it
is communicated – fair processes and appropriate
safeguards will play an important part in driving or hindering
trust
Identify public information needs (cf. other research). E.g.
technical terms about data/data science/data collection,
safeguards, consent options and role of commerce in health
Safeguards help but there is much leg work to do before this –
need to establish public benefit and tackle scepticism
Consider terminology and public understanding of word
‘commercial’ – being specific will help remove public biases
26
Done well, could drive
trust in government and
create optimism around
future health data-sharing
and role of commerce in
health
But done poorly, could
lead to ‘confidence
collapse’ and jeopardise
future public support
Rather put the brakes on now…
Public clearly concerned about commercial access and broader
implications of a data-rich world
If health data is a national resource then how it is handled now will
impact future opportunities
Q & A
For more info:
naomi.boal@ipsos.com
debbie.chan@ipsos.com
stephanie.crowe@ipsos.com

Mais conteúdo relacionado

Mais procurados

McKinsey Survey: Emirati consumer sentiment during the coronavirus crisis
McKinsey Survey: Emirati consumer sentiment during the coronavirus crisisMcKinsey Survey: Emirati consumer sentiment during the coronavirus crisis
McKinsey Survey: Emirati consumer sentiment during the coronavirus crisisMcKinsey on Marketing & Sales
 
COVID-19: How Businesses Are Handling the Crisis
COVID-19: How Businesses Are Handling the CrisisCOVID-19: How Businesses Are Handling the Crisis
COVID-19: How Businesses Are Handling the CrisisSarah Jackson
 
McKinsey COVID-19 impact Morocco wave 3
McKinsey COVID-19 impact Morocco wave 3McKinsey COVID-19 impact Morocco wave 3
McKinsey COVID-19 impact Morocco wave 3John Euart
 
The State of Global Well-Being
The State of Global Well-BeingThe State of Global Well-Being
The State of Global Well-BeingStinson
 
For later life: Better health and care in tough times
For later life: Better health and care in tough timesFor later life: Better health and care in tough times
For later life: Better health and care in tough timesIpsos UK
 
McKinsey Survey: Colombian consumer sentiment during the coronavirus crisis
McKinsey Survey: Colombian consumer sentiment during the coronavirus crisisMcKinsey Survey: Colombian consumer sentiment during the coronavirus crisis
McKinsey Survey: Colombian consumer sentiment during the coronavirus crisisMcKinsey on Marketing & Sales
 
How to respond to what healthcare professionals are telling us?
How to respond to what healthcare professionals are telling us?How to respond to what healthcare professionals are telling us?
How to respond to what healthcare professionals are telling us?Agnitio
 
McKinsey Survey: Chinese consumer sentiment during the coronavirus crisis
McKinsey Survey: Chinese consumer sentiment during the coronavirus crisisMcKinsey Survey: Chinese consumer sentiment during the coronavirus crisis
McKinsey Survey: Chinese consumer sentiment during the coronavirus crisisMcKinsey on Marketing & Sales
 
McKinsey Survey: Mexican consumer sentiment during the coronavirus crisis
McKinsey Survey: Mexican consumer sentiment during the coronavirus crisisMcKinsey Survey: Mexican consumer sentiment during the coronavirus crisis
McKinsey Survey: Mexican consumer sentiment during the coronavirus crisisMcKinsey on Marketing & Sales
 
Survey results: Consumer discretionary spending in China
Survey results: Consumer discretionary spending in ChinaSurvey results: Consumer discretionary spending in China
Survey results: Consumer discretionary spending in ChinaHeather Hanselman
 
McKinsey Survey: US consumer sentiment during the coronavirus crisis
McKinsey Survey: US consumer sentiment during the coronavirus crisisMcKinsey Survey: US consumer sentiment during the coronavirus crisis
McKinsey Survey: US consumer sentiment during the coronavirus crisisMcKinsey on Marketing & Sales
 
Business Consulting Presentation
Business Consulting PresentationBusiness Consulting Presentation
Business Consulting PresentationJoeHart
 
Webchutney Digital Healthcare Report 2011
Webchutney Digital Healthcare Report 2011Webchutney Digital Healthcare Report 2011
Webchutney Digital Healthcare Report 2011Sidharth Rao
 
McKinsey Survey: Global B2B decision maker response to COVID-19 crisis
McKinsey Survey: Global B2B decision maker response to COVID-19 crisisMcKinsey Survey: Global B2B decision maker response to COVID-19 crisis
McKinsey Survey: Global B2B decision maker response to COVID-19 crisisMcKinsey on Marketing & Sales
 
CES COVID-19 Consumer Pulse Survey
CES COVID-19 Consumer Pulse SurveyCES COVID-19 Consumer Pulse Survey
CES COVID-19 Consumer Pulse SurveyOliur Tarek
 
McKinsey Survey: European B2B decision maker response to COVID-19 crisis
McKinsey Survey: European B2B decision maker response to COVID-19 crisisMcKinsey Survey: European B2B decision maker response to COVID-19 crisis
McKinsey Survey: European B2B decision maker response to COVID-19 crisisMcKinsey on Marketing & Sales
 
20200407 asia covid 19 - grocery retail survey - south korea v final-ds v2
20200407 asia covid 19 - grocery retail survey - south korea v final-ds v220200407 asia covid 19 - grocery retail survey - south korea v final-ds v2
20200407 asia covid 19 - grocery retail survey - south korea v final-ds v2DaniellaSeiler
 
Edelman Trust Barometer - Ireland
Edelman Trust Barometer - IrelandEdelman Trust Barometer - Ireland
Edelman Trust Barometer - IrelandPiaras Kelly
 

Mais procurados (20)

2019 CPG Growth Leaders Report
2019 CPG Growth Leaders Report2019 CPG Growth Leaders Report
2019 CPG Growth Leaders Report
 
McKinsey Survey: Emirati consumer sentiment during the coronavirus crisis
McKinsey Survey: Emirati consumer sentiment during the coronavirus crisisMcKinsey Survey: Emirati consumer sentiment during the coronavirus crisis
McKinsey Survey: Emirati consumer sentiment during the coronavirus crisis
 
COVID-19: How Businesses Are Handling the Crisis
COVID-19: How Businesses Are Handling the CrisisCOVID-19: How Businesses Are Handling the Crisis
COVID-19: How Businesses Are Handling the Crisis
 
McKinsey COVID-19 impact Morocco wave 3
McKinsey COVID-19 impact Morocco wave 3McKinsey COVID-19 impact Morocco wave 3
McKinsey COVID-19 impact Morocco wave 3
 
The State of Global Well-Being
The State of Global Well-BeingThe State of Global Well-Being
The State of Global Well-Being
 
For later life: Better health and care in tough times
For later life: Better health and care in tough timesFor later life: Better health and care in tough times
For later life: Better health and care in tough times
 
McKinsey Survey: Colombian consumer sentiment during the coronavirus crisis
McKinsey Survey: Colombian consumer sentiment during the coronavirus crisisMcKinsey Survey: Colombian consumer sentiment during the coronavirus crisis
McKinsey Survey: Colombian consumer sentiment during the coronavirus crisis
 
How to respond to what healthcare professionals are telling us?
How to respond to what healthcare professionals are telling us?How to respond to what healthcare professionals are telling us?
How to respond to what healthcare professionals are telling us?
 
McKinsey Survey: Chinese consumer sentiment during the coronavirus crisis
McKinsey Survey: Chinese consumer sentiment during the coronavirus crisisMcKinsey Survey: Chinese consumer sentiment during the coronavirus crisis
McKinsey Survey: Chinese consumer sentiment during the coronavirus crisis
 
McKinsey Survey: Mexican consumer sentiment during the coronavirus crisis
McKinsey Survey: Mexican consumer sentiment during the coronavirus crisisMcKinsey Survey: Mexican consumer sentiment during the coronavirus crisis
McKinsey Survey: Mexican consumer sentiment during the coronavirus crisis
 
Survey results: Consumer discretionary spending in China
Survey results: Consumer discretionary spending in ChinaSurvey results: Consumer discretionary spending in China
Survey results: Consumer discretionary spending in China
 
McKinsey Survey: US consumer sentiment during the coronavirus crisis
McKinsey Survey: US consumer sentiment during the coronavirus crisisMcKinsey Survey: US consumer sentiment during the coronavirus crisis
McKinsey Survey: US consumer sentiment during the coronavirus crisis
 
Carediac
CarediacCarediac
Carediac
 
Business Consulting Presentation
Business Consulting PresentationBusiness Consulting Presentation
Business Consulting Presentation
 
Webchutney Digital Healthcare Report 2011
Webchutney Digital Healthcare Report 2011Webchutney Digital Healthcare Report 2011
Webchutney Digital Healthcare Report 2011
 
McKinsey Survey: Global B2B decision maker response to COVID-19 crisis
McKinsey Survey: Global B2B decision maker response to COVID-19 crisisMcKinsey Survey: Global B2B decision maker response to COVID-19 crisis
McKinsey Survey: Global B2B decision maker response to COVID-19 crisis
 
CES COVID-19 Consumer Pulse Survey
CES COVID-19 Consumer Pulse SurveyCES COVID-19 Consumer Pulse Survey
CES COVID-19 Consumer Pulse Survey
 
McKinsey Survey: European B2B decision maker response to COVID-19 crisis
McKinsey Survey: European B2B decision maker response to COVID-19 crisisMcKinsey Survey: European B2B decision maker response to COVID-19 crisis
McKinsey Survey: European B2B decision maker response to COVID-19 crisis
 
20200407 asia covid 19 - grocery retail survey - south korea v final-ds v2
20200407 asia covid 19 - grocery retail survey - south korea v final-ds v220200407 asia covid 19 - grocery retail survey - south korea v final-ds v2
20200407 asia covid 19 - grocery retail survey - south korea v final-ds v2
 
Edelman Trust Barometer - Ireland
Edelman Trust Barometer - IrelandEdelman Trust Barometer - Ireland
Edelman Trust Barometer - Ireland
 

Destaque

Congenica Genome Analysis and Clinical Interpretation: An Overview
Congenica Genome Analysis and Clinical Interpretation: An OverviewCongenica Genome Analysis and Clinical Interpretation: An Overview
Congenica Genome Analysis and Clinical Interpretation: An OverviewCongenica
 
Ipsos MORI Issues Index March 2017
Ipsos MORI Issues Index March 2017Ipsos MORI Issues Index March 2017
Ipsos MORI Issues Index March 2017Ipsos UK
 
Medical device data protection and security
Medical device data protection and security Medical device data protection and security
Medical device data protection and security Erik Vollebregt
 
EU General Data Protection Regulation top 8 operational impacts in personal c...
EU General Data Protection Regulation top 8 operational impacts in personal c...EU General Data Protection Regulation top 8 operational impacts in personal c...
EU General Data Protection Regulation top 8 operational impacts in personal c...Erik Vollebregt
 
Ipsos MORI: The public mood
Ipsos MORI: The public moodIpsos MORI: The public mood
Ipsos MORI: The public moodIpsos UK
 
Public Health England: Public awareness and opinion survey 2016
Public Health England: Public awareness and opinion survey 2016Public Health England: Public awareness and opinion survey 2016
Public Health England: Public awareness and opinion survey 2016Ipsos UK
 

Destaque (6)

Congenica Genome Analysis and Clinical Interpretation: An Overview
Congenica Genome Analysis and Clinical Interpretation: An OverviewCongenica Genome Analysis and Clinical Interpretation: An Overview
Congenica Genome Analysis and Clinical Interpretation: An Overview
 
Ipsos MORI Issues Index March 2017
Ipsos MORI Issues Index March 2017Ipsos MORI Issues Index March 2017
Ipsos MORI Issues Index March 2017
 
Medical device data protection and security
Medical device data protection and security Medical device data protection and security
Medical device data protection and security
 
EU General Data Protection Regulation top 8 operational impacts in personal c...
EU General Data Protection Regulation top 8 operational impacts in personal c...EU General Data Protection Regulation top 8 operational impacts in personal c...
EU General Data Protection Regulation top 8 operational impacts in personal c...
 
Ipsos MORI: The public mood
Ipsos MORI: The public moodIpsos MORI: The public mood
Ipsos MORI: The public mood
 
Public Health England: Public awareness and opinion survey 2016
Public Health England: Public awareness and opinion survey 2016Public Health England: Public awareness and opinion survey 2016
Public Health England: Public awareness and opinion survey 2016
 

Semelhante a Commercial access to health data

People, health professionals and health information Working together in 2014
People, health professionals and health information Working together in 2014People, health professionals and health information Working together in 2014
People, health professionals and health information Working together in 2014Health Informatics New Zealand
 
ey-getting-from-big-data-to-analytics
ey-getting-from-big-data-to-analyticsey-getting-from-big-data-to-analytics
ey-getting-from-big-data-to-analyticsGautam Jaggi
 
Natalie banner
Natalie bannerNatalie banner
Natalie bannerHIQAHIS
 
Jeremy Wyatt's Presentation on Privacy for the mHealthHabitat Heart of the Ha...
Jeremy Wyatt's Presentation on Privacy for the mHealthHabitat Heart of the Ha...Jeremy Wyatt's Presentation on Privacy for the mHealthHabitat Heart of the Ha...
Jeremy Wyatt's Presentation on Privacy for the mHealthHabitat Heart of the Ha...m Habitat
 
Patients Rising: How to Reach Empowered, Digital Health Consumers
Patients Rising: How to Reach Empowered, Digital Health ConsumersPatients Rising: How to Reach Empowered, Digital Health Consumers
Patients Rising: How to Reach Empowered, Digital Health Consumerse-Patient Connections
 
Social Media Analytics in Life Sciences
Social Media Analytics in Life SciencesSocial Media Analytics in Life Sciences
Social Media Analytics in Life SciencesIGATE Corporation
 
Social media healthcare
Social media healthcareSocial media healthcare
Social media healthcareRichard Meyer
 
How Artificial Intelligence Can Overcome Healthcare Data Security Challenges ...
How Artificial Intelligence Can Overcome Healthcare Data Security Challenges ...How Artificial Intelligence Can Overcome Healthcare Data Security Challenges ...
How Artificial Intelligence Can Overcome Healthcare Data Security Challenges ...Health Catalyst
 
Care data against
Care data   againstCare data   against
Care data against3GDR
 
Cisco for Health Plans
Cisco for Health PlansCisco for Health Plans
Cisco for Health PlansEJ Bowen
 
mHealth Israel_GEARING COMMUNICATIONS TO RAISE CAPITAL AND ATTRACT CUSTOMERS_...
mHealth Israel_GEARING COMMUNICATIONS TO RAISE CAPITAL AND ATTRACT CUSTOMERS_...mHealth Israel_GEARING COMMUNICATIONS TO RAISE CAPITAL AND ATTRACT CUSTOMERS_...
mHealth Israel_GEARING COMMUNICATIONS TO RAISE CAPITAL AND ATTRACT CUSTOMERS_...Levi Shapiro
 
Strat Comm Pharm Report (1)
Strat Comm Pharm Report (1)Strat Comm Pharm Report (1)
Strat Comm Pharm Report (1)Linda Johnson
 
Integrating information.pdf
Integrating information.pdfIntegrating information.pdf
Integrating information.pdfSirius Partners
 
Seriously Thinking series - Integrating information .pdf
Seriously Thinking series - Integrating information .pdfSeriously Thinking series - Integrating information .pdf
Seriously Thinking series - Integrating information .pdfSirius Partners
 
Seriously Thinking series - Integrating information .pdf
Seriously Thinking series - Integrating information .pdfSeriously Thinking series - Integrating information .pdf
Seriously Thinking series - Integrating information .pdfSirius Partners
 

Semelhante a Commercial access to health data (20)

People, health professionals and health information Working together in 2014
People, health professionals and health information Working together in 2014People, health professionals and health information Working together in 2014
People, health professionals and health information Working together in 2014
 
ey-getting-from-big-data-to-analytics
ey-getting-from-big-data-to-analyticsey-getting-from-big-data-to-analytics
ey-getting-from-big-data-to-analytics
 
PA Data Sharing Survey 2016 POSTED.final
PA Data Sharing Survey 2016 POSTED.finalPA Data Sharing Survey 2016 POSTED.final
PA Data Sharing Survey 2016 POSTED.final
 
Natalie banner
Natalie bannerNatalie banner
Natalie banner
 
Jeremy Wyatt's Presentation on Privacy for the mHealthHabitat Heart of the Ha...
Jeremy Wyatt's Presentation on Privacy for the mHealthHabitat Heart of the Ha...Jeremy Wyatt's Presentation on Privacy for the mHealthHabitat Heart of the Ha...
Jeremy Wyatt's Presentation on Privacy for the mHealthHabitat Heart of the Ha...
 
Patients Rising: How to Reach Empowered, Digital Health Consumers
Patients Rising: How to Reach Empowered, Digital Health ConsumersPatients Rising: How to Reach Empowered, Digital Health Consumers
Patients Rising: How to Reach Empowered, Digital Health Consumers
 
Social media and pharma
Social media and pharmaSocial media and pharma
Social media and pharma
 
Healthcare: the new-gold-rush
Healthcare: the new-gold-rushHealthcare: the new-gold-rush
Healthcare: the new-gold-rush
 
Social Media Pharma
Social Media PharmaSocial Media Pharma
Social Media Pharma
 
Social Media Analytics in Life Sciences
Social Media Analytics in Life SciencesSocial Media Analytics in Life Sciences
Social Media Analytics in Life Sciences
 
Social media healthcare
Social media healthcareSocial media healthcare
Social media healthcare
 
How Artificial Intelligence Can Overcome Healthcare Data Security Challenges ...
How Artificial Intelligence Can Overcome Healthcare Data Security Challenges ...How Artificial Intelligence Can Overcome Healthcare Data Security Challenges ...
How Artificial Intelligence Can Overcome Healthcare Data Security Challenges ...
 
Care data against
Care data   againstCare data   against
Care data against
 
Cisco for Health Plans
Cisco for Health PlansCisco for Health Plans
Cisco for Health Plans
 
mHealth Israel_GEARING COMMUNICATIONS TO RAISE CAPITAL AND ATTRACT CUSTOMERS_...
mHealth Israel_GEARING COMMUNICATIONS TO RAISE CAPITAL AND ATTRACT CUSTOMERS_...mHealth Israel_GEARING COMMUNICATIONS TO RAISE CAPITAL AND ATTRACT CUSTOMERS_...
mHealth Israel_GEARING COMMUNICATIONS TO RAISE CAPITAL AND ATTRACT CUSTOMERS_...
 
Strat Comm Pharm Report (1)
Strat Comm Pharm Report (1)Strat Comm Pharm Report (1)
Strat Comm Pharm Report (1)
 
Integrating information.pdf
Integrating information.pdfIntegrating information.pdf
Integrating information.pdf
 
Seriously Thinking series - Integrating information .pdf
Seriously Thinking series - Integrating information .pdfSeriously Thinking series - Integrating information .pdf
Seriously Thinking series - Integrating information .pdf
 
Seriously Thinking series - Integrating information .pdf
Seriously Thinking series - Integrating information .pdfSeriously Thinking series - Integrating information .pdf
Seriously Thinking series - Integrating information .pdf
 
Nicolas Terry, "Big Data, Regulatory Disruption, and Arbitrage in Health Care"
Nicolas Terry, "Big Data, Regulatory Disruption, and Arbitrage in Health Care"Nicolas Terry, "Big Data, Regulatory Disruption, and Arbitrage in Health Care"
Nicolas Terry, "Big Data, Regulatory Disruption, and Arbitrage in Health Care"
 

Mais de Ipsos UK

The Beat: 5 years on from the Brexit vote
The Beat: 5 years on from the Brexit voteThe Beat: 5 years on from the Brexit vote
The Beat: 5 years on from the Brexit voteIpsos UK
 
Bridging the gap: cyber security skills
Bridging the gap: cyber security skillsBridging the gap: cyber security skills
Bridging the gap: cyber security skillsIpsos UK
 
The state of cyber resilience in the UK
The state of cyber resilience in the UKThe state of cyber resilience in the UK
The state of cyber resilience in the UKIpsos UK
 
Ipsos Global Advisor: The Perils of Perception: Environment and Climate Change
Ipsos Global Advisor:  The Perils of Perception: Environment and Climate ChangeIpsos Global Advisor:  The Perils of Perception: Environment and Climate Change
Ipsos Global Advisor: The Perils of Perception: Environment and Climate ChangeIpsos UK
 
Ipsos Community: Quotes following the events around the vigil for Sarah Everard
Ipsos Community: Quotes following the events around the vigil for Sarah EverardIpsos Community: Quotes following the events around the vigil for Sarah Everard
Ipsos Community: Quotes following the events around the vigil for Sarah EverardIpsos UK
 
Global Infrastructure Index 2020
Global Infrastructure Index 2020Global Infrastructure Index 2020
Global Infrastructure Index 2020Ipsos UK
 
Women, work and COVID-19
Women, work and COVID-19Women, work and COVID-19
Women, work and COVID-19Ipsos UK
 
US Election 2020 Webinar - Ipsos MORI
US Election 2020 Webinar - Ipsos MORIUS Election 2020 Webinar - Ipsos MORI
US Election 2020 Webinar - Ipsos MORIIpsos UK
 
Sexual orientation and attitudes to LGBTQ+ in Britain
Sexual orientation and attitudes to LGBTQ+ in BritainSexual orientation and attitudes to LGBTQ+ in Britain
Sexual orientation and attitudes to LGBTQ+ in BritainIpsos UK
 
COVID-19: Conspiracies and Confusions and the link with Social Media
COVID-19: Conspiracies and Confusions and the link with Social MediaCOVID-19: Conspiracies and Confusions and the link with Social Media
COVID-19: Conspiracies and Confusions and the link with Social MediaIpsos UK
 
Solving the Cyber Security Skills Gap with DCMS
Solving the Cyber Security Skills Gap with DCMSSolving the Cyber Security Skills Gap with DCMS
Solving the Cyber Security Skills Gap with DCMSIpsos UK
 
Ipsos MORI Politial Pulse - April 2020
Ipsos MORI Politial Pulse - April 2020Ipsos MORI Politial Pulse - April 2020
Ipsos MORI Politial Pulse - April 2020Ipsos UK
 
Ipsos MORI Political Monitor - March 2020
Ipsos MORI Political Monitor - March 2020Ipsos MORI Political Monitor - March 2020
Ipsos MORI Political Monitor - March 2020Ipsos UK
 
International Women's Day 2020: What is acceptable behaviour in the workplace?
International Women's Day 2020: What is acceptable behaviour in the workplace?International Women's Day 2020: What is acceptable behaviour in the workplace?
International Women's Day 2020: What is acceptable behaviour in the workplace?Ipsos UK
 
Coronavirus Opinion and Reaction - Ipsos MORI
Coronavirus Opinion and Reaction - Ipsos MORICoronavirus Opinion and Reaction - Ipsos MORI
Coronavirus Opinion and Reaction - Ipsos MORIIpsos UK
 
The Perils of Perception 2020: Causes of Death
The Perils of Perception 2020: Causes of DeathThe Perils of Perception 2020: Causes of Death
The Perils of Perception 2020: Causes of DeathIpsos UK
 
Public Perception of Environmental Impact: Ipsos Omnibus Poll
Public Perception of Environmental Impact: Ipsos Omnibus PollPublic Perception of Environmental Impact: Ipsos Omnibus Poll
Public Perception of Environmental Impact: Ipsos Omnibus PollIpsos UK
 
Ipsos MORI Social Media Britain November 2019
Ipsos MORI Social Media Britain November 2019Ipsos MORI Social Media Britain November 2019
Ipsos MORI Social Media Britain November 2019Ipsos UK
 
Ipsos MORI 2019 General Election Campign Tracker - Housing
Ipsos MORI 2019 General Election Campign Tracker - HousingIpsos MORI 2019 General Election Campign Tracker - Housing
Ipsos MORI 2019 General Election Campign Tracker - HousingIpsos UK
 
Ipsos MORI Political Monitor - 6 December 2019
Ipsos MORI Political Monitor - 6 December 2019Ipsos MORI Political Monitor - 6 December 2019
Ipsos MORI Political Monitor - 6 December 2019Ipsos UK
 

Mais de Ipsos UK (20)

The Beat: 5 years on from the Brexit vote
The Beat: 5 years on from the Brexit voteThe Beat: 5 years on from the Brexit vote
The Beat: 5 years on from the Brexit vote
 
Bridging the gap: cyber security skills
Bridging the gap: cyber security skillsBridging the gap: cyber security skills
Bridging the gap: cyber security skills
 
The state of cyber resilience in the UK
The state of cyber resilience in the UKThe state of cyber resilience in the UK
The state of cyber resilience in the UK
 
Ipsos Global Advisor: The Perils of Perception: Environment and Climate Change
Ipsos Global Advisor:  The Perils of Perception: Environment and Climate ChangeIpsos Global Advisor:  The Perils of Perception: Environment and Climate Change
Ipsos Global Advisor: The Perils of Perception: Environment and Climate Change
 
Ipsos Community: Quotes following the events around the vigil for Sarah Everard
Ipsos Community: Quotes following the events around the vigil for Sarah EverardIpsos Community: Quotes following the events around the vigil for Sarah Everard
Ipsos Community: Quotes following the events around the vigil for Sarah Everard
 
Global Infrastructure Index 2020
Global Infrastructure Index 2020Global Infrastructure Index 2020
Global Infrastructure Index 2020
 
Women, work and COVID-19
Women, work and COVID-19Women, work and COVID-19
Women, work and COVID-19
 
US Election 2020 Webinar - Ipsos MORI
US Election 2020 Webinar - Ipsos MORIUS Election 2020 Webinar - Ipsos MORI
US Election 2020 Webinar - Ipsos MORI
 
Sexual orientation and attitudes to LGBTQ+ in Britain
Sexual orientation and attitudes to LGBTQ+ in BritainSexual orientation and attitudes to LGBTQ+ in Britain
Sexual orientation and attitudes to LGBTQ+ in Britain
 
COVID-19: Conspiracies and Confusions and the link with Social Media
COVID-19: Conspiracies and Confusions and the link with Social MediaCOVID-19: Conspiracies and Confusions and the link with Social Media
COVID-19: Conspiracies and Confusions and the link with Social Media
 
Solving the Cyber Security Skills Gap with DCMS
Solving the Cyber Security Skills Gap with DCMSSolving the Cyber Security Skills Gap with DCMS
Solving the Cyber Security Skills Gap with DCMS
 
Ipsos MORI Politial Pulse - April 2020
Ipsos MORI Politial Pulse - April 2020Ipsos MORI Politial Pulse - April 2020
Ipsos MORI Politial Pulse - April 2020
 
Ipsos MORI Political Monitor - March 2020
Ipsos MORI Political Monitor - March 2020Ipsos MORI Political Monitor - March 2020
Ipsos MORI Political Monitor - March 2020
 
International Women's Day 2020: What is acceptable behaviour in the workplace?
International Women's Day 2020: What is acceptable behaviour in the workplace?International Women's Day 2020: What is acceptable behaviour in the workplace?
International Women's Day 2020: What is acceptable behaviour in the workplace?
 
Coronavirus Opinion and Reaction - Ipsos MORI
Coronavirus Opinion and Reaction - Ipsos MORICoronavirus Opinion and Reaction - Ipsos MORI
Coronavirus Opinion and Reaction - Ipsos MORI
 
The Perils of Perception 2020: Causes of Death
The Perils of Perception 2020: Causes of DeathThe Perils of Perception 2020: Causes of Death
The Perils of Perception 2020: Causes of Death
 
Public Perception of Environmental Impact: Ipsos Omnibus Poll
Public Perception of Environmental Impact: Ipsos Omnibus PollPublic Perception of Environmental Impact: Ipsos Omnibus Poll
Public Perception of Environmental Impact: Ipsos Omnibus Poll
 
Ipsos MORI Social Media Britain November 2019
Ipsos MORI Social Media Britain November 2019Ipsos MORI Social Media Britain November 2019
Ipsos MORI Social Media Britain November 2019
 
Ipsos MORI 2019 General Election Campign Tracker - Housing
Ipsos MORI 2019 General Election Campign Tracker - HousingIpsos MORI 2019 General Election Campign Tracker - Housing
Ipsos MORI 2019 General Election Campign Tracker - Housing
 
Ipsos MORI Political Monitor - 6 December 2019
Ipsos MORI Political Monitor - 6 December 2019Ipsos MORI Political Monitor - 6 December 2019
Ipsos MORI Political Monitor - 6 December 2019
 

Último

bhubaneswar Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
bhubaneswar Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meetbhubaneswar Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
bhubaneswar Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetCall Girls Service
 
Enjoyment ★ 8854095900 Indian Call Girls In Dehradun 🍆🍌 By Dehradun Call Girl ★
Enjoyment ★ 8854095900 Indian Call Girls In Dehradun 🍆🍌 By Dehradun Call Girl ★Enjoyment ★ 8854095900 Indian Call Girls In Dehradun 🍆🍌 By Dehradun Call Girl ★
Enjoyment ★ 8854095900 Indian Call Girls In Dehradun 🍆🍌 By Dehradun Call Girl ★indiancallgirl4rent
 
Hubli Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Hubli Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetHubli Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Hubli Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetCall Girls Service
 
(Sonam Bajaj) Call Girl in Jaipur- 09257276172 Escorts Service 50% Off with C...
(Sonam Bajaj) Call Girl in Jaipur- 09257276172 Escorts Service 50% Off with C...(Sonam Bajaj) Call Girl in Jaipur- 09257276172 Escorts Service 50% Off with C...
(Sonam Bajaj) Call Girl in Jaipur- 09257276172 Escorts Service 50% Off with C...indiancallgirl4rent
 
Bareilly Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Bareilly Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetBareilly Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Bareilly Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetCall Girls Service
 
Ozhukarai Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Ozhukarai Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetOzhukarai Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Ozhukarai Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetCall Girls Service
 
VIP Call Girl DLF Phase 2 Gurgaon (Noida) Just Meet Me@ 9711199012
VIP Call Girl DLF Phase 2 Gurgaon (Noida) Just Meet Me@ 9711199012VIP Call Girl DLF Phase 2 Gurgaon (Noida) Just Meet Me@ 9711199012
VIP Call Girl DLF Phase 2 Gurgaon (Noida) Just Meet Me@ 9711199012adityaroy0215
 
Muzaffarpur Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Muzaffarpur Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetMuzaffarpur Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Muzaffarpur Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetCall Girls Service
 
VIP Call Girls Noida Sia 9711199171 High Class Call Girl Near Me
VIP Call Girls Noida Sia 9711199171 High Class Call Girl Near MeVIP Call Girls Noida Sia 9711199171 High Class Call Girl Near Me
VIP Call Girls Noida Sia 9711199171 High Class Call Girl Near Memriyagarg453
 
Mangalore Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Mangalore Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetMangalore Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Mangalore Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetCall Girls Service
 
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real MeetCall Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meetpriyashah722354
 
Ernakulam Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Ernakulam Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetErnakulam Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Ernakulam Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetCall Girls Chandigarh
 
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR Call G...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR   Call G...❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR   Call G...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR Call G...Gfnyt.com
 
❤️♀️@ Jaipur Call Girls ❤️♀️@ Jaispreet Call Girl Services in Jaipur QRYPCF ...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Jaispreet Call Girl Services in Jaipur QRYPCF  ...❤️♀️@ Jaipur Call Girls ❤️♀️@ Jaispreet Call Girl Services in Jaipur QRYPCF  ...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Jaispreet Call Girl Services in Jaipur QRYPCF ...Gfnyt.com
 
❤️♀️@ Jaipur Call Girl Agency ❤️♀️@ Manjeet Russian Call Girls Service in Jai...
❤️♀️@ Jaipur Call Girl Agency ❤️♀️@ Manjeet Russian Call Girls Service in Jai...❤️♀️@ Jaipur Call Girl Agency ❤️♀️@ Manjeet Russian Call Girls Service in Jai...
❤️♀️@ Jaipur Call Girl Agency ❤️♀️@ Manjeet Russian Call Girls Service in Jai...Gfnyt.com
 
VIP Call Girl Sector 32 Noida Just Book Me 9711199171
VIP Call Girl Sector 32 Noida Just Book Me 9711199171VIP Call Girl Sector 32 Noida Just Book Me 9711199171
VIP Call Girl Sector 32 Noida Just Book Me 9711199171Call Girls Service Gurgaon
 
Call Girls Service Faridabad 📲 9999965857 ヅ10k NiGhT Call Girls In Faridabad
Call Girls Service Faridabad 📲 9999965857 ヅ10k NiGhT Call Girls In FaridabadCall Girls Service Faridabad 📲 9999965857 ヅ10k NiGhT Call Girls In Faridabad
Call Girls Service Faridabad 📲 9999965857 ヅ10k NiGhT Call Girls In Faridabadgragmanisha42
 
Russian Call Girls Kota * 8250192130 Service starts from just ₹9999 ✅
Russian Call Girls Kota * 8250192130 Service starts from just ₹9999 ✅Russian Call Girls Kota * 8250192130 Service starts from just ₹9999 ✅
Russian Call Girls Kota * 8250192130 Service starts from just ₹9999 ✅gragmanisha42
 
dhanbad Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
dhanbad Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meetdhanbad Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
dhanbad Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetCall Girls Service
 
Punjab❤️Call girls in Mohali ☎️7435815124☎️ Call Girl service in Mohali☎️ Moh...
Punjab❤️Call girls in Mohali ☎️7435815124☎️ Call Girl service in Mohali☎️ Moh...Punjab❤️Call girls in Mohali ☎️7435815124☎️ Call Girl service in Mohali☎️ Moh...
Punjab❤️Call girls in Mohali ☎️7435815124☎️ Call Girl service in Mohali☎️ Moh...Sheetaleventcompany
 

Último (20)

bhubaneswar Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
bhubaneswar Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meetbhubaneswar Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
bhubaneswar Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
 
Enjoyment ★ 8854095900 Indian Call Girls In Dehradun 🍆🍌 By Dehradun Call Girl ★
Enjoyment ★ 8854095900 Indian Call Girls In Dehradun 🍆🍌 By Dehradun Call Girl ★Enjoyment ★ 8854095900 Indian Call Girls In Dehradun 🍆🍌 By Dehradun Call Girl ★
Enjoyment ★ 8854095900 Indian Call Girls In Dehradun 🍆🍌 By Dehradun Call Girl ★
 
Hubli Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Hubli Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetHubli Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Hubli Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
 
(Sonam Bajaj) Call Girl in Jaipur- 09257276172 Escorts Service 50% Off with C...
(Sonam Bajaj) Call Girl in Jaipur- 09257276172 Escorts Service 50% Off with C...(Sonam Bajaj) Call Girl in Jaipur- 09257276172 Escorts Service 50% Off with C...
(Sonam Bajaj) Call Girl in Jaipur- 09257276172 Escorts Service 50% Off with C...
 
Bareilly Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Bareilly Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetBareilly Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Bareilly Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
 
Ozhukarai Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Ozhukarai Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetOzhukarai Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Ozhukarai Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
 
VIP Call Girl DLF Phase 2 Gurgaon (Noida) Just Meet Me@ 9711199012
VIP Call Girl DLF Phase 2 Gurgaon (Noida) Just Meet Me@ 9711199012VIP Call Girl DLF Phase 2 Gurgaon (Noida) Just Meet Me@ 9711199012
VIP Call Girl DLF Phase 2 Gurgaon (Noida) Just Meet Me@ 9711199012
 
Muzaffarpur Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Muzaffarpur Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetMuzaffarpur Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Muzaffarpur Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
 
VIP Call Girls Noida Sia 9711199171 High Class Call Girl Near Me
VIP Call Girls Noida Sia 9711199171 High Class Call Girl Near MeVIP Call Girls Noida Sia 9711199171 High Class Call Girl Near Me
VIP Call Girls Noida Sia 9711199171 High Class Call Girl Near Me
 
Mangalore Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Mangalore Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetMangalore Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Mangalore Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
 
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real MeetCall Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
Call Girls Chandigarh 👙 7001035870 👙 Genuine WhatsApp Number for Real Meet
 
Ernakulam Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Ernakulam Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real MeetErnakulam Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
Ernakulam Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
 
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR Call G...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR   Call G...❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR   Call G...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Meghna Jaipur Call Girls Number CRTHNR Call G...
 
❤️♀️@ Jaipur Call Girls ❤️♀️@ Jaispreet Call Girl Services in Jaipur QRYPCF ...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Jaispreet Call Girl Services in Jaipur QRYPCF  ...❤️♀️@ Jaipur Call Girls ❤️♀️@ Jaispreet Call Girl Services in Jaipur QRYPCF  ...
❤️♀️@ Jaipur Call Girls ❤️♀️@ Jaispreet Call Girl Services in Jaipur QRYPCF ...
 
❤️♀️@ Jaipur Call Girl Agency ❤️♀️@ Manjeet Russian Call Girls Service in Jai...
❤️♀️@ Jaipur Call Girl Agency ❤️♀️@ Manjeet Russian Call Girls Service in Jai...❤️♀️@ Jaipur Call Girl Agency ❤️♀️@ Manjeet Russian Call Girls Service in Jai...
❤️♀️@ Jaipur Call Girl Agency ❤️♀️@ Manjeet Russian Call Girls Service in Jai...
 
VIP Call Girl Sector 32 Noida Just Book Me 9711199171
VIP Call Girl Sector 32 Noida Just Book Me 9711199171VIP Call Girl Sector 32 Noida Just Book Me 9711199171
VIP Call Girl Sector 32 Noida Just Book Me 9711199171
 
Call Girls Service Faridabad 📲 9999965857 ヅ10k NiGhT Call Girls In Faridabad
Call Girls Service Faridabad 📲 9999965857 ヅ10k NiGhT Call Girls In FaridabadCall Girls Service Faridabad 📲 9999965857 ヅ10k NiGhT Call Girls In Faridabad
Call Girls Service Faridabad 📲 9999965857 ヅ10k NiGhT Call Girls In Faridabad
 
Russian Call Girls Kota * 8250192130 Service starts from just ₹9999 ✅
Russian Call Girls Kota * 8250192130 Service starts from just ₹9999 ✅Russian Call Girls Kota * 8250192130 Service starts from just ₹9999 ✅
Russian Call Girls Kota * 8250192130 Service starts from just ₹9999 ✅
 
dhanbad Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
dhanbad Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meetdhanbad Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
dhanbad Call Girls 👙 6297143586 👙 Genuine WhatsApp Number for Real Meet
 
Punjab❤️Call girls in Mohali ☎️7435815124☎️ Call Girl service in Mohali☎️ Moh...
Punjab❤️Call girls in Mohali ☎️7435815124☎️ Call Girl service in Mohali☎️ Moh...Punjab❤️Call girls in Mohali ☎️7435815124☎️ Call Girl service in Mohali☎️ Moh...
Punjab❤️Call girls in Mohali ☎️7435815124☎️ Call Girl service in Mohali☎️ Moh...
 

Commercial access to health data

  • 1. Commercial access to health data Key findings April 2016
  • 2. 2 Recap of methodology 16 qualitative workshops across GB, 246 individuals Quantitative survey of 2,017 GB adults 8 x general public 3 x GPs and hospital doctors 4 x long-term health conditions 1 x cohort members Quantitative research run as follow-up to qualitative work Face-to-face interviews
  • 4. 4 Lots of initial uncertainty and wariness Lack of understanding around current data-use and sharing Most haven’t thought about private sector/academic/charities’ involvement in NHS Individual-level data thought of as ‘my data’. Aggregate data as ‘statistics’ (instinctively more benign) Little knowledge of safeguards and how datasets are handled Most assume rules are in place ?!?Future communication challenges
  • 5. 5 It’s a one-way mirror: they know everything about you – but we don’t know what they’re doing with that
  • 6. 6 Two traditional mindsets for data sharing 1. Commercial transactions: ‘My data has financial value’ Buying Doing Data is given as part of a deal: consumer gets something in return Expectation it will be used and shared for financial gain by the collector Actively given Passively taken Wary mindset
  • 7. 7 2. Social contract mindset: ‘We’re all helping each other’ Service using Being Data is given in confidence in exchange for a service, assumption it will be used for that purpose only Assumption that only high- level data is collected and for health purposes Actively given Passively taken Open, vulnerable mindset Two traditional mindsets for data sharing
  • 8. 8 Commercial access to health data constitutes ‘context collapse’ Should I be a helpful citizen? Being Is it being passively taken? Am I actively giving it? Doing Buying Service using Should I be wary? ? Concern for vulnerable groups, risk of exploitation Tendency to revert to assumptions and prejudices e.g. ‘private companies cannot be trusted’
  • 9. 9 What drives acceptability: four key tests More acceptable Less acceptable/red lines 1. WHY 2. WHO 3. WHAT 4. HOW Clear public benefit Public health providers Aggregate data, passively collected Secure storage & regulation is assumed Solely private benefit No link to improving public health Identifiable personal details with real world implications Mix of public and private benefit For profit but in health sector Aggregate but risk of jigsaw ID Uncertain future users – e.g. ‘sharing on‘ with third party Genetic data; uncertain future uses
  • 10. 10 The public can see opportunities 1. WHY 2. WHO 3. WHAT 4. HOW Clear public benefit Public health providers Aggregate data Secure storage & regulation is assumed Primary driver: without this, majority say data shouldn’t be shared NHS, Charities, Academic researchers and partnerships involving them Aggregate data, passively collected (i.e. no personal details ever attached) less risky Transparency, independent scrutiny, sanctions and fines for misuse reassure
  • 11. 11 But they also have concerns 1. WHY 2. WHO 3. WHAT 4. HOW Mix of public and private benefit For profit but in health sector Aggregate but risk of jigsaw ID Secure storage & regulation is assumed For some acceptable: WHO becomes more important – is the organisation trusted? e.g. analytics company working with NHS. Some fears about ‘big pharma’ & retail – makes regulation more important If originally taken from identifiable data - potential risk to the individual Doubts generally linked to WHO is handling the data and whether they are trusted; regulation helps reassure
  • 12. 12 …and some red lines 1. WHY 2. WHO 3. WHAT 4. HOW Solely private benefit No link to improving public health Identifiable personal details with real world implications Secure storage & regulation is assumed If no clear public benefit, sharing is unacceptable to most Insurance companies, marketing companies; never benefit public, motivated by profit Concerns about impact on employment prospects, insurance premiums etc. Uncertain future users – e.g. ‘sharing on‘ with third party Genetic data; uncertain future uses No regulation/scrutiny to ensure data is used for intended purpose and not passed on
  • 13. 13 Seven mindsets influence views Pragmatic Concerned with impact of privacy at personal level Abstract Concern for human rights, social goods, and impact on everyone Open to commercial interest Accepting of private sector involvement in general Wary of commercial interest Sceptical of private sector involvement Commercial access necessary for social development; public benefits worth risk to personal privacy. Duty to share health data? Less concerned with public benefit, risks to society; neutral stance towards commercial orgs (including marketing and insurance). Not worried/haven’t really thought about security risks. Fear large-scale negative impact on all society: do not trust commercial orgs. ‘Big Brother’ society where commercial use of data worsens social inequality. Sceptical of commercial motives and coexistence of public and private benefit. Lack faith in systems. Recognise benefits but commercial involvement is imperfect solution. Pro opt out.
  • 15. 15 5 5 12 13 11 21 25 25 29 25 27 21 31 31 16 1 1 1 Academics researchers Commercial organisations NHS A great deal A fair amount Just a little Heard of, know nothing about Never heard of Don’t know Awareness is an initial stumbling block to understanding Source: Ipsos MORI/Wellcome Trust Base: 2,017 GB adults, aged 16+ How much, if anything, would you say you know about how the following organisations use health data for these purposes?* 33% 21% *See report for full question wording 56%18% 16% 58%
  • 16. 16 But more support than oppose health data sharing for research 18 3519 13 13 2 Strongly support Tend to support Neither support nor oppose Tend to oppose Strongly oppose Don't know Source: Ipsos MORI/Wellcome Trust Base: 2,017 GB adults, aged 16+ To what extent, if at all, would you support your health data being accessed by commercial organisations if they are undertaking health research?* 54% 26% *See report for full question wording Educational attainment: Degree (59%) A-level (57%) GCSE (52%) No qualifications (43%) Knowledge factors influence support Social grade: AB (62%) C1 (53%) C2 (53%) DE (46%) Data usage awareness: Aware (56%-59%) Not aware (45%- 47%) Internet access: Daily users (56%) Less frequent (52%) No access (39%)
  • 17. 17 30 32 23 22 24 30 9 7 10 7 2 2 Drug company Public health regulator 5 - completely acceptable 4 3 2 1 - completely unacceptable Don't know Drug companies aren’t deal-breakers… Source: Ipsos MORI/Wellcome Trust Base: split sample, bases on chart [INTRODUCTION about public health regulator OR drug company running tests on a new drug] …On a scale of 1-5, how acceptable, if at all, do you find this use of data?* *See report for full question wording (997) (1,020)
  • 18. 18 10 5 28 21 26 27 18 21 18 24 1 3 Marketing Insurance Strongly agree Tend to agree Neither agree nor disagree Tend to disagree Strongly disagree …but insurance and marketing purposes might be Source: Ipsos MORI/Wellcome Trust Base: split sample, bases on chart To what extent, if at all, would you support insurance companies using health data collected in the NHS to further develop their health insurance prices?* To what extent, if at all, would you support companies using health data collected in the NHS to help target health products at different groups of people?* 26% 44% 37% 36% *See report for full question wording (992) (1,025)
  • 19. 19 Support for commercial access if research at risk 31 31 14 12 13 2 Agree much more with B than with A Agree a little more with B than with A Agree equally with both / don't agree with either Agree a little more with A than with B Source: Ipsos MORI/Wellcome Trust Base: 974 GB adults, aged 16+ Which of the following statements comes closest to your view of health data being shared with commercial organisations?* 61% 25% *See report for full question wording B. The research should be conducted by commercial organisations if there is a possibility of new treatments for diseases being developed A. I would not want commercial organisations to have access to anonymised health data, even if this means the research does not take place
  • 20. 20 Differences within differences – not all sceptics the same Source: Ipsos MORI/Wellcome Trust Base: All those who do not want commercial organisations to have access to health data under any circumstances (356) Which of the following views, if any, comes closest to why you do not want commercial organisations to have access to health data under any circumstances?* *See report for full question wording 4 2 2 2 2 6 8 8 13 16 18 20They cannot be trusted to store the data safely I don't agree profit should be made from NHS data, even if there are benefits Commercial orgs cannot be trusted to put society before profit They might sell data onto another commercial org and you cannot control where it ends up If commercial orgs access the data, they could manipulate it and this is unfair They may try and market products and services to me There might be negative consequences for me or my family They may re-identify me even though names and personal information might be removed from the data There might be negative consequences for the community Even if they misuse the data they won't be punished Don’t know Other 49% of people asked this question aligned with reasons related to things that could harm them or their family 46% aligned themselves with social reasons; that commercial orgs having health data could negatively impact society
  • 22. 22 We need a shared understanding of value Aggregate Recognised as a national resource, but with conditions Long-term value to society, not just private interest/financial gain Support for public goods e.g. NHS Fair process – data shared when vulnerable ‘service use mind set’ so should not be exploited Individual Harder to grasp, questions of ownership and perverse incentives Health data as currency – potential benefits for those without money But worries over unintended consequences – What if the wealthier opt out leading to bad datasets? Will vulnerable groups be exploited for their data? Communications need to take into account how the public conceive of different types of data
  • 23. 23 And a new social contract Public question if commercial access is consistent with ‘promotion of health’ Care Act 2014 – data can be shared for provision of care or promotion of health Scepticism towards commercial interest leading to socially beneficial outcomes Even the more pragmatic lack awareness of the role commercial interests play in health (e.g. provide essential services/drug trials) New innovations mean new challenges Rise of wearables, passive data collection without full consent (e.g. small print Ts and Cs) links to questions of ownership and ethics Individuals unaware of potential autonomy to shape own care Communications need to: • Tackle scepticism and low awareness of commercial access • Signal potential benefits and risks of data and tech innovations
  • 24. 24 Currently, “no job description for being a citizen”  Public don’t currently know enough to be guardians of their own health data They have low awareness of the “quantified self”, many expect practitioners to make decisions for them And low understanding of consent models, implications of ‘opt-out’ on accuracy  There is space for a further conversation about future healthcare delivery: role of state, commerce, big data and individual citizens  Shared learnings will be key: Academy of Medical Sciences, ‘Exploring a new social contract for medical innovation’, Royal Society’s work on Machine Learning, Cabinet Office on Data Science Ethics
  • 25. 25 What next? Think about how commercial access is managed not just how it is communicated – fair processes and appropriate safeguards will play an important part in driving or hindering trust Identify public information needs (cf. other research). E.g. technical terms about data/data science/data collection, safeguards, consent options and role of commerce in health Safeguards help but there is much leg work to do before this – need to establish public benefit and tackle scepticism Consider terminology and public understanding of word ‘commercial’ – being specific will help remove public biases
  • 26. 26 Done well, could drive trust in government and create optimism around future health data-sharing and role of commerce in health But done poorly, could lead to ‘confidence collapse’ and jeopardise future public support Rather put the brakes on now… Public clearly concerned about commercial access and broader implications of a data-rich world If health data is a national resource then how it is handled now will impact future opportunities
  • 27. Q & A For more info: naomi.boal@ipsos.com debbie.chan@ipsos.com stephanie.crowe@ipsos.com