SVMPharma Real World Evidence – Why NHS must embrace Real World Data

Why NHS must embrace
Real World Data
SVMPharma Ltd
CONTACT US
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+44(0) 1252 417030www.svmpharma.com

Why the NHS must embrace Real World Data
© 2015 SVMPharma Ltd. All rights reserved.
2
Contents
EXECUTIVE SUMMARY 3
INTRODUCTION 4
WHAT IS REAL WORLD DATA? 4
DOES THE NHS USE REAL WORLD DATA? 4
WHAT ARE THE OPTIONS FOR DATA COLLECTION IN THE NHS? 5
CONCLUSION 7
REFERENCES 8

3
Executive Summary
The unprecedented operational and financial challenges facing the National Health
Service (NHS) have been well documented and are hardly ever out of the news. The
massive gap in NHS funding in recent years and pressure on services caused by an
aging population with multiple long term conditions are just some of the more widely
reported reasons for the crisis.1
Various thinktanks and policy makers have put
forward solutions to help reduce the pressures on the NHS. Primary among these are
the integration of health and social care, greater emphasis on disease prevention and
the introduction of new models of care into the NHS structure.2
In this paper, we
argue that in order to navigate the difficult balance between financial sustainability
and optimal performance the NHS needs to be more proactive in the collection and
analysis of Real World Data (RWD) and exploit the multiple opportunities for
commissioning RWD analysis at a local and national level. The current status quo and
potential benefits to the NHS of gathering this type of data are also explored.

4
Introduction
There is a broad consensus that in order for the
NHS to continue to meet the objectives and values
for which it was set up, it must change the way in
which it functions as an organisation.3
A downturn
in the UK economy over the last decade or so has
resulted in reduced government funding for the
NHS. This, coupled with increased demand on
services by an aging population means that the
NHS now operates under remarkable financial and
operational pressure.
It is estimated that if the current trajectory of flat
government funding and growth in demand is
maintained, the NHS in England will experience a
funding deficit of around £30 billion per year by
2020/21.4
The NHS itself acknowledges that it
needs to come up with smarter ways of resolving
the financial and productivity challenges it faces,
by promoting intelligent use of research data.5
The
size and scale of the NHS6
and its capacity to offer
a cradle-to-grave service to everyone means that it
possesses an unsurpassed repository of healthcare
data which can be a huge source of information to
improve health outcomes.
What is Real World Data?
The concept of gathering Real World Data has
largely evolved in recent years as a result of the
increased interest by health technology
assessment (HTA) agencies in data which
demonstrates the value and effectiveness of
healthcare interventions. Real World Data (RWD)
collection encompasses anything outside
traditional randomised controlled trials (RCTs) and
goes beyond what is normally investigated during
phase III clinical trials in the evaluation of normal
clinical practice.7
There is increasing acknowledgement that classical
RCTs while crucial to determine the safety and
efficacy of a medicine, are inadequate to evaluate
effectiveness in a practical real-life setting.8 .
RWD
may be sourced from patient databases and
disease registries (e.g. Hospital Episodes Statistics
dataset or Clinical Practice Research Datalink),
patient and population surveys, patient reported
outcome measures (PROMS), patient reported
experience measures (PREMS), observational
studies, clinical audits and service evaluations.
Does the NHS use RWD?
In the UK, the NHS is the predominant source of
clinical and patient data and it is reasonable to
expect that information contained within the data
would be routinely used as a performance
management tool within the organisation.
However, this potential is yet to be realised
because of an apparent lack of awareness of the
concept and its value to decision making. At
present, the principal source of hospital data in
England is the Hospital Episodes Statistics (HES)
dataset. It contains over 125 million records from
hospital Accident and Emergency, in-patient and
outpatient departments every year.9
Analysis of
the HES dataset is
useful to monitor
quality and safety of
clinical procedures
across hospitals and
predict trends in
hospital activity,
resource use and
disease patterns.
Unfortunately, many
clinicians, commissioners and managers remain
largely unaware of the existence of HES or are
apathetic to its usefulness as a strategic planning
and clinical safety tool. 10
These stakeholders are
largely restricted to the Secondary Uses Service
(SUS) dataset which provides relatively basic
information on patients’ hospital procedures and
has problems of poor quality and incomplete
data.11
Clinicians frequently exhibit a distrust of the
integrity of available data and can be suspicious of
the motives behind data collection, questioning
whether the process might be used as a cost-
cutting exercise or an opportunity to exert more
managerial influence over them. 12
Many clinical
audits frequently run in hospitals or the medicines
audits carried out by CCG medicines management
teams do not achieve enough clinician engagement
from the outset and can often focus on a narrow
However, this
potential is yet to
be realised
because of an
apparent lack of
awareness of the
concept and its
value to decision
making.

5
cost-cutting objective. These audits present an
excellent opportunity to gather useful data from
patient records and managers should do more to
engage clinicians and patients to develop broader
outcomes-based objectives which focus on aligning
patients, clinicians and managers’ needs. Analysed
data can potentially
reveal hitherto unseen
opportunities to
optimise resource use
and capacity, drive
efficiency and
promote positive
patient outcomes. This
must be the driving
force behind the
initiation of such
projects.
And there are signs that real world evidence
increasingly influences how the NHS makes
decisions. The controversial off-label use of
bevacizumab (Avastin) in place of ranibizumab
(Lucentis) in the treatment of wet age-related
macular degeneration (AMD) offers a case in
point.13
Real life clinical practice has shown that
both treatments lead to similar outcomes and
many clinicians are willing to use the unlicensed
but cheaper bevacizumab for treatment of wet
AMD. The NHS must strive to routinely evaluate
health interventions in this way to drive access to
innovative treatments and optimise resource use.
It is notable that health technology assessment
bodies are also starting to acknowledge the
importance of using RWD to evaluate the true
value of health technologies.
The National Institute for Health and Care
Excellence (NICE) has indicated its willingness to
explore additional drug analysis designs other than
traditional clinical trials to aid decision-making. It
is, together with other stakeholders across Europe
working to develop standardised methodology for
incorporating RWD into the drug development and
reimbursement process.14
Another significant
observation about data that is currently available
to stakeholders is that they are mainly
retrospective, reporting what has already occurred
(e.g. the number of patients that have had a fall or
perhaps had a drug allergy), but not what is
happening at present or what may happen in
future. In order to maximise the opportunities that
real life data presents, the NHS needs not only to
collect and analyse data, but attempt to gain an
insight into the future by using innovative
predictive analytics tools. Predictive analysis
involves the use of technology and statistical
modelling methods to search through massive
amounts of data and analysing these to predict
individualised patient outcomes.15
This approach
has the capability to provide solutions to a range of
healthcare problems, from assessing individual
patients’ risk of contracting disease and identifying
the most suitable treatments to reducing
readmission rates and predicting healthcare
workforce requirements.16
A newly established National Information Board
(NIB) charged with defining information
technology strategy for the health and care system
recently set out a framework for the
transformation of care quality and outcomes
through data and technology. It plans to make
patient records accessible online in real time and,
enable data integration across various health and
care pathways.17
In addition to these, the NIB
would do well to actively embrace the concept of
predictive analytics so as to tap into the
opportunities it offers for transforming healthcare
and reach out to partners both within and outside
of the NHS to ensure that the organisation does not
miss out on what many observers consider to be
the next big revolution in healthcare.18
What are the options for data
collection in the NHS?
RWD evaluation has for the most part been driven
by the life sciences industry primarily to
demonstrate the real world value and
effectiveness of health technologies to
reimbursement authorities. Some of these
projects have been undertaken under a joint
working arrangement between industry and the
NHS where both parties pool together skills and
Analysed data can
potentially reveal
hitherto unseen
opportunities to
optimise resource
use and capacity,
drive efficiency
and promote
positive patient
outcomes

6
resources in order to achieve aligned and agreed
objectives which are targeted to improve patient
outcomes.
The Salford Lung Study which was a collaboration
between the NHS, Manchester University and
Glaxo SmithKline is lauded as a prime example of
this kind of arrangement.19
While there exists vast
opportunity for similar mutually beneficial
alliances to be forged between the NHS and the life
sciences industry this has yet to happen on a large
scale. There are inadequate mechanisms to foster
transparency and trust between the involved
stakeholders (patients, clinicians, commissioners,
regulators and the pharmaceutical industry)
regarding the benefits
of data collection and a
lack of assurance that
appropriate safeguards
to protect personal data
are in place.20
Better
communication and
transparency about the
benefits of RWD
together with the
development of a
robust governance
process for the handling of health data mutually
acceptable to all stakeholders, are some of the
steps which commentators suggest are required to
build trust.21
In contrast to joint working arrangements, the NHS
could also explore the use of innovative RWD
analysis to support commissioning decisions by
working directly with expert consultancies in the
field. Particularly in the area of specialised
commissioning for cancer and rare diseases,
commissioners can use intelligent data analysis to
better understand disease treatment pathways
and the impact of health interventions on
healthcare resources and outcomes. Many
hospital trusts already commission consulting firms
to gather data on patient experience and
satisfaction (e.g. the NHS Friends and Family Test22
)
and may derive further benefit from tapping into
data analytics expertise within these consultancies.
A major advantage of this option is the ability to
conduct independent projects which are free from
bias of interested parties (commissioners or
industry).
Commissioners and clinicians may also choose to
proactively collect “in-house” data to support local
clinical and
commissioning
decision-making. The
routine audits carried
out in primary care and
hospitals must start to
move beyond narrow
cost-saving goals and
more towards
collecting data to
establish “what really
works” in real life clinical practice. Regional
stakeholders should take a cue from NHS
England’s, “Commissioning through Evaluation”
program which aims to gather real world data on
innovative health treatments that are not routinely
funded due to a lack of evidence.23
This is
particularly relevant to those services and
treatments that are accessed by a relatively small
number of patients.
Clinical commissioning groups (CCGs), hospitals
and regional therapeutic guidelines bodies should
collaborate to develop local “commissioning
hotspots” for these treatments. Real life outcomes
data and information obtained from these
hotspots may then be shared to support decision
making across health economies in the same
region. Commissioners in the North East of
England used this approach to support a decision
to fund an innovative treatment, Xiapex (a
collagenase injection used in the treatment of
Dupuytrens contracture).Clinical audit data
demonstrated that Xiapex enhanced patient
experience and cost-effectiveness, leading to a
positive decision by the North East Treatment
Advisory Group (NETAG).24
Xiapex has since been
approved for use in Scotland and Wales and in
some CCGs across England. More recently, doctors
at the Chelsea and Westminster Hospital in London
carried out a real world clinical practice audit of the
effects of dapagliflozin, a new treatment for type 2
diabetes, and compared their results to those
Move beyond
narrow cost
saving goals and
more towards
collecting data to
establish ‘what
really works’ in
real life clinical
practice
There are
inadequate
mechanisms to
foster
transparency and
trust between
stakeholders
regarding the
benefits of data
collection

7
reported in clinical trials.25
The outcome of this
work supported the trust’s decision to commission
dapagliflozin and make it accessible to eligible
patients even before the treatment was approved
by NICE. In addition to improving patients’ access
to innovative treatments, this approach can foster
closer ties between stakeholders and positively
impact service redesign and the development of
mutually beneficial payment mechanisms.
Whatever option is chosen must be overseen by a
robust data governance protocol which ensures
that the process maintains the integrity of
individual patients’ privacy and confidentiality.
Conclusion
It is clear that there is huge potential for RWD to
revolutionise healthcare delivery as we know it.
The current NHS leadership has committed to
promoting innovation and the use of RWD in its
five year plan to transform care,26
and while they
have been generally well received, these plans
stand the risk of remaining just that, if the will and
commitment to implement them does not trickle
down to local grassroots NHS stakeholders.
Overflowing accident and emergency
departments, delayed hospital discharges and the
use of health interventions with inconclusive
treatment outcomes are just some of the real
everyday issues facing the health service. To better
understand these issues and help drive innovative
solutions to solve them, local NHS managers must
invest in RWD.
Data monitoring and analytics can, amongst other
things, help hospitals cut down on administrative
costs, enhance clinicians’ real time decision making
capabilities, improve co-ordination across care
pathways as well as enhance the patient
experience.27
Public hesitation over the extension
of healthcare data use (as observed with the
current debate over care.data)28
- must be matched
with adequate information and re-assurance to the
public about a transparent governance mechanism
which safeguards patients’ privacy. Despite all of
its problems, the NHS still ranks as one of the most
efficient healthcare systems in the world.29
However, in order for it to remain so, and continue
to be at the forefront of developing cutting edge
solutions to healthcare challenges, it cannot afford
to conduct business as usual. The adoption of a
top-to-bottom culture of working with Real World
Data offers a viable opportunity to achieve this.
CONTACT US
Real World Evidence
Influence Mapping
Patient Experience
Healthcare Data Analytics

8
References
1. Ham, Chris. "Reforming the NHS in England: opportunities
and challenges. “ Medico-Legal Journal 81.1 (2013): 2-17.
2. Goodwin, Nick, et al. "Integrated care for patients and
populations: Improving outcomes by working together.”
London: King’s Fund (2012).
3. The NHS Constitution: The NHS belongs to us all
https://www.gov.uk/government/uploads/system/uploads
/attachment_data/file/170656/NHS_Constitution.pdf
4. Adam Roberts, Louise Marshall and Anita Charlesworth.
The funding pressures facing the NHS from 2010/11 to
2021/22: A decade of austerity? The Nuffield Trust (2012)
http://www.nuffieldtrust.org.uk/sites/files/nuffield/12120
3_a_decade_of_austerity_full_report_1.pdf
5. Innovation, Health and Wealth. NHS White Paper (2011)
http://webarchive.nationalarchives.gov.uk/201301071053
54/http:/www.dh.gov.uk/prod_consum_dh/groups/dh_dig
italassets/documents/digitalasset/dh_134597.pdf
6. NHS Workforce: Summary of staff in the NHS: Results from
September 2013 Census. Health and Social Care
Information Centre (2014)
7. Real Life Data : A Growing Need accessed 30/03/15
http://www.ispor.org/news/articles/oct07/rld.asp
8. The Vision for Real World Data – Harnessing the
Opportunities in the UK .Association of the British
Pharmaceutical Industry(ABPI) accessed 30/03/15
http://www.abpi.org.uk/our-
work/library/industry/Documents/Vision-for-Real-World-
Data.pdf
9. Hospital Episodes Statistics (HES) Health and Social Care
Information Centre http://www.hscic.gov.uk/hes
10. Hospital Episode Statistics (HES): Improving the quality and
value of hospital data. A discussion document. Academy
of Medical Royal Colleges (2011)
11. NHS Hospital Data and Datasets: A Consultation. Health
and Social Care Information Centre
(2013)
12. Are clinicians engaged in quality improvement? The Health
Foundation (2011)
http://www.health.org.uk/public/cms/75/76/313/2440/Ar
e%20clinicians%20engaged%20in%20quality%20improvem
ent.pdf?realName=y8NfS4.pdf
13. Steinbrook, Robert. "The price of sight—
Ranibizumab, Bevacizumab, and the treatment of
macular degeneration.” New England Journal of
Medicine 355.14 (2006): 1409-1412.
14. IMI GetReal project https://www.nice.org.uk/about/what-
we-do/research-and-development/imi-getreal-project
15. Winters-Miner, Linda A. Seven ways predictive analytics
can improve healthcare Elsevier Connect (2014)
http://www.elsevier.com/connect/seven-ways-predictive-
analytics-can-improve-healthcare
16. Jeff Elton, Arad Ural Predictive Medicine Depends on
Analytics. Harvard Business Review (2014)
https://hbr.org/2014/10/predictive-medicine-depends-on-
analytics/
17. Personalised Health and Care 2020 Using Data and
Technology to Transform Outcomes for Patients and
Citizens. A Framework for Action. National Information
Board (2014)
https://www.gov.uk/government/uploads/system/uploads
/attachment_data/file/384650/NIB_Report.pdf
18. Groves, Peter, et al. "The ‘big data ‘revolution in
healthcare.” McKinsey Quarterly (2013).
19. New, John P., et al. "Obtaining real-world evidence:
the Salford Lung Study. “ Thorax (2014): thoraxjnl-
2014.
20. Weitzman, Elissa R., et al. "Willingness to share
personal health record data for care improvement and
public health: a survey of experienced personal health
record users.” BMC medical informatics and decision
making 12.1 (2012): 39.
21. Taylor, K .Building trust in the collection and use of real
world health data. Deloitte Blogs (2014)
http://blogs.deloitte.co.uk/health/2014/06/building-trust-
in-the-collection-and-use-of-real-world-health-data.html
22. The NHS Friends and Family Test NHS Choices.
http://www.nhs.uk/nhsengland/aboutnhsservices/pages/n
hs-friends-and-family-test.aspx
23. NHS England Commissioning through Evaluation
http://www.england.nhs.uk/2013/09/26/com-through-
eval/
24. Collagenase (Xiapex®) for Dupuytrens contracture NETAG
Decision Summary Notice
http://www.netag.nhs.uk/files/recommendations/NETAG%
20decision%20summary%20notice%20-
%20Collagenase%20-Xiapex-
%20for%20dupuytrens%20contracture%20-Mar2012.pdf
25. McGovern, Andrew P., et al. "Dapagliflozin: Clinical
practice compared with pre-registration trial
data." British Journal of Diabetes & Vascular
Disease 14.4 (2014): 138-143.
26. Five Year Forward View. NHS England (2014)
http://www.england.nhs.uk/wp-
content/uploads/2014/10/5yfv-web.pdf
27. K.Brimmer 5 ways hospitals can use data analytics.
Healthcare IT News accessed 08/04/2015
http://www.healthcareitnews.com/news/5-ways-hospitals-
can-use-data-analytics
28. Care.data is in chaos. It breaks my heart. Ben Goldacre
The Guardian (February 2014)
http://www.theguardian.com/commentisfree/2014/feb/28
/care-data-is-in-chaos
29. Karen Davis, Kristof Stremikis, David Squires, and Cathy
Schoen Mirror, Mirror on the Wall: How the Performance
of the U.S. Health Care System Compares Internationally
The Commonwealth Fund (2014)
http://www.commonwealthfund.org/~/media/files/publica
tions/fund-
report/2014/jun/1755_davis_mirror_mirror_2014.pdf
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CONTACT SVMPHARMA
Vaneet Nayar
Director SVMPharma
enquiry@svmpharma.com
Tel: +44 (0) 1252 417030
SVMPharma Ltd
Visit svmpharma.com
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