> Definition of RWD > RWD - Big Data Characteristics > Sources of RWD > Important Stakeholders > Benefits of RWD > Why Data Sharing is Important? > Benefits of Data Sharing > Who Benefits? > Ultimate Goals > Case Studies > Challenges > Data Privacy Scenario > Data Security in India > Regulatory Perspectives Around RWD > How to Encourage Data Sharing?

1. Importance of RWD in HEOR:
An Industrial Perspective
Ms. Dimple Arora
Director | MarksMan Healthcare Communications
Treasurer | ISPOR - Mumbai

2. Expectation v/s Reality
Rising Costs
Varying Quality
Fragmented Care Model
Missing Links in Patient Journey
Lack of RWD
Cost Reduction
Expanding Precision Medicine
Transforming Care Delivery
Improving Patient Experience
Digitalizing Healthcare
Data Analytics

3. “Real World Data (RWD) as defined by US-FDA is the data collected from sources outside of
traditional clinical trials, which can range from large simple trials or pragmatic clinical trials,
prospective observational or registry studies, retrospective database studies to case reports,
administrative or healthcare claims, electronic health records (EHRs), data obtained as part of
public health investigation or routine public health surveillance, and registries”
Definition of RWD

4. RWD - Big Data Characteristics
“large volumes of high velocity,
complex, and variable data
that require advanced
techniques and technologies to
enable the capture, storage,
distribution, management and
analysis of the information”
Variety Velocity
Veracity Volume

5. Sources of RWD
The clinical practice and
reimbursement policies are
now targeting outcome, in
addition to just the treatment
administration. This is a major
pushing force for compilation
and evaluation of big data

6. Important Stakeholders
Areas to Improve:
• Epidemiology
• Clinical Trials/Analytics
• Genomics
• Health insurance
• Medical billing operations/Service Segments
• Patient care
• Hospitals
• Physician Practices
• Operational Analytics
Data
Holders
Laboratories
Healthcare
Providers
PatientsPayers
Government

7. Benefits of RWD
• RWD is generalizable because of larger
sample size and actual clinical scenarios
• RWD analyses/utilizes extensive
health records from all possible
sources of a particular geographical
area (e.g. health records, registries etc.)
to generate evidence
• It can help in generating evidence about
many aspects like natural disease
• It can help in providing information
about rare diseases
• Comparison of available treatment
options is possible
RWD
• Social and Behavioral Data
• mHealth
• eHealth
• Smart Health
• Tele health
• Biomedical Data
Precision
Medicine
Personalized Patient Care

8. Why Data Sharing is Important?
• Data is the basis for healthcare and medical research
• The increasing gap between healthcare costs and outcomes
can be attributed to poor management of research insights,
poor usage of available evidence, and poor capture of care
experience as well as valuable data
• Around 30% of the stored global data is generated within the
healthcare industry
• A single patient normally generates about 80 MB of data every
year in the form of imaging and EMRs
• Data exchange is now emerging as the new currency in
healthcare
• Open data sharing is vital to understand the source of ever
expanding base of scientific knowledge
• Open data will most certainly reduce waste in case of time,
costs, and patient burden
Raw Data
Knowledge
Practice
Change
In order to fully utilize the power of data and data
sharing, providers, payers, and purchasers must be
willing to work together to share cost and quality
data across the entire healthcare system

9. Benefits of Data Sharing
• Genetic studies, cancer/chronic disease
registries, substance abuse, population health
management, larger-scale analytics,
epidemiology/disease tracking, and even
interoperability for routine patient care in the
emergency department are all potential uses
of data sharing
• Data exchange is essential for ensuring that
best practices can be shared between
healthcare organizations, or even between
entities in other industries, such as financial
institutions or government agencies
Information sharing matters
because we all need to be aware
of what is going on and
understand the consequences of
what may occur. We all can be
the eyes and ears of an
organization.

10. Who Benefits?
Big Data
Analytics
Pharmaceutical
industry
Healthcare
providers
PatientsPayers
Government
• Value based medicine
• Low cost
• Better care
• Evidence based medicine
• Protocol driven treatment
• Gain patient confidence
• Improved clinical trial design
• Better access of medicines
• Better patient outcomes
• Healthcare fraud detection
• Patient profile analytics
• Fee for performance
• Early stage disease detection
• Remote monitoring of diseases
• Healthcare insurance

11. Ultimate Goals
• Better healthcare decision making
• Improve healthcare outcomes by
providing value based care
• Encourage quality care to patients
benefitting payers as well as investors
• Shorten hospital stays
• Build healthier communities relying on
preventative measures
• Reduce the healthcare cost

12. Case Studies
Clinical
experience
v/s clinical
research
Real World Practice
Real World
Data
analytics
Desipramine for oncology
Wearable
Technologies
Reimbursement Decisions

13. Challenges
• Incompatible data formats
• Lack of real time data
• Lag between data collection and processing
• Availability of numerous analytics algorithms, models and methods
• Managerial issues of ownerships, governance and standards
• Privacy and security issues
• Quality assurance of data

14. Data Privacy Scenario
• Data security concerns are often one reason that
providers are hesitant to share data
• Data protection involves taking adequate steps to
protect data from accidental or malevolent leak
• Data privacy involves getting consent from
individuals before collecting their information,
being transparent about why and how the
information will be used, and deleting the
information when it is no longer needed or when
consent is withdrawn.
USA - HIPAA Europe - GDPR
Japan - APPI India - DISHA

15. Data Security in India -
• To facilitate promotion/adoption of e-Health standards along with entailing privacy and security
measures for electronic health data, regulation of storage, and exchange of electronic health records
(EHRs); the Ministry of Health and Family Welfare, Govt. of India, is planning to enforce a ‘Digital
Information Security in Healthcare Act’ (DISHA)
• The purpose of this act is to ensure electronic health data privacy, confidentiality, security and
standardization, and to provide for establishment of ‘National Digital Health Authority’, Health
Information Exchanges, and related matters
• As per the draft, the owners have the right to privacy, confidentiality, and security of their digital health
data and the right to give or refuse consent for generation and collection of such data. Additionally, the
owner of the data shall hold the rights to – i) give/refuse/withdraw consent for using this data, ii) data
collection, iii) transparency, iv) rectification, v) sharing, vi) not to be refused health service if they refuse
to give the consent for data use, and vii) protection.
• This law will form the foundation for creating digital health records in India, as it will enable the digital
sharing of personal health records with hospitals and clinics, and between hospitals and clinics.

16. Regulatory Perspectives Around RWD
• Over the years, the need for generation of real
world data (RWD) has grown stronger
• It is important to regulate the design and
conduct of real world studies on the similar
pattern of RCTs
• World over, the medical agencies and
professional societies are conducting workshops
to generate awareness, and are in the process of
making drafts and guidelines for RWE/RWD
• Further to FDA and EMA role in RWE, the
National Health Services (NHS) has collaborated
with Cancer Drugs Fund (CDF) to collect RWD to
improve the health care system

17. How to Encourage Data Sharing?
• An ‘opt-in’ approach based on active patient
consent
• Educate consumers and policy makers on the
importance of data sharing
• Association among groups by means of
workshops and agendas for data sharing
• Implementation of data sharing policies and
campaigns
• Use of incentives
• Introduction to data systems for data deposition
in order to integrate a credit system through
data linkage
• Group collaborations to use data attribution as
an incentive
Secure healthcare data
sharing options have the
potential to greatly benefit
healthcare organizations,
but entities should
understand the challenges
of interoperability as well

18. Way Forward…
• Making compatible data formats
• Generating high-quality and reliable data sources
• Focusing on creating longitudinal database
• Bridging the gap between data collection and processing
• Application of numerous analytic algorithms, models and methods
• Merging and integrating inpatient, outpatient, pharmacy resource
utilization, and clinical outcomes data seamlessly
• Overcoming managerial issues of ownerships, governance and
standards
• Complying privacy and security laws
• Maintaining quality assurance of data
• Collaborating technical expertise and scientific knowledge among
various stakeholders

19. Career Options
HEOR
Pharma/Biotech/Med-
Tech
•Market Access
•HEOR
•Pricing and
Reimbursement
•Economic Modelers
Consulting
•Medical Information
Specialists
•Evidence Analyst
•HEOR Writing
•Database Manager
•Economic Modelers
Research
•Evidence Synthesis
•Practice Guidelines
•Consensus Generation
CROs
•CRCs
•Regulatory Writing
(RWE)
•Bio-statisticians
•Medical
Writing(HEOR)
Government
•Policy Makers
•Health Economists
•Program Budgeting
Insurance
•Claims Data
•Policy Making
•Data Analytics
Teaching
•Trainers/Lecturers
•PhDs (Higher Studies)
Hospitals
•EMRs
•Disease Registries
•Formularies

20. Certification Programme
“Fundamentals of Health Economics and Outcomes Research”

21. Thank you!
dimple.d@marksmanhealthcare.com