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Scope and Sources of RWE and Value of Data
Sharing in Healthcare
Ms. Dimple Arora
Director, MarksMan Healthcare Communications Pvt. Ltd.
Treasurer, ISPOR-Mumbai-India Chapter
Course Director, HEOR Certification Programme by MarksMan Academy of Health Sciences (MAHS)
HTA and Real World Evidence (RWE)
Healthcare Technology Assessment
 Disparity in healthcare facilities
 Waste of resources
 Inappropriate investments
 Increasing healthcare costs
Technological Advancement Real World Scenario
• Improves the access to healthcare facilities
• Appropriate channelization of investments
• Bridging gap between technology and its optimum utilization
• A tool for implementation of Universal Health Coverage
• Preparation of clinical practice guidelines and treatment protocols
• To set prices of drugs and other medical technologies
• Formulation of reimbursement policies
• Introduction of new drug therapies
Why RWE? - Limitations with RCT
• Controlled environment
• Small no./selective group of patients
• Rigid inclusion/exclusion criteria
• Expensive
• Intensive monitoring
• Prioritized as per sponsor
• Difficult to access clinical trial data
• Results of RCTs not be relevant for all treatment
outcomes
• Results difficult to generalize
• Difficult to conduct for rare diseases
• Publication bias present
Too Narrow
Too FewToo Short
RCT v/s RWE
Both RCT and RWE are essential tools
of evidence generation, starting from
drug discovery to clinical evaluation to
approval and lastly the post-marketing
experience. Both types of studies
complement each other and form an
integral component of healthcare
research.
“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 RWE
Sources of RWE
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
Advantages of RWE
• RWE is generalizable because of larger sample size and actual
clinical scenarios
• RWE 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
• Less investment is required for conducting real world studies as
compared to RCTs
• Minimal risk of publication bias
Evidence Based
Medicine should be
from the daily clinical
practice also, and not
only from research
Application of Real World Data
(RWD) in RWE
“Large, routinely or automatically collected datasets which are electronically
captured and stored”
Benefits of RWD in RWE
• Increasing the effectiveness and
quality of treatments
• Early detection of diseases
• Evidence-based medicine
• Comparative effectiveness research
• Genomic analytics
• Quick and efficient detection of health
care fraud
• To monitor health and predict adverse
event
RWD
• Social and Behavioral Data
• mHealth
• eHealth
• Smart Health
• Tele health
• Biomedical Data
Precision
Medicine
Personalized patient care
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
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
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
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.
Case Studies
Clinical
experience
v/s clinical
research
Real World Practice
Real World
Data
analytics
Desipramine for oncology
Wearable
Technologies
Reimbursement Decisions
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
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.
Regulatory Perspectives Around RWD/RWE
• Over the years, the need for generation of real
world evidence (RWE) 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
• Further to FDA and EMA role in RWE, the
National Health Services (NHS) has
collaborated with Cancer Drugs Fund (CDF) to
collect real data to improve the health care
system
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
Certification Programme
“Fundamentals of Health Economics and
Outcomes Research”
Thank you!
dimple.d@marksmanhealthcare.com

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Scope and Sources of RWE and Value of Data Sharing in Healthcare

  • 1. Scope and Sources of RWE and Value of Data Sharing in Healthcare Ms. Dimple Arora Director, MarksMan Healthcare Communications Pvt. Ltd. Treasurer, ISPOR-Mumbai-India Chapter Course Director, HEOR Certification Programme by MarksMan Academy of Health Sciences (MAHS)
  • 2. HTA and Real World Evidence (RWE) Healthcare Technology Assessment  Disparity in healthcare facilities  Waste of resources  Inappropriate investments  Increasing healthcare costs Technological Advancement Real World Scenario • Improves the access to healthcare facilities • Appropriate channelization of investments • Bridging gap between technology and its optimum utilization • A tool for implementation of Universal Health Coverage • Preparation of clinical practice guidelines and treatment protocols • To set prices of drugs and other medical technologies • Formulation of reimbursement policies • Introduction of new drug therapies
  • 3. Why RWE? - Limitations with RCT • Controlled environment • Small no./selective group of patients • Rigid inclusion/exclusion criteria • Expensive • Intensive monitoring • Prioritized as per sponsor • Difficult to access clinical trial data • Results of RCTs not be relevant for all treatment outcomes • Results difficult to generalize • Difficult to conduct for rare diseases • Publication bias present Too Narrow Too FewToo Short
  • 4. RCT v/s RWE Both RCT and RWE are essential tools of evidence generation, starting from drug discovery to clinical evaluation to approval and lastly the post-marketing experience. Both types of studies complement each other and form an integral component of healthcare research.
  • 5. “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 RWE
  • 6. Sources of RWE 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
  • 7. Advantages of RWE • RWE is generalizable because of larger sample size and actual clinical scenarios • RWE 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 • Less investment is required for conducting real world studies as compared to RCTs • Minimal risk of publication bias Evidence Based Medicine should be from the daily clinical practice also, and not only from research
  • 8. Application of Real World Data (RWD) in RWE “Large, routinely or automatically collected datasets which are electronically captured and stored”
  • 9. Benefits of RWD in RWE • Increasing the effectiveness and quality of treatments • Early detection of diseases • Evidence-based medicine • Comparative effectiveness research • Genomic analytics • Quick and efficient detection of health care fraud • To monitor health and predict adverse event RWD • Social and Behavioral Data • mHealth • eHealth • Smart Health • Tele health • Biomedical Data Precision Medicine Personalized patient care
  • 10. 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
  • 11. 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
  • 12. 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
  • 13. 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.
  • 14. Case Studies Clinical experience v/s clinical research Real World Practice Real World Data analytics Desipramine for oncology Wearable Technologies Reimbursement Decisions
  • 15. 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
  • 16. 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.
  • 17. Regulatory Perspectives Around RWD/RWE • Over the years, the need for generation of real world evidence (RWE) 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 • Further to FDA and EMA role in RWE, the National Health Services (NHS) has collaborated with Cancer Drugs Fund (CDF) to collect real data to improve the health care system
  • 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. Certification Programme “Fundamentals of Health Economics and Outcomes Research”