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What We Talk About When We Talk
About Real-world Data?
Nevena Veljkovic
Principal research scientist, Vinca Institute of Nuclear Sciences, University of
Belgrade, National institute of Republic of Serbia
Chief Scientific Officer, Heliant doo
Founder and CEO, Genial doo
PhD Chemistry and chemical engineering, University of Belgrade
Professional interests: computational biology and chemistry, analyses of
clinical data and biomarkers
About me
About HELIANT
HELIANT is a software company
focused on IT solutions for
healthcare and well-being.
HELIANT is leader in the
Western Balkan market.
280
institutions
6
million
prescriptions
per month 5
million
examinations
per month
100 000
users
120
employees
STAKEHOLDERS
• Individuals, patients and families
• Healthcare providers
• Governments & policy makers
• Industry
• Research & educators
and many more…
INDUSTRIES
• Drugs
• Medical Equipment
• Insurance
• Healthcare Facilities
• IT
and many more…
Healthcare ecosystem
Digitalization is changing healthcare
Let’s turn knowledge into innovations for seamless digital patient journeys.
Big Data & Healthcare Analytics
Tan Tock Seng Hospital's operations command center
REAL WORLD DATA (RWD)
&
REAL WORLD EVIDENCE (RWE)
Real World Data (RWD) are the data
relating to patient health status and/or
the delivery of health care routinely
collected from a variety of sources.
Real-World Evidence (RWE) is the clinical
evidence about the usage and potential
benefits or risks of a medical product
derived from analysis of RWD.
USE of RWD
Patient Identification
Resources Management
Scientific Research
Clinical Trials
Precision Public Health
AI & ML Models
Sources of RWD
Wearable devices
Mobile devices
Claims and billing
activities
Electronic Health
records (EHRs)
Disease
registries
Social Media Patient reported Molecular profiling Enviromental
An electronic medical record (EMR) is a
patient’s medical history that is
maintained electronically by a single
provider. It is a digital version of a
patient's paper chart.
An electronic health record (EHR) is a
patient’s medical history that is
maintained electronically by multiple
providers.
TYPES of DATA
• Contact and demographic
information
• Information about visits to
healthcare professionals
• Allergies
• Insurance information
• Family history
• Immunization status
• Information about any
conditions or diseases
• A list of medications
• Records of hospitalization
Disease registries
• Global
• Regional
• National
• Intra-Hospital
Disease Registry a database that stores
detailed information about people with a
specific disease or condition
CHALLENGES & OPPORTUNITIES
Characteristics of RWD
Sub-optimal Data Quality that requires
intensive pre-processing
Unstructured and structured
Inconsistent
Voluminous and dynamic
Incomplete and often missing crucial end points
Subject to bias and measurement errors
Missingness rate is high
Multiple events overlap
Challenges
Data Quality Efficient and practical ML
and statistical procedures
Explainability and
interpretability
Reproducibility and
replicability
Privacy, data sharing Diversity, Equity, Algorithmic
fairness, and Transparency
(DEAT)
Challenges
Adapted from Liu & Panagiotakos, 2022
How to harness the value of data?
Patient data anonymization
Data standards
Standardized Analytics
Regulate data sharing
Opportunities
How to harness the value of data?
Patient data anonymization
Data standards
Standardized Analytics
Regulate data sharing
What We Need to Keep Moving Forward?
Identifying
stakeholders
who can drive
the change
Data Access
Protection
Anonymization
Data Exchange
Data Security
Education
Public Trust
TECHNICAL
POLITICAL REGULATORY CULTURAL
When We Talk About Real-World Data We Talk About
Real-world hold great potential for answering
questions that may not be addressed otherwise.
…rich health data sources beyond the confines
of traditional studies.
…data source that can make savings in cost
and time in evidence generation.
...routinely collected data that can be used to
make regulatory decisions.
Thank you.
nevena.veljkovic@heliant.rs

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[DSC Europe 23] Nevena Veljkovic - What We Talk About When We Talk About Real - world Data.pptx

  • 1. What We Talk About When We Talk About Real-world Data? Nevena Veljkovic
  • 2. Principal research scientist, Vinca Institute of Nuclear Sciences, University of Belgrade, National institute of Republic of Serbia Chief Scientific Officer, Heliant doo Founder and CEO, Genial doo PhD Chemistry and chemical engineering, University of Belgrade Professional interests: computational biology and chemistry, analyses of clinical data and biomarkers About me
  • 3. About HELIANT HELIANT is a software company focused on IT solutions for healthcare and well-being. HELIANT is leader in the Western Balkan market. 280 institutions 6 million prescriptions per month 5 million examinations per month 100 000 users 120 employees
  • 4. STAKEHOLDERS • Individuals, patients and families • Healthcare providers • Governments & policy makers • Industry • Research & educators and many more… INDUSTRIES • Drugs • Medical Equipment • Insurance • Healthcare Facilities • IT and many more… Healthcare ecosystem
  • 5. Digitalization is changing healthcare Let’s turn knowledge into innovations for seamless digital patient journeys.
  • 6. Big Data & Healthcare Analytics Tan Tock Seng Hospital's operations command center
  • 7. REAL WORLD DATA (RWD) & REAL WORLD EVIDENCE (RWE)
  • 8. Real World Data (RWD) are the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Real-World Evidence (RWE) is the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD.
  • 9. USE of RWD Patient Identification Resources Management Scientific Research Clinical Trials Precision Public Health AI & ML Models
  • 10. Sources of RWD Wearable devices Mobile devices Claims and billing activities Electronic Health records (EHRs) Disease registries Social Media Patient reported Molecular profiling Enviromental
  • 11. An electronic medical record (EMR) is a patient’s medical history that is maintained electronically by a single provider. It is a digital version of a patient's paper chart. An electronic health record (EHR) is a patient’s medical history that is maintained electronically by multiple providers.
  • 12. TYPES of DATA • Contact and demographic information • Information about visits to healthcare professionals • Allergies • Insurance information • Family history • Immunization status • Information about any conditions or diseases • A list of medications • Records of hospitalization
  • 13. Disease registries • Global • Regional • National • Intra-Hospital Disease Registry a database that stores detailed information about people with a specific disease or condition
  • 15. Characteristics of RWD Sub-optimal Data Quality that requires intensive pre-processing Unstructured and structured Inconsistent Voluminous and dynamic Incomplete and often missing crucial end points Subject to bias and measurement errors Missingness rate is high Multiple events overlap
  • 16. Challenges Data Quality Efficient and practical ML and statistical procedures Explainability and interpretability Reproducibility and replicability Privacy, data sharing Diversity, Equity, Algorithmic fairness, and Transparency (DEAT)
  • 17. Challenges Adapted from Liu & Panagiotakos, 2022
  • 18. How to harness the value of data? Patient data anonymization Data standards Standardized Analytics Regulate data sharing
  • 19. Opportunities How to harness the value of data? Patient data anonymization Data standards Standardized Analytics Regulate data sharing
  • 20. What We Need to Keep Moving Forward? Identifying stakeholders who can drive the change Data Access Protection Anonymization Data Exchange Data Security Education Public Trust TECHNICAL POLITICAL REGULATORY CULTURAL
  • 21. When We Talk About Real-World Data We Talk About Real-world hold great potential for answering questions that may not be addressed otherwise. …rich health data sources beyond the confines of traditional studies. …data source that can make savings in cost and time in evidence generation. ...routinely collected data that can be used to make regulatory decisions.