Real World Data Mapping – Identifying and Navigating Data Sources Globally

The landscape of RWD can be difficult to navigate. Real world data mapping provides a tool to systematically identify and evaluate RWD sources.

Real world data (RWD) has the potential to inform drug development, drug regulation, health technology assessments, and to refine clinical guidelines by characterising a product’s clinical outcomes in more diverse, real world patient populations. RWD sources are wide ranging, from national and regional registries, electronic medical records, claims databases, health surveys, to clinical databases. The growth and heterogeneity of RWD sources has created a data landscape that is increasingly difficult to navigate; identifying data sources to help answer strategic or study objectives is not always an obvious choice.

Real world data mapping is a flexible methodology that can be customized to meet various needs, whether to locate data sources to answer a specific study question or to get a larger overview of RWD sources for an indication of interest.

Join us for an overview real world data mapping and learn how it can be leveraged to uncover real world data.

Speakers

René Schade MD, MSc, Senior Principal, Real World Evidence Strategy and Analytics, ICON plc.

René Schade has 20+ years of experience in clinical medicine and/or health sciences, with 14+ years of postgraduate experience in (pharmaco)epidemiology and medical informatics, mainly with the use of large databases of longitudinal electronic health records, insurance claims, and patient registries. He has a wealth of experience in designing, executing, and coordinating epidemiology studies in highly collaborative, mostly multi-country, real-world data and advanced analytics projects. His projects have encompassed methodologies to assess drug safety, comparative effectiveness, indirect treatment comparison (external controls), health resource utilization, treatment patterns, burden of illness, disease comorbidity, and methods for terminology mapping and common data models. René is a senior leadership team member in ICON’s Real World Evidence and Analytics (RWESA) group. He provides strategic direction and coaches an international team of epidemiology, health economics and data analytics experts at ICON.

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Dr. Bernd Schweikert, MSc, Senior Research Consultant, Real World Evidence Strategy and Analytics, ICON plc.

Bernd Schweikert is a health economist with over 15 years of experience in health economics, epidemiological research and evidence generation, and data analytics, working with large longitudinal data sets claims data sets in different countries. Bernd has extensive expertise in study design and conceptualization; advanced epidemiologic methods; data collation and analysis; and dissemination into the scientific community. At ICON, Bernd is responsible for designing, leading, and analysing observational studies, including retrospective database studies and chart reviews in a variety of indications.

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Ruchika Sharma, BDS, MPH, Analyst II, Real World Evidence Strategy and Analytics, ICON plc.

Ruchika Sharma has over six years of experience encompassing epidemiology, public health and health care. At ICON, Sharma has worked in multiple database mapping and feasibility studies across Europe, North America and Asia-Pacific. She has extensive experience on literature review, disease forecasting techniques, risk-factor modeling, patient-population sizing, epidemiological methods and study design with expertise in analyzing large population-based databases like HCUP, NHANES, SEER and NSSO. Sharma has worked on a variety of therapeutic areas like infectious diseases, neurology, oncology, cardiovascular diseases, metabolic disorders, immunology and respiratory diseases.

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