Real World Data (RWD) is patient-level data routinely collected for medical and/or health administration purposes versus data collected in conventional randomized controlled clinical trials.

Over the past decade, healthcare stakeholders have come to appreciate the strong value proposition of RWD as a powerful tool to generate uniquely valuable evidence for healthcare product development and lifecycle strategy.

But not all data is created (or transformed) equally. There are key steps to getting the most from Real World Data, and it starts with understanding the challenges of making RWD work.

RWD Presents Incredible Promise to be Tapped

RWD is almost infinitely rich in the kind of detail that can dramatically deepen the understanding of patient journeys, highlight important new treatment pathways, identify unserved patient populations, and demonstrate drug efficacy under complex circumstances.

Some regulatory bodies are beginning to adapt their processes supporting market approval to encompass RWD generated insights, as a complement to the gold standard of prospective randomized controlled clinical trials (RCTs). For example, it is now widely recognized that treatments for certain indications such as many rare diseases can only be evaluated based on RWD.

Growing Interest, Impact, and Investment

The growing acknowledgement of RWD’s importance and unique value will continue as advances in RWD analysis and processing improve; and as the potential for truly remarkable, otherwise unobtainable insights, becomes more established. For those who are heavily involved in RWD, the early results are already powerfully salient.

For these reasons, pharma companies and regulatory bodies are currently investing to build internal knowledge and expertise and are adopting RWE-based strategies to support effective and safe product launches, new development needs, and drug use assessment and impact in real world settings.

Better Data Transformation Means Better Answers

IQVIA is constantly improving our data access and management processes. Benefiting from our strong expertise in managing proprietary data sets, IQVIA has heavily invested in Real World Data factories to collect or enable access, clean, curate, bridge, harmonize, link, and de-identify data for compliant usage to generate highly specific insights to meet pressing clinical and commercial challenges.

PUT THIS IN A BOX?

Main types of patient databases available:

• Longitudinal prescriptions (LRx): from pharmacy channel
• Electronical Medical Records (EMR): from medical practice management software
• Claims: from Payer, Medical, Hospital, Drug Plans
• Hospital Patient Encounters: in-patient treatment, outpatient (in some countries)
• Registries and patients’ cohorts: typically generated by academic research
• Cross sectional data: patients’ charts (when longitudinal data does not exist)
• Genomics data: global access to a network of genomic-clinical data

Choosing the Right Data Sources for Your Need

It is crucial to choose the right data source to ensure researchers have fit-for-purpose data to answer the research question at hand. While numerous public/private initiatives are underway to render real world data easier to Find, Access, Interoperate, and Reuse (the FAIR standard initially published in March 2016 by a group of scientists (Mark D. Wilkinson) in Scientific Data), different RWD sources come with different strengths and limitations, therefore it may be the case that one RWD source does not fully answer to a specific research question.

Appreciating the Complex Transformation of RWD

Generating and preparing useful Real World Data aimed at producing Real World Evidence is not a trivial task. Before being accessible, real world data — data that is collected for clinical rather than analytic purposes – needs to undergo several transformation processes so that it may become analytically ready. This requires a secure infrastructure and state of the art data production factories to integrate, clean, curate, bridge, de-identify and perform ongoing quality controls on data collected from diverse sources. (IQVIA has invested heavily in all those infrastructure and processes, and in the expertise to put it all together.)

Combining Same-Patient Data to Provide Richer Insights

Linking data at the patient level, from different sources, can produce a clearer picture of the patient journey, and overcome potential data gaps, while providing richer, more meaningful insights. In fact, effective RWD utilization requires the combining of disparate data sources into high-quality (often de-identified) datasets as an early step. The more data can be combined, the more effective it will be at providing insights while increasing re-identification risks.

Putting RWD to Effective Use

Once curated, harmonized and analytically ready, answer-rich RWD can — and should — be leveraged for multiple usage across the drug development lifecycle. This should be done as early as possible to plan for real world evidence strategy: from adopting the most appropriate clinical trial designs, comparators, and evaluation criteria, to performing most thorough post marketing evaluation.

About IQVIA Real World Data

Real-world data and analytics are increasingly available today across many stakeholders. However, generating meaningful evidence remains complex and elusive; as with most complex fields of product development, quality and expertise are key differentiating factors. The scope and quality of data, and the tools and expertise to generate meaningful evidence remain key differentiators. IQVIA’s position is unique in terms of international scope, data diversity and privacy, and our expertise in health data orchestration and analysis.

Have More Questions about Real World Data? See Our Guide.

IQVIA has created an in-depth eBook Guide to RWD usage including several tables and diagrams showing features of the different types of datasets, the regulatory history, examples of RWD usage through the product cycle, and much more. Download our guide to see:

• How to determine which RWD sources are most likely to be of most value to you
• How to leverage RWD to answer your most important business questions
• The key steps, standards, and decisions that go into gathering and refining RWD
• How you can use RWD to generate Real World Evidence
• Use cases revealing how RWD sources can be used to support research and power insight generation through innovative analytic platforms.