Drug Discovery and Development

  • Home Drug Discovery and Development
  • Drug Discovery
  • Women in Pharma and Biotech
  • Oncology
  • Neurological Disease
  • Infectious Disease
  • Resources
    • Video features
    • Podcast
    • Voices
    • Views
    • Webinars
  • Pharma 50
    • 2025 Pharma 50
    • 2024 Pharma 50
    • 2023 Pharma 50
    • 2022 Pharma 50
    • 2021 Pharma 50
  • Advertise
  • SUBSCRIBE

Using Real-World Data for Outcomes Research and Comparative Effectiveness Studies

By Drug Discovery Trends Editor | November 4, 2014

Biopharma is increasingly harnessing the power of data collected outside of a controlled clinical environment to generate valuable insights to support products throughout their lifecycle. Recent advances, such as greater availability of information technology and stronger observational research methods, have improved our ability to leverage real-world data sources, making them attractive tools for research use. As we continue to investigate and use these sources to strengthen evidence of real-world safety and effectiveness and influence value-based purchasing and pricing, we recognize the importance of selecting the right data source and study design for a given research question. Given the number of potential clinical data sources and their increasing availability for research, selection of an appropriate source is challenging. Here we examine how to best leverage these data in today’s complex environment.

Real-world data can be divided into two key types: primary data, which are collected specifically for research purposes; and secondary data, which are collected for purposes other than the research question of focus. Primary data are generally obtained from study-specific case report forms and/or through clinical outcomes assessments such as Patient-Reported Outcomes (PROs). These data are collected in nonexperimental prospective observational studies, patient registries and health surveys. Additionally, real-world patient data can be collected through interventional Phase 3B and 4 trials, which include supplemental data collection within traditional randomized controlled trials (RCT piggybacks) and pragmatic studies. Secondary data are often obtained from clinical chart reviews, electronic medical and health records, existing registries or administrative sources, such as insurance claims.

Retrospective database studies look backward in time using secondary data, thus having the potential to generate large, real-world sample sizes quickly and efficiently. However, they are limited by the fact that the data already exist and there is no control over what elements are collected. Prospective study designs, which generally require primary data collection, allow a high degree of control over data elements collected. These generally take longer and cost more than retrospective designs. Hybrid studies using mixed data models combine elements of both of these approaches through prospective data collection and the use of retrospective administrative data, creating efficiencies in study operation. A hybrid study combines automated, passive data capture with active, de novo data collection, to create a data set with broad application. In this setting, EMR or claims data can be used retrospectively for baseline data collection, and prospective EMR feeds can proceed in parallel with direct-to-clinician and direct-to-patient survey administration.

A firm understanding of stakeholder and evidentiary needs is a critical first step in the process of selecting an appropriate data source and study design. A number of factors influence which data source, study design, and timing of data collection will be ideal for a given research question. First, consider whether the required data elements are recorded in routine clinical practice or through healthcare administration, and if so, where specifically would these data be found? Are they available in electronic medical records or claims, and if not, is chart review a possibility? Answers of “yes” to these questions lead to use of secondary data. If data elements are not routinely collected, prospective data capture may be the solution. The middle ground hybrid approach allows for the combining of these approaches to capture what is possible from electronic databases and augment with primary data collection.

Every study is unique, and there are a variety of flexible frameworks for tapping into the power of real-world data sources to effectively and efficiently answer research questions. These data are recognized as an increasingly valuable asset for research at all points of the drug development process. Practical considerations for customized and creative uses of data can help researchers generate the most robust study conclusions.

 


Filed Under: Drug Discovery

 

Related Articles Read More >

Swissmedic approves first malaria treatment for infants
Korean team reports all-in-one cancer nanomedicine in pre-clinical studies
Nektar’s Phase 2b atopic dermatitis win triggers 1,746% analyst target surge, but legal tussle with ex-partner Lilly could complicate path forward
Dupixent approved to treat bullous pemphigoid
“ddd
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest news and trends happening now in the drug discovery and development industry.

MEDTECH 100 INDEX

Medtech 100 logo
Market Summary > Current Price
The MedTech 100 is a financial index calculated using the BIG100 companies covered in Medical Design and Outsourcing.
Drug Discovery and Development
  • MassDevice
  • DeviceTalks
  • Medtech100 Index
  • Medical Design Sourcing
  • Medical Design & Outsourcing
  • Medical Tubing + Extrusion
  • Subscribe to our E-Newsletter
  • Contact Us
  • About Us
  • R&D World
  • Drug Delivery Business News
  • Pharmaceutical Processing World

Copyright © 2025 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search Drug Discovery & Development

  • Home Drug Discovery and Development
  • Drug Discovery
  • Women in Pharma and Biotech
  • Oncology
  • Neurological Disease
  • Infectious Disease
  • Resources
    • Video features
    • Podcast
    • Voices
    • Views
    • Webinars
  • Pharma 50
    • 2025 Pharma 50
    • 2024 Pharma 50
    • 2023 Pharma 50
    • 2022 Pharma 50
    • 2021 Pharma 50
  • Advertise
  • SUBSCRIBE