Starting a Real-World Evidence Project?

A Guide to Starting a Real-World Evidence Project: Self-Solutioning Steps

Before embarking on a real-world evidence (RWE) project, it’s crucial to ensure proper planning and preparation. Here is a self-solutioning checklist that outlines key steps:


Define Objectives and Research Questions:

  • Define the objectives of the RWE project.
  • List specific insights or evidence you are seeking to generate.
  • Identify key research objective(s). Here are a few examples of RWE studies and use cases:
    • Medical Affairs/HEOR use cases - natural history of disease, patient journey, treatment patterns, outcomes study, comparative effectiveness, HCRU, prevalence study, etc.
    • Commercial use cases - market assessment, patient segmentation, provider mapping, market tracking, referral patterns, etc.
  • Formulate research questions that align with the key objectives and will guide the study design, data requirements and analytical plan.
  • Define timelines. Are there target conferences for publications? Is there an internal urgency?

Identify Stakeholders and Collaborators:

  • Identify all cross-functional stakeholders involved in the project, including researchers, clinicians, data scientists, regulatory experts, and decision-makers.

  • Establish collaboration with relevant partners to access necessary data sources and expertise.

  • Determine if your organization could benefit from an RWE Center of Excellence.

Understand Regulatory Requirements:

  • Familiarize yourself with the regulatory landscape governing RWE studies in your jurisdiction, such as FDA guidelines in the United States or EMA regulations in Europe.

Data Source Identification and Access:

  • Identify fit-for-purpose data source(s) that will be utilized for the RWE study.

Datasets and data partners should be evaluated based on the following attributes:

  • Quality trusted data sources
  • Sufficient volume of data for the disease/treatment of interest
  • Availability of key data elements (e.g., clinical outcomes)
  • In-house data services expertise
  • Data or services timelines to align with your deadlines
  • Accessibility and availability of these data sources, including any data sharing agreements or access restrictions

Data Quality Assessment:

  • Assess the quality, completeness and reliability of the selected data sources. Evaluate factors such as data accuracy, consistency, and timeliness.

By following these steps, you can lay a solid foundation for a successful RWE project, enabling you to generate meaningful insights that will help inform healthcare decision-making and improve patient outcomes.


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