(186) The Best of All Worlds: Development of a Consolidated Data Model to Expand the Ability to Generate Real-World Evidence

Publication Number: 860

Background: The need for real-world evidence (RWE) is ever increasing; however, there are limitations to means of RWE generation. Large healthcare databases are quick and inexpensive but lack comprehensive data on clinical characteristics and patient outcomes. Bespoke data collection address these limitations, but at a cost that constrains scale and generalizability. A need thus exists for a single source solution to solve this issue.

Objectives: To describe development of a consolidated data model to support RWE generation.

Methods: In the United States, integrated delivery networks (IDNs) own healthcare facilities and employ healthcare providers. Electronic medical records (EMR) capture information from encounters at their facilities, with curated data including diagnoses, prescription orders, and lab results; chart review can be used to extract information from unstructured/uncurated data fields (e.g., signs, symptoms, diagnostic findings). IDNs may also capture claims for care within/outside their facilities, including prescription dispenses, procedures, and charged/paid amounts. Some allow direct-to-patient contact, which offers the ability to collect data on preferences, indirect cost, and health-related quality of life.

Results: Our consolidated data model can support various RWE use cases, including but not limited to: (1) external control arms; (2) case-selection algorithm development; (3) pragmatic trials; (4) prospective observational studies (including but not limited to registries); (5) clinical decision support tools and medical device utility development/implementation; and (6) RWE effectiveness/cost-effectiveness. The distinguishing factor of studies that leverage such a model is the need to combine "depth" of clinical data with "breadth" of information typically provided with structured/curated electronic data, and/or the desire to facilitate data collection/reduce site burden over relatively long study periods. Depending on location, the model also may lend insight into historically underserved/underrepresented populations.

Conclusions: Our consolidated data model enables and facilitates RWE generation by combining breadth of large databases with depth and customization of bespoke data collection, while reducing administrative and site burden. Each use case should be assessed for data quality, budgetary and timeline efficiencies, and ability to generate RWE to address stakeholder needs.