P242: Building a Holistic Patient View Through High Quality Source Data Collection and Linkage
Poster Presenter
Molly Shields
Policy Analyst, Assistant
Duke-Margolis Institute For Health Policy (DMI) United States
Objectives
Assess the feasibility of creating holistic patient profiles through quality real-world data (RWD) collection, linkage, and interoperability to enhance clinical trial infrastructure, quality care improvements, and learning health systems to support better patient outcomes.
Method
We conducted a landscape analysis of RWD and real-world evidence (RWE) use cases from industry, academia, and government organizations leveraging relevant literature. These use cases (n = 40) then informed recommendations and considerations for advancing better data collection and interoperability.
Results
The landscape analysis illustrates it is currently difficult—but conceptually feasible—to create holistic patient profiles from RWD. Challenges include incomplete data collection and an undue burden on providers to assist with additional data collection beyond routine care responsibilities. Sponsors of clinical research rely on certain data source types more frequently than others (e.g., electronic health records versus social determinants of health data) and unevenly display data collection and quality assurance methods. While operational frameworks exist to guide data accrual, sponsors do not uniformly adopt the same frameworks despite prioritizing similar quality indicators. Federal guidance offers several controlled terminologies and data measurements for sponsors, but further stakeholder collaboration and feedback would encourage improved data standardization and shared quality assurance methods.
Promising opportunities to create holistic patient profiles include data linkage and interoperability strategies such as common data models, application programming interfaces, and the use of artificial intelligence to address challenges with unstructured data and data missingness. However, use cases reveal siloed data strategies impede data linkage efforts to validate inter-source data and trace a patient’s visits throughout their longitudinal health journey. Academic use cases discuss data linkage strategies more frequently than industry use cases, likely a result of operating within an insular university health system. Among industry use cases, start-up health technology companies face more infrastructure limitations than larger pharmaceutical companies with established data infrastructure systems. Findings on data collection and data strategies reveal areas for improvement and reinforce that real-world data sources can sustain holistic patient profiles that generate evidence to inform and align clinical care and research priorities.
Conclusion
Holistic patient profiles are conceptually feasible, but presently difficult, to create because of disparate data standards and a siloed healthcare and clinical research landscape. Incentivizing engagement from providers, payers, and health data companies can diversify data source collection, strengthen data accrual infrastructure, and mitigate challenges with data errors and missingness. Professional societies and health system leaders can help shape best practices for operational frameworks and collaborate with regulatory agencies to adapt existing data quality frameworks to include standardized terminologies and quality measures. Importantly, improved data collection and standardization processes will support data linkage across data sources and a patient’s healthcare journey. Current data linkage and interoperability efforts such as common data models, corresponding application programming interfaces, and artificial intelligence are promising solutions for overcoming the fragmented U.S. healthcare system. Expanded agency guidance on data linkage and interoperability, and engagement between agencies like FDA and CMS, will foster an integrated learning health system.
Expanded federal regulations and multi-stakeholder collaboration will help support holistic patient profiles using existing data strategies. Engagement from patients, providers, payers, industry sponsors, health technology companies, and regulatory agencies will ensure RWD and RWE informs holistic, longitudinal collection that is both sustainable and scalable. Holistic patient profiles that enable investigators and providers to trace long-term health outcomes can align clinical trial infrastructure and quality care improvements to enhance patient outcomes. An integrated health system inclusive of clinical trial research, care delivery, and patient engagement will enable the U.S. healthcare system to develop efficient, novel treatments and respond to future healthcare emergencies.
