Real-world data (RWD) is increasingly used in health care research to provide insights into patient health and the delivery of care outside traditional research settings. Examples of RWD include medical and pharmaceutical claims, electronic health records (EHRs), disease registry data, and information from sources such as mobile devices, social media, and wearable technology.
RTI International has established itself as a leader in leveraging RWD for various health research initiatives. These efforts range from using EHRs to support public health surveillance to employing wearable devices for early detection of illnesses like influenza, as well as analyzing social media data to study the impact of tobacco marketing on youth.
Researchers value RWD because it does not require additional data collection, offers large sample sizes, and often reflects more diverse patient populations than clinical trials. Claims data are particularly useful for operational purposes such as processing payments between providers and insurers or government agencies. This type of data can help answer questions about the costs associated with treating specific diseases or patterns of medication use among certain groups.
However, individual RWD sources may lack key information needed for comprehensive analysis since they are not typically designed with research in mind. Linking multiple sources of RWD—or combining them with survey data—can address these gaps. For example, while surveys might capture patients’ experiences with coordinated cancer care, they may not include cost information; insurance claims have detailed cost data but lack insights into care coordination.
RTI International has been at the forefront of integrating different types of RWD to improve research outcomes. The organization has used linked resources such as the National Cancer Institute’s Surveillance, Epidemiology and End Results (SEER) cancer registry combined with Medicare Consumer Assessment of Healthcare Providers and Systems (CAHPS) patient surveys and Medicare claims. According to RTI International: “After analyzing this linked resource, we found that coordinated care was associated with less expensive care.”
The process of linking disparate health care datasets is considered crucial infrastructure for evidence-based research today. Such linkages enable studies that would be difficult or impossible through traditional methods by providing a more complete view across diverse populations.
Looking ahead, RTI International plans to explore how artificial intelligence can further improve record linkage processes by enhancing quality control and speeding up matching procedures.
