Generating consistent longitudinal real-world data to support research: lessons from physical therapists

esearchers using real-world data (RWD) hope to generate answers to clinical effectiveness research (CER) and patient-centered outcomes research (PCOR) questions. However, reliability and validity of these results are dependent on data completeness and consistency. Because RWD are not generated with research as the primary goal, they suffer from incomplete and inconsistent documentation of routine clinical interventions. The two most common sources of RWD are clinician-documented and health system use data stored in electronic health records (EHRs) and administrative data, respectively. Both sources of RWD are readily available within health systems or aggregated in regional databases, such as PCORNet or administrative claims data. EHR data quality, in particular, suffers from inconsistent data structure and documentation as well as fragmentation across time and settings. For example, prescription refills or physical therapy (PT) interventions are not systematically documented in the primary care physician's EHR. In rheumatology practices, performance on rheumatoid arthritis quality measures using the American College of Rheumatology's Rheumatology Informatics System for Effectiveness registry varies according to the specific EHR employed (1). In an era of chronic disease, the richness of existing data and the value to research driven by these data will be enhanced when systematic and comprehensive clinical documentation of interventions is included in the EHR across settings.