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

Abstract

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.The EHR is the primary data source for real-world CER and PCOR applications but can be a source of bias when clinical documentation is inconsistent, incomplete, and potentially biased (2). Missing EHR data result from clinician inconsistencies in what and when to document or when patients receive care across multiple health systems or from community-based providers. Human decisions determine content and definition of the data elements (or not) in the EHR, hence contributing to incomplete intervention and outcome data (3). Thus, research using today's EHR, and its clinical data, risks validity because of two major factors: 1) inconsistent clinical intervention and outcome documentation in the course of care and 2) lack of integration of clinical documentation across time and place.Following total knee (TKR) and hip replacement surgeries, PT providers are commonly not affiliated with the health system where the surgery was performed. Thus, their documentation Author disclosures are available at https://onlinelibrary.wiley.com/action/ downloadSupplement?doi=10.1002%2Facr2.11465&file=acr211465-sup-0001-Disclosureform.pdf.

Evaluating the implementation of personalised outcomes forecasts to optimise supervised exercise therapy in patients with intermittent claudication in the Netherlands: a multimethods study

“…Reasons for missing data could be attributed to patient factors (eg, early termination of therapy) or to therapist inconsistencies in what and when to document. 55 This lost to follow-up may have introduced bias in the results, particularly since patients lost to follow-up tend to have lower baseline scores (data not shown). Nevertheless, these differences in baseline scores did not exceed the MID thresholds.…”

“…Many patients were excluded from analysis due to incomplete or missing follow-up measurements within the databases. Reasons for missing data could be attributed to patient factors (eg, early termination of therapy) or to therapist inconsistencies in what and when to document 55. This lost to follow-up may have introduced bias in the results, particularly since patients lost to follow-up tend to have lower baseline scores (data not shown).…”