Measuring the use of spoken plain language by clinicians in healthcare encounters: A scoping review.

Abstract

Poor communication in clinical encounters impacts both clinical and patient outcomes. We aimed to summarize the available data on the measurement and use of clinician-spoken plain language, as well as the associations between elements of plain language use and patient outcomes. Using Arksey and O'Malley's framework, we conducted a scoping review of the published literature through November 2024 including any analysis of clinician use of plain language in English-based clinical encounters. We assessed study quality using the Joanna Briggs Institute cross-sectional assessment tool. We summarized our findings qualitatively. From 4398 unique citations, we found 36 papers (utilizing 34 distinct datasets) meeting our criteria. Studies were published from 2007 to 2023 and included 1225 clinicians total (range: 2-214) across many clinical settings. Study quality was mixed, although most (28/36, 77.8 %) measured plain language outcomes using reliable methods. Use of medical terminology was measured in 21/36 (58.3 %) studies, where all used manual methods to count terms, and some supplemented (5/21, 23.8 %) with automation. Median medical terms per encounter was 19.5 (range: 2.4-72.3), but interpretation was limited since encounter length varied substantially. Language complexity was measured in 15/36 (41.7 %), primarily using methods designed for written text. The average transcript grade level was 6.3 (range: 2.7-9.8; sixth grade). Only 4/36 (11.1 %) reported findings back to clinicians. This review offers insight into an emerging area of research in measuring clinician-spoken plain language. Significant heterogeneity exists in the elements that are measured, methods used, and findings. Future research should account for variation in encounter length. The use of automated analysis methods is growing, but limited, in this field. Measuring clinician-spoken plain language is an emerging area with potential applications in medical and continuing education. Real-world implementation may be supported through standardization of measurement methods and delivering results back to clinicians.