Individual factors that affect laypeople's understanding of definitions of medical jargon

IF 3.4 3区医学 Q1 HEALTH POLICY & SERVICES

Health Policy and Technology Pub Date : 2024-12-01 DOI:10.1016/j.hlpt.2024.100932

David A. Levy , Harmon S. Jordan , John P. Lalor , Jenni Kim Smirnova , Wen Hu , Weisong Liu , Hong Yu

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引用次数: 0

Abstract

Objective

Patients have difficulty understanding medical jargon in electronic health record (EHR) notes. Lay definitions can improve patient comprehension, which is the goal of the NoteAid project. We assess whether the NoteAid definitions are understandable to laypeople and whether understandability differs with respect to layperson characteristics.

Methods

Definitions for jargon terms were written for laypersons with a 4th-to-7th-grade reading level. 300 definitions were randomly sampled from a corpus of approximately 30,000 definitions. 280 laypeople (crowdsource workers) were recruited; each layperson rated the understandability of 20 definitions. Understandability was rated on a 5-point scale. Using a generalized estimating equation model (GEE) we analyzed the relationship between understandability and age, sex, race/ethnicity, education level, native language, health literacy, and definition writer.

Results

Overall, 81.1 % (95 % CI: 76.5–85.7 %) of the laypeople reported that the definitions were understandable. Males were less likely to report understanding the definitions than females (OR: 0.73, 95 % CI: 0.63–0.84). Asians, Hispanics, and those who marked their race/ethnicity as “other” were more likely to report understanding the definitions than whites (Asians: OR: 1.43, 95 % CI: 1.17–1.73; Hispanics: OR: 1.86, 95 % CI: 1.33–2.59; Other: OR: 2.48, 95 % CI: 1.65–3.74). Laypeople whose native language was not English were less likely to report understanding the definitions (OR: 0.51, 95 % CI: 0.36–0.74). Laypeople with lower health literacy were less likely to report understanding definitions (health literacy score 3: OR: 0.51, 95 % CI: 0.43–0.62; health literacy score 4: OR: 0.40, 95 % CI: 0.29–0.55).

Conclusion

Understandability of definitions among laypeople was high. There were statistically significant race/ethnic differences in self-reported understandability, even after controlling for multiple demographics.

Public interest summary

We conducted a study to ensure that definitions written for the NoteAid EHR jargon identification tool are understandable. We recruited a diverse group of crowdsource workers and found that overall, the definitions were understandable, but understanding levels varied based on several demographic characteristics.

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来源期刊

Health Policy and Technology Medicine-Health Policy

CiteScore

9.20

自引率

3.30%

发文量

审稿时长

88 days

期刊介绍： Health Policy and Technology (HPT), is the official journal of the Fellowship of Postgraduate Medicine (FPM), a cross-disciplinary journal, which focuses on past, present and future health policy and the role of technology in clinical and non-clinical national and international health environments. HPT provides a further excellent way for the FPM to continue to make important national and international contributions to development of policy and practice within medicine and related disciplines. The aim of HPT is to publish relevant, timely and accessible articles and commentaries to support policy-makers, health professionals, health technology providers, patient groups and academia interested in health policy and technology. Topics covered by HPT will include: - Health technology, including drug discovery, diagnostics, medicines, devices, therapeutic delivery and eHealth systems - Cross-national comparisons on health policy using evidence-based approaches - National studies on health policy to determine the outcomes of technology-driven initiatives - Cross-border eHealth including health tourism - The digital divide in mobility, access and affordability of healthcare - Health technology assessment (HTA) methods and tools for evaluating the effectiveness of clinical and non-clinical health technologies - Health and eHealth indicators and benchmarks (measure/metrics) for understanding the adoption and diffusion of health technologies - Health and eHealth models and frameworks to support policy-makers and other stakeholders in decision-making - Stakeholder engagement with health technologies (clinical and patient/citizen buy-in) - Regulation and health economics