Health IT Usability Focus Section: Adapting EHR-Based Medication Instructions to Comply with Plain Language Guidance-A Randomized Experiment

健康信息技术可用性专题:调整基于电子病历的用药说明以符合简明语言指南——一项随机实验

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Abstract

Objective Patient instructions are generally written by clinicians. However, clinician-centered language is challenging for patients to understand; in the case of pediatric medication instructions, consequences can be serious. Using examples of clinician-written medication instructions from an electronic health record, we conducted an experiment to determine whether parental misinterpretations would be reduced by instructions that followed best practices for plain language. Methods We selected examples of dosing instructions from after-visit summaries in a commercial electronic health record. A demographically diverse sample of parents and adult caregivers was recruited from an online panel to participate in an English-language experiment, in which they received a comprehension questionnaire with either original after-visit summary instructions or instructions revised to comply with federal and other sources of plain-language guidance. Results Nine-hundred and fifty-one respondents completed the experiment; 50% were women, the mean age was 36 years, and 38% had less than a 4-year college education. The revisions were associated with an 8 percentage point increase in correct answers overall (from 55% to 63%, p < 0.001), although revisions were not equally effective for all instructions. Health literacy and health numeracy were strong and independent predictors of comprehension. Overall, mistakes on comprehension questions were common, with respondents missing an average of 41% (6.1 of 15) of questions. Conclusion In this experimental study, a relatively simple intervention of revising text was associated with a modest reduction in frequency of misinterpretations of medication instructions. As a supplement to more intensive high-touch interventions, revising electronic health record output to replace complex language with patient-centered language in an automated fashion is a potentially scalable solution that could reduce medication administration errors by parents.

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