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

2017 ◽  
Vol 08 (04) ◽  
pp. 1127-1143
Author(s):  
Jessica Ancker ◽  
Alexander Send ◽  
Baria Hafeez ◽  
Snezana Osorio ◽  
Erika Abramson

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.

2021 ◽  
Vol 3 (2) ◽  
pp. 167-170
Author(s):  
Soraya Arzhan ◽  
Christos Argyropoulos ◽  
Maria-Eleni Roumelioti

2021 ◽  
Vol 3 (2) ◽  
pp. 231-240.e1 ◽  
Author(s):  
June Tome ◽  
Shahbaz Ahmed ◽  
Angela Fagerlin ◽  
Corey Powell ◽  
Marcio Mourao ◽  
...  

2014 ◽  
Vol 96 (3) ◽  
pp. 315-319 ◽  
Author(s):  
Richard L. Street ◽  
Lin Liu ◽  
Neil J. Farber ◽  
Yunan Chen ◽  
Alan Calvitti ◽  
...  

2017 ◽  
Vol 22 (1) ◽  
pp. 1396171 ◽  
Author(s):  
Wei Wei Lee ◽  
Maria L. Alkureishi ◽  
Kristen E. Wroblewski ◽  
Jeanne M. Farnan ◽  
Vineet M. Arora

2020 ◽  
pp. 193229682096661
Author(s):  
Kristen Kulasa ◽  
Brittany Serences ◽  
Michael Nies ◽  
Robert El-Kareh ◽  
Kirk Kurashige ◽  
...  

Background: Computerized insulin infusion protocols have demonstrated higher staff satisfaction, better compliance with protocols, and increased time with glucose in range compared to paper protocols. At University of California San Diego Health (UCSDH), we implemented an insulin infusion computer calculator (IICC) and transitioned it from a web-based platform directly into the electronic medication administration record (eMAR) of our primary electronic health record (EHR). Methods: This is a retrospective analysis of 6306 adult patients at UCSDH receiving intravenous (IV) insulin infusion from March 7, 2013 to May 30, 2019. We created three periods of the study—(1) the pre-eMAR integration period; (2) the eMAR integration period; and (3) the post-eMAR integration period—and looked at the percentage of readings within goal range (90-150 mg/dL for intensive care unit [ICU], 90-180 mg/dL for non-ICU) in patients with and without hyperglycemic emergencies. As our safety endpoints, we elected to look at incidence of blood glucose (BG) readings <70 mg/dL, <54 mg/dL, and <40 mg/dL. Results: Pre-eMAR 69.8% of readings were in the 90-150 mg/dL range compared to 70.2% post-eMAR ( P = .03) and 82.7% of readings were in the 90-180 mg/dL range pre-eMAR versus 82.9% ( P = .09) post-eMAR in patients without hyperglycemic emergencies. Rates of hypoglycemia with BG <70 mg/dL were 0.43%, <54 mg/dL were 0.07%, and <40 mg/dL were 0.01% of readings pre- and post-eMAR. Conclusions: At UCSDH, our IICC has shown to be safe and effective in a wide variety of clinical situations and we were able to successfully transition it from a web-based platform directly into the eMAR of our primary EHR.


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