Marianne Sharko1, Mohit M Sharma2, Natalie C Benda2, Melissa Chan3, Eric Wilsterman3, Lisa Grossman Liu4, Michelle Demetres5, Diana Delgado5, Jessica S Ancker6. 1. Dept. of Population Health Sciences, Division of Health Informatics, Weill Cornell Medical College, New York, NY, USA; Department of Pediatrics, Weill Cornell Medical College, New York, NY, USA. Electronic address: marsharko@gmail.com. 2. Dept. of Population Health Sciences, Division of Health Informatics, Weill Cornell Medical College, New York, NY, USA. 3. Department of Pediatrics, Weill Cornell Medical College, New York, NY, USA. 4. Department of Biomedical Informatics, Columbia University, New York, NY, USA. 5. Weill Cornell Medicine Samuel J Wood Library, New York, NY, USA. 6. Dept. of Population Health Sciences, Division of Health Informatics, Weill Cornell Medical College, New York, NY, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Abstract
OBJECTIVE: To develop evidence-based recommendations for improving comprehension of quantitative medication instructions. METHODS: This review included a literature search from inception to November 2021. Studies were included for the following: 1) original research; 2) compared multiple formats for presenting quantitative medication information on dose, frequency, and/or time; 3) included patients/lay-people; 4) assessed comprehension-related outcomes quantitatively. To classify the studies, we developed a concept map. We weighed 3 factors (risk of bias in individual studies, consistency of findings among studies, and homogeneity of the interventions tested) to generate 3 levels of recommendations. RESULTS: Twenty-one studies were included. Level 1 recommendations are: 1) use visualizations of medication doses for liquid medications, and 2) express instructions in time-periods rather than times per day. Level 2 recommendations include: validate icons, use panels or tables with explanatory text, use visualizations for non-English speaking populations and for those with low health literacy and limited English proficiency. CONCLUSIONS: Visualized liquid medication doses and time period-based administration instructions improve comprehension of numerical medication instructions. Use of visualizations for those with limited health literacy and English proficiency could result in improved outcomes. PRACTICE IMPLICATIONS: Practitioners should use visualizations for liquid medication instructions and time period-based instructions to improve outcomes.
OBJECTIVE: To develop evidence-based recommendations for improving comprehension of quantitative medication instructions. METHODS: This review included a literature search from inception to November 2021. Studies were included for the following: 1) original research; 2) compared multiple formats for presenting quantitative medication information on dose, frequency, and/or time; 3) included patients/lay-people; 4) assessed comprehension-related outcomes quantitatively. To classify the studies, we developed a concept map. We weighed 3 factors (risk of bias in individual studies, consistency of findings among studies, and homogeneity of the interventions tested) to generate 3 levels of recommendations. RESULTS: Twenty-one studies were included. Level 1 recommendations are: 1) use visualizations of medication doses for liquid medications, and 2) express instructions in time-periods rather than times per day. Level 2 recommendations include: validate icons, use panels or tables with explanatory text, use visualizations for non-English speaking populations and for those with low health literacy and limited English proficiency. CONCLUSIONS: Visualized liquid medication doses and time period-based administration instructions improve comprehension of numerical medication instructions. Use of visualizations for those with limited health literacy and English proficiency could result in improved outcomes. PRACTICE IMPLICATIONS: Practitioners should use visualizations for liquid medication instructions and time period-based instructions to improve outcomes.
Authors: Laura J Sahm; M S Wolf; L M Curtis; R Behan; M Brennan; H Gallwey; S Mc Carthy Journal: Eur J Clin Pharmacol Date: 2011-11-30 Impact factor: 2.953
Authors: Michael S Wolf; Terry C Davis; Laura M Curtis; Jennifer A Webb; Stacy Cooper Bailey; William H Shrank; Lee Lindquist; Bernice Ruo; Mary V Bocchini; Ruth M Parker; Alastair J J Wood Journal: Med Care Date: 2011-01 Impact factor: 2.983
Authors: Danielle M McCarthy; Terry C Davis; Jennifer P King; Rebecca J Mullen; Stacy C Bailey; Marina Serper; Kara L Jacobson; Ruth M Parker; Michael S Wolf Journal: J Health Commun Date: 2013
Authors: Katerina Andreadis; Ethan Chan; Minha Park; Natalie C Benda; Mohit M Sharma; Michelle Demetres; Diana Delgado; Elizabeth Sigworth; Qingxia Chen; Andrew Liu; Lisa Grossman Liu; Marianne Sharko; Brian J Zikmund-Fisher; Jessica S Ancker Journal: J Gen Intern Med Date: 2021-08-06 Impact factor: 5.128