Efficiency and effectiveness of geriatric drug infographics: A randomized, controlled trial

Adverse drug events (ADEs) are a leading cause of mortality, disability, and healthcare costs in older adults due to multimorbidity, age-related changes to pharmacology and polypharmacy.1, 2 Infographics have proliferated in health literature as an efficient, effective, and user-friendly means to convey complex information through the judicious application of text and visuals.3-5 Through a randomized controlled trial (RCT), we sought to develop geriatric drug infographics (GDIs) and evaluate their potential to improve clinician pharmacotherapy learning to mitigate ADEs in older, medically complex, and frail adults. We created prototype GDIs for drugs (risperidone, digoxin, warfarin, dimenhydrinate, cannabis) associated with serious ADEs among older adults.1, 2, 6 Our interdisciplinary team conducted literature reviews of each drug's pharmacology and prioritized relevant pharmacotherapeutic knowledge for inclusion based on a pilot survey.7 Graphic designers and clinicians created prototypes through a collaborative and iterative process. The design team applied principles of eye-tracking, visual hierarchy, and iconography to facilitate ease and speed of comprehension, then modified the prototypes based on clinician feedback (Figure 1). We conducted a RCT of nurse practitioners, pharmacists, and physicians in Canada recruited through email between February 7 and August 8, 2019. Informed consent preceded the survey on Survey Monkey® (www.surveymonkey.com). We randomized participants using Survey Monkey®'s A/B Test function to an intervention group (infographics) or to a control group (usual pharmacotherapeutic resources). We obtained ethics approval from Hamilton Integrated Research Ethics Board (4790) and registered with the ISRCTN Clinical Trials Registry (13433969). The primary outcome was the time required to complete a knowledge test, and secondary outcomes included the accuracy of knowledge and knowledge retention tests (Appendix S1). The knowledge retention test followed a demographic survey and the Health Professionals' Inventory of Learning Styles.8 We assessed reading experience and user-friendliness using 10-point Likert scales and open-ended questions.4 With an alpha of 0.05 and 80% power, a total sample of 34 individuals was required to detect a 10-minute difference to complete the knowledge test, deemed clinically important per pilot data.7 We used the t test to detect a difference in the primary outcome, and t test or Mann–Whitney U test for secondary outcomes. We conducted descriptive analyses of demographic statistics and reading experience and user-friendliness. We analyzed data using R software, version 4.0.2 (R Project for Statistical Computing). We contacted 143 healthcare providers and received 50 (35.0%) responses (Figure S1). We randomized 22 participants in the infographic group, and 21 participants in the control group (Table S1). The control group reported using text-only primary and tertiary resources (e.g., Micromedex®, Lexicomp®). There was no statistically significant difference in the time required (45.1 minute; 95% confidence interval [CI] 5.6–84.7) with infographics compared with usual resources (20.0 minute; 95% CI 13.4–26.6) (p-value = 0.21). Participants using infographics answered more clinical questions correctly (60.0%; 95% CI 51.7–70.0%) compared to those in the usual resources group (35.0%; 95% CI 28.3–43.3) (Table S2, p-value <0.001), and had greater knowledge retention with infographics (78.0%; 95% CI 68.0–88.0%) versus usual resources (40.0%; 95% CI 30.0–50.0) (p-value <0.001). Overall, participants reported positive reading experiences with the infographics, and the majority found the information easy to follow and quick to retrieve (Table S3, Appendix S2). They appreciated the comprehensive yet concise, one-page format, pictorial elements, quantified risks and benefits, and prescribing information. Content-related and readability feedback included adding examples of major drug interactions, deprescribing recommendations, and simplifying and enlarging text. This is the first study describing the development and evaluation of infographics to facilitate clinician learning about pharmacotherapy for older adults. Combining text and graphic depictions of information stems from dual-coding and cognitive load theories and improve knowledge retention.9, 10 GDIs enhanced retrieval and retention of clinically relevant prescribing information compared to usual resources; however, the time required varied considerably, and may reflect the unfamiliarity with the novel infographics' iconography, or the possibility of insufficient study power. With repeated use or explanatory aides (e.g., legend), the time required may decrease. Limitations include using clinical scenarios with multiple choice and very short answer questions rather than observing actual clinical practice due to feasibility. We were also unable to detect or prevent contamination between groups. Although we developed the GDIs and set the knowledge tests, they reflected real-world clinical questions, and were validated by external clinicians from multiple disciplines. Infographics potentially enhance retrieval and retention of geriatric drug information. We would like to thank Dr. Tejal Patel for content expertise; Lindsay Cox, Tonya Weir, Caylee Raber, and Nadia Beyzaei for administrative support; and Curtis Lau, Fiona Lee, Karen Wang, and Vithusha Ganesh for contributions to the infographics. This project was supported by a Spark grant from the Centre for Aging and Brain Health Innovation. The funder had no role in the design, methods, subject recruitment, data collection, analysis, and preparation of the paper. The authors have no conflicts. All authors meet ICJME criteria for authorship. Jennifer Tung, R. Jack Bodkin, Cameron Neat, Sophiya Benjamin, Howard An, and Joanne M.-W. Ho conceived and designed the study. Thomas Laughton, R. Jack Bodkin, and Joanne M.-W. Ho designed the data collection tools, and monitored the data collection for the trial. Jennifer Tung, Tony Antoniou, and Joanne M.-W. Ho analyzed and interpreted the data. Jennifer Tung and Joanne M.-W. Ho drafted the article. All authors (Jennifer Tung, R. Jack Bodkin, Cameron Neat, Thomas Laughton, Sophiya Benjamin, Howard An, Tony Antoniou, and Joanne M.-W. Ho) were involved in the critical revision of the article and the final approval of the version to be published. The funding organization had no role in the design, methods, subject recruitment, data collections, analysis, and preparation of paper. Table S1: Characteristics of participants Table S2: Pharmacotherapy case-based knowledge testing among clinicians using geriatric drug infographics compared to usual resources Table S3: Geriatric drug infographics reading experience and user-friendliness 10-point Likert rating scale Appendix S1: Knowledge questions Appendix S2: Reading experience and user friendliness of geriatric drug infographics Figure S1: Flow chart Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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