The Impact of Lighting and Typography on Medication Prescription Reading Errors: An Experimental Study

Background: Medication errors, particularly those related to prescription and label reading, pose a significant challenge in healthcare, affecting patient safety and the quality of care. Objectives: This study aimed to identify lighting conditions and typographic features (font size and type) that reduce reading errors in printed medication prescriptions and to evaluate their combined effects on error rates. Methods: This cross-sectional study involved 30 female nurses (aged 25 - 40) and used repeated measures to assess reading errors in standardized prescriptions under controlled conditions. The independent variables included light intensity (150 lx, 500 lx), correlated color temperature (CCT: 2700 K, 4000 K, 6500 K), font types (Tahoma, Zar, Yekan), and font sizes (9 pt, 11 pt, 13 pt). A linear mixed-effects model was used to analyze the data. Results: Light intensity significantly influenced reading errors [F (5, 1404) = 17.39, P < 0.001, η2p = 0.058], with 500 lx reducing errors by up to 28.2% compared to 150 lx (e.g., optimal lighting conditions: 500 lx & 6500 K vs. current conditions: 150 lx & 4000 K, as implemented in the studied hospital). Font size also had a significant effect [F (2, 1404) = 44.65, P < 0.001, η2p = 0.060], with 11 pt and 13 pt reducing errors by 12.5% and 15%, respectively, compared to 9 pt. The results indicated that CCT and font type had no significant impact on reading errors. Furthermore, participants preferred the 500 lx & 6500 K lighting condition for its pleasantness and perceived adequacy. Conclusions: Higher light intensity (500 lx) and larger font sizes (≥ 11 pt) significantly enhance prescription readability, offering practical solutions to reduce medication errors. These findings underscore the need for optimized lighting and typography in healthcare settings to improve patient safety. However, because this study was limited to Persian fonts, young, healthy females, and printed medication prescriptions, further research is needed to assess generalizability across different ages, genders, writing systems, and handwritten prescriptions.