Inclusion of salt form on prescription medication labeling as a source of patient confusion: a pilot study

Background: It has been estimated that 10,000 patient injuries occur in the US annually due to confusion involving drug names. An unexplored source of patient misunderstandings may be medication salt forms. Objective: The objective of this study was to assess patient knowledge and comprehension regarding the salt forms of medications as a potential source of medication errors. Methods: A 12 item questionnaire which assessed patient knowledge of medication names on prescription labels was administered to a convenience sample of patients presenting to a family practice clinic. Descriptive statistics were calculated and multivariate analyses were performed. Results: There were 308 responses. Overall, 41% of patients agreed they find their medication names confusing. Participants correctly answered to salt form questions between 12.1% and 56.9% of the time. Taking more prescription medications and higher education level were positively associated with providing more correct answers to 3 medication salt form knowledge questions, while age was negatively associated. Conclusions: Patient misconceptions about medication salt forms are common. These findings support recommendations to standardize the inclusion or exclusion of salt forms. Increasing patient education is another possible approach to reducing confusion.

Comparison of the traditional pharmaceutical validation method versus an assisted pharmaceutical validation in hospitalized patients

Objective: To analyze pharmaceutical interventions that have been carried out with the support of an automated system for validation of treatments vs. the traditional method without computer support. Method: The automated program, ALTOMEDICAMENTOS® version 0, has 925 052 data with information regarding approximately 20 000 medicines, analyzing doses, administration routes, number of days with such a treatment, dosing in renal and liver failure, interactions control, similar drugs, and enteral medicines. During eight days, in four different hospitals (high complexity with over 1 000 beds, 400-bed intermediate, geriatric and monographic), the same patients and treatments were analyzed using both systems. Results: 3,490 patients were analyzed, with 42 155 different treatments. 238 interventions were performed using the traditional system (interventions 0.56% / possible interventions) vs. 580 (1.38%) with the automated one. Very significant pharmaceutical interventions were 0.14% vs. 0.46%; significant was 0.38% vs. 0.90%; non-significant was 0.05% vs. 0.01%, respectively. If both systems are simultaneously used, interventions are performed in 1.85% vs. 0.56% with just the traditional system. Using only the traditional model, 30.5% of the possible interventions are detected, whereas without manual review and only the automated one, 84% of the possible interventions are detected. Conclusions: The automated system increases pharmaceutical interventions between 2.43 to 3.64 times. According to the results of this study the traditional validation system needs to be revised relying on automated systems. The automated program works correctly in different hospitals.