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  • 标题:Adverse drug reactions in drug information databases: does presentation affect interpretation?
  • 本地全文:下载
  • 作者:Sean M. McConachie ; Christopher A. Giuliano ; Insaf Mohammad
  • 期刊名称:Journal of the Medical Library Association
  • 印刷版ISSN:1536-5050
  • 出版年度:2020
  • 卷号:108
  • 期号:1
  • 页码:76-83
  • DOI:10.5195/jmla.2020.748
  • 出版社:Medical Library Association
  • 摘要:Objective Formatting of adverse drug reaction (ADR) information differs among drug information (DI) resources and may impact clinical decision-making. The objective of this study was to determine whether ADR formatting impacts adverse event interpretation by pharmacy practitioners and students. Methods Participants were randomized to receive ADR information in a comparative quantitative (CQUANT), noncomparative quantitative (NQUANT), or noncomparative qualitative (NQUAL) format to interpret 3 clinical vignettes. Vignettes involved patients presenting with adverse events that varied in the extent to which they were associated with a medication. The primary outcome was interpretation of the likelihood of medication-induced adverse events on a 10-point Likert scale. Lower scoring on likelihood (i.e., ADR deemed unlikely) reflected more appropriate interpretation. Linear regression was performed to analyze the effects of ADR information format on the primary outcome. Results A total of 108 participants completed the study (39 students and 69 pharmacists). Overall, the CQUANT group had the lowest average likelihood compared to NQUAL (4.0 versus 5.4; p <0.01) and NQUANT (4.0 versus 4.9; p =0.016) groups. There was no difference between NQUAL and NQUANT groups (5.4 versus 4.9; p =0.14). In the final model, at least 2 years of postgraduate training (−1.1; 95% CI: −1.8 to −0.3; p <0.01) and CQUANT formatting (−1.3; 95% CI: −0.9 to −1.7; p <0.01) were associated with reduced likelihood. Conclusions Formatting impacts pharmacists’ and pharmacy students’ interpretation of ADR information. CQUANT formatting and at least two years of postgraduate training improved interpretation of adverse events..
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