Adverse drug reactions in drug information databases: does presentation affect interpretation?
Keywords:Adverse Drug Reaction, Clinical Pharmacy Information Systems, Drug Information Service
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.
Kantor ED, Rehm CD, Haas JS, Chan AT, Giovannucci EL. Trends in prescription drug use among adults in the United States from 1999–2012. JAMA. 2015 Nov 3;314(17):1818–31. DOI: http://dx.doi.org/10.1001/jama.2015.13766.
Institute for Safe Medication Practices. Baxter and the Institute for Safe Medication Practices (ISMP) address global medication error prevention [Internet]. The Institute; 2017 [cited 21 May 2019]. <https://www.ismp.org/news/baxter-and-institute-safe-medication-practices-ismp-address-global-medication-error-prevention>.
Miguel A, Azevedo LF, Araujo M, Pereira AC. Frequency of adverse drug reactions in hospitalized patients: a systematic review and meta-analysis. Pharmacoepidemiol Drug Saf. 2012 Nov;21(11):1139–54. DOI: http://dx.doi.org/10.1002/pds.3309.
Kongkaew C, Noyce PR, Ashcroft DM. Hospital admissions associated with adverse drug reactions: a systematic review of prospective observational studies. Ann Pharmacother. 2008 Jul;42(7–8):1017–25. DOI: http://dx.doi.org/10.1345/aph.1L037.
Greenhalgh T, Kostopolou O, Harries C. Making decisions about medications and harms of medicines. BMJ. 2004 Jul 3;329(7456):47–50. DOI: http://dx.doi.org/10.1136/bmj.329.7456.47.
Wahab IA, Pratt NL, Kalisch LM, Roughead EE. The detection of adverse events in randomized clinical trials: can we really say new medicines are safe? Curr Drug Saf. 2013 Apr;8(2):104–13. DOI: http://dx.doi.org/10.2174/15748863113089990030.
Beninger P. Pharmacovigilance: an overview. Clin Ther. 2018 Dec;40(12):1991–2004. DOI: http://dx.doi.org/10.1016/j.clinthera.2018.07.012.
Sharrar RG, Dieck GS. Monitoring product safety in the postmarketing environment. Ther Adv Drug Saf. 2013 Oct;4(5):211–9. DOI: http://dx.doi.org/10.1177/2042098613490780.
Tangisuran B, Auyeung V, Cheek L, Rajkumar C, Davies G. Interrater reliability of the assessment of adverse drug reactions in the hospitalised elderly. J Nutr Health Aging. 2013 Oct;17(8):700–5. DOI: http://dx.doi.org/10.1007/s12603-013-0011-1.
Arimone Y, Begaud B, Miremont-Salame G, Fourrier-Reglat A, Moore N, Molimard M, Haramburu F. Agreement of expert judgement in causality assessment of adverse drug reactions. Eur J Clin Pharmacol. 2005 May;61(3):169–73. DOI: http://dx.doi.org/10.1007/s00228-004-0869-2.
Arimone Y, Miremont-Salame G, Haramburu F, Molimard M, Moore N, Fourrier-Reglat A, Begaud B. Inter-expert agreement of seven criteria in causality assessment of adverse drug reactions. Br J Clin Pharmacol. 2007 Oct;64(4):482–8. DOI: http://dx.doi.org/10.1111/j.1365-2125.2007.02937.x.
Behera SK, Das S, Xavier AS, Velupula S, Sandhiya S. Comparison of different methods for causality assessment of adverse drug reactions. Int J Clin Pharm. 2018 Aug;40(4):903–10. DOI: http://dx.doi.org/10.1007/s11096-018-0694-9.
Belgado BS, Hatton RC, Doering PL. Evaluation of electronic drug information resources for answering questions received by decentralized pharmacists. Am J Health Syst Pharm. 1997 Nov 15;54(22):2592–6. DOI: http://dx.doi.org/10.1093/ajhp/54.22.2592.
Moutford CM, Lee T, De Lemos J, Loewen PS. Quality and usability of common drug information databases. Can J Hosp Pharm. 2010 Mar;63(2):130–7. DOI: http://dx.doi.org/10.4212/cjhp.v63i2.898.
Clauson KA, Marsh WA, Polen HH, Seamon MJ, Ortiz BI. Clinical decision support tools: analysis of online drug information databases. BMC Med Inform Decis Mak. 2007 Mar 8;7:7. DOI: http://dx.doi.org/10.1186/1472-6947-7-7.
Polen HH, Zapantis A, Clauson KA, Jebrock J, Paris M. Ability of online drug databases to assist in clinical decision-making with infectious disease therapies. BMC Infect Dis. 2008 Nov 6;8:153. DOI: http://dx.doi.org/10.1186/1471-2334-8-153.
Rambaran KA, Huynh HA, Zhang Z, Robles J. The gap in electronic drug information resources: a systematic review. Cureus. 2018 Jun 22;10(6):e2860. DOI: http://dx.doi.org/10.7759/cureus.2860.
Sinayev A, Peters E, Tusler M, Fraenkel L. Presenting numeric information with percentages and descriptive risk labels: a randomized trial. Med Decis Making. 2015 Nov;35(8):937–47. DOI: http://dx.doi.org/10.1177/0272989X15584922.
Gong J, Zhang Y, Yang Z, Huang Y, Feng J, Zhang W. The framing effect in medical decision-making: a review of the literature. Psychol Health Med. 2013;18(6):645–53. DOI: http://dx.doi.org/10.1080/13548506.2013.766352.
Perneger TV, Agoritsas T. Doctors and patients’ susceptibility to framing bias: a randomized trial. J Gen Intern Med. 2011 Dec;26(12):1411–7. DOI: http://dx.doi.org/10.1007/s11606-011-1810-x.
Peters E, Sol Hart P, Fraenkel L. Informing patients: the influence of numeracy, framing, and format of side effect information on risk perceptions. Med Decis Making. 2011 May–Jun;31(3):432–6. DOI: http://dx.doi.org/10.1177/0272989X10391672.
Bui T, Krieger HA, Blumenthal-Barby JS. Framing effects on physicians’ judgement and decision making. Psychol Rep. 2015 Oct;117(2):508–22. DOI: http://dx.doi.org/10.2466/13.PR0.117c20z0.
O’Donohughe AC, Sullivan HW, Aikin KJ. Randomized study of placebo and framing information in direct-to-consumer print advertisements for prescription drugs. Ann Behav Med. 2014 Dec;48(3):311–22. DOI: http://dx.doi.org/10.1007/s12160-014-9603-1.
Lipkus IM. Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations. Med Decis Making. 2007 Sep/Oct;27(5):696–713. DOI: http://dx.doi.org/10.1177/0272989X07307271.
Woloshin S, Schwartz LM, Tremmel J, Welch HG. Direct-to-consumer advertisements for prescription drugs: what are Americans being sold? Lancet. 2001 Oct 6;358(9288):1141–6. DOI: http://dx.doi.org/10.1016/S0140-6736(01)06254-7.
Bradley CK, Wang TY, Li S, Robinson JG, Roger VL, Goldberg AC, Virani SS, Louie MJ, Lee LV, Peterson ED, Navar AM. Patient-reported reasons for declining or discontinuing statin therapy: insights from the PALM Registry. J Am Heart Assoc. 2019 Apr 2;8(7):e011765. DOI: http://dx.doi.org/10.1161/JAHA.118.011765.
Toth PP, Patti AM, Giglio RV, Nikolic D, Castellino G, Rizzo M, Banach M. Management of statin intolerance in 2018: still more questions than answers. Am J Cardiovasc Drugs. 2018 Jun;18(3):157–73. DOI: http://dx.doi.org/10.1007/s40256-017-0259-7.
Zhang H, Plutzky J, Skentzos S, Morrison F, Mar P, Shubina M, Turchin A. Discontinuation of statins in routine care settings: a cohort study. Ann Intern Med. 2013 Apr 2;158(7):526–34. DOI: http://dx.doi.org/10.7326/0003-4819-158-7-201304020-00004.
American Society of Health-System Pharmacists. Guidance document for the ASHP accreditation standard for postgraduate year one (PGY1) pharmacy residency programs [Internet]. The Society; 2019 [cited 3 May 2019]. <https://www.ashp.org/-/media/assets/professional-development/residencies/docs/guidance-document-PGY1-standards.ashx>.
Ipema HJ, Lodolce AE, Mancuso CE. Survey of drug information activities of ASHP-accredited pharmacy practice residency programs. Am J Health Syst Pharm. 2011 Jul;68(13):1194–5. DOI: http://dx.doi.org/10.2146/ajhp100360.
Accreditation Council for Pharmacy Education. Accreditation standards and key elements for the professional program in pharmacy leading to the doctor of pharmacy degree [Internet]. The Council; 2015 [cited 3 May 2019]. <https://www.acpe-accredit.org/pdf/Standards2016FINAL.pdf>.
Naranjo CA, Busto U, Sellers EM, Sandor P, Ruiz I, Roberts EA, Janecek E, Domecq C, Greenblatt DJ. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981 Aug;30(2):239–45. DOI: http://dx.doi.org/10.1038/clpt.1981.154.
This work is licensed under a Creative Commons Attribution 4.0 International License.