Autumn L Stewart1, Kevin J Lynch. 1. Division of Clinical, Social and Administrative Sciences, Mylan School of Pharmacy, Duquesne University, Pittsburgh, PA, USA. run-yona@duq.edu
Abstract
OBJECTIVES: To describe the types and causes of medication discrepancies in the electronic medical record identified by pharmacist medication reconciliation during outpatient medical visits and to identify patient characteristics associated with the presence of discrepancies. DESIGN: Observational case series study. SETTING: Indigent primary care clinic in Pittsburgh, PA, from April 2009 to May 2010. PATIENTS: 219 adults presenting for follow-up medical visits and self-reporting medication use. INTERVENTION: Medication reconciliation as part of patient interview and concurrent chart review. MAIN OUTCOME MEASURES: Frequency, types, and reasons for medication discrepancies and demographic variables, patient knowledge, and adherence. RESULTS: Of 219 patients interviewed, 162 (74%) had at least one discrepancy. The most common type of discrepancy was an incorrect medication documented on the chart. The most common reasons included over-the-counter (OTC) use of medications and patients not reporting use of medications. The presence of one or more medication discrepancies was associated with the use of three or more medications. Patient factors such as gender, age, and race were not associated with discrepancies. Patients able to recall the strength for more than 75% of their medications had fewer discrepancies, while knowledge of the medication name, indication, or regimen had no association with discrepancies. CONCLUSION: Pharmacists play a critical role in identifying discrepancies between charted medication lists and self-reported medication use, independent of adherence. Inaccuracies in charted medications are frequent and often are related to use of OTC therapies and lack of communication and documentation during physician office visits. Knowledge of patient-related variables and other reasons for discrepancies may be useful in identifying patients at greatest risk for discrepancies and interventions to prevent and resolve them.
OBJECTIVES: To describe the types and causes of medication discrepancies in the electronic medical record identified by pharmacist medication reconciliation during outpatient medical visits and to identify patient characteristics associated with the presence of discrepancies. DESIGN: Observational case series study. SETTING: Indigent primary care clinic in Pittsburgh, PA, from April 2009 to May 2010. PATIENTS: 219 adults presenting for follow-up medical visits and self-reporting medication use. INTERVENTION: Medication reconciliation as part of patient interview and concurrent chart review. MAIN OUTCOME MEASURES: Frequency, types, and reasons for medication discrepancies and demographic variables, patient knowledge, and adherence. RESULTS: Of 219 patients interviewed, 162 (74%) had at least one discrepancy. The most common type of discrepancy was an incorrect medication documented on the chart. The most common reasons included over-the-counter (OTC) use of medications and patients not reporting use of medications. The presence of one or more medication discrepancies was associated with the use of three or more medications. Patient factors such as gender, age, and race were not associated with discrepancies. Patients able to recall the strength for more than 75% of their medications had fewer discrepancies, while knowledge of the medication name, indication, or regimen had no association with discrepancies. CONCLUSION: Pharmacists play a critical role in identifying discrepancies between charted medication lists and self-reported medication use, independent of adherence. Inaccuracies in charted medications are frequent and often are related to use of OTC therapies and lack of communication and documentation during physician office visits. Knowledge of patient-related variables and other reasons for discrepancies may be useful in identifying patients at greatest risk for discrepancies and interventions to prevent and resolve them.
Authors: L E Redding; F Cubas-Delgado; M D Sammel; G Smith; D T Galligan; M Z Levy; S Hennessy Journal: Prev Vet Med Date: 2014-02-19 Impact factor: 2.670
Authors: Abraham A Brody; Bryan Gibson; David Tresner-Kirsch; Heidi Kramer; Iona Thraen; Matthew E Coarr; Randall Rupper Journal: J Am Geriatr Soc Date: 2016-09-27 Impact factor: 5.562
Authors: Floor Willeboordse; Jacqueline G Hugtenburg; François G Schellevis; Petra J M Elders Journal: Br J Clin Pharmacol Date: 2014-12 Impact factor: 4.335
Authors: Aaron M Gilson; Jamie A Stone; Ashley O Morris; Roger L Brown; Ka Z Xiong; Nora Jacobson; Richard J Holden; Steven M Albert; Cynthia H Phelan; Denise L Walbrandt Pigarelli; Robert M Breslow; Lauren Welch; Michelle A Chui Journal: J Am Pharm Assoc (2003) Date: 2021-04-15