Jan Horsky1,2,3, Elizabeth A Drucker3,4,5, Harley Z Ramelson1,2,3. 1. Brigham & Women's Hospital, Department of Medicine, Division of General Internal Medicine and Primary Care, Boston, MA, USA. 2. Partners HealthCare, Information Systems, Boston, MA, USA. 3. Harvard Medical School, Boston, MA, USA. 4. Newton-Wellesley Hospital, Department of Radiology, Newton, MA, USA. 5. Massachusetts General Hospital, Department of Radiology, Boston, MA, USA.
Abstract
Objective: Investigate the accuracy of 2 different medication reconciliation tools integrated into electronic health record systems (EHRs) using a cognitively demanding scenario and complex medication history. Materials and Methods: Seventeen physicians reconciled medication lists for a polypharmacy patient using 2 EHRs in a simulation study. The lists contained 3 types of discrepancy and were transmitted between the systems via a Continuity of Care Document. Participants updated each EHR and their interactions were recorded and analyzed for the number and type of errors. Results: Participants made 748 drug comparisons that resulted in 53 errors (93% accuracy): 12 using EHR2 (3% rate, 0-3 range) and 41 using EHR1 (11% rate, 0-9 range; P < .0001). Twelve clinicians made completely accurate reconciliations with EHR2 (71%) and 6 with EHR1 (35%). Most errors (28, 53%) occurred in medication entries containing discrepancies: 4 in EHR2 and 24 in EHR1 (P = .008). The order in which participants used the EHRs to complete the task did not affect the results. Discussion: Significantly fewer errors were made with EHR2, which presented lists in a side-by-side view, automatically grouped medications by therapeutic class and more effectively identified duplicates. Participants favored this design and indicated that they routinely used several workarounds in EHR1. Conclusion: Accurate assessment of the safety and effectiveness of electronic reconciliation tools requires rigorous testing and should prioritize complex rather than simpler tasks that are currently used for EHR certification and product demonstration. Higher accuracy of reconciliation is likely when tools are designed to better support cognitively demanding tasks.
Objective: Investigate the accuracy of 2 different medication reconciliation tools integrated into electronic health record systems (EHRs) using a cognitively demanding scenario and complex medication history. Materials and Methods: Seventeen physicians reconciled medication lists for a polypharmacy patient using 2 EHRs in a simulation study. The lists contained 3 types of discrepancy and were transmitted between the systems via a Continuity of Care Document. Participants updated each EHR and their interactions were recorded and analyzed for the number and type of errors. Results:Participants made 748 drug comparisons that resulted in 53 errors (93% accuracy): 12 using EHR2 (3% rate, 0-3 range) and 41 using EHR1 (11% rate, 0-9 range; P < .0001). Twelve clinicians made completely accurate reconciliations with EHR2 (71%) and 6 with EHR1 (35%). Most errors (28, 53%) occurred in medication entries containing discrepancies: 4 in EHR2 and 24 in EHR1 (P = .008). The order in which participants used the EHRs to complete the task did not affect the results. Discussion: Significantly fewer errors were made with EHR2, which presented lists in a side-by-side view, automatically grouped medications by therapeutic class and more effectively identified duplicates. Participants favored this design and indicated that they routinely used several workarounds in EHR1. Conclusion: Accurate assessment of the safety and effectiveness of electronic reconciliation tools requires rigorous testing and should prioritize complex rather than simpler tasks that are currently used for EHR certification and product demonstration. Higher accuracy of reconciliation is likely when tools are designed to better support cognitively demanding tasks.
Authors: Lindsay A Thompson; Matthew J Gurka; Stephanie L Filipp; Desmond A Schatz; Rebeccah E Mercado; David A Ostrov; Mark A Atkinson; Sonja A Rasmussen Journal: EClinicalMedicine Date: 2021-06-04
Authors: Jonathan H DeAntonio; Tammy Nguyen; Gregory Chenault; Michel B Aboutanos; Rahul J Anand; Paula Ferrada; Stephanie Goldberg; Stefan W Leichtle; Levi D Procter; Edgar B Rodas; Alan P Rossi; James F Whelan; V Ramana Feeser; Michael J Vitto; Beth Broering; Sarah Hobgood; Martin Mangino; Dayanjan S Wijesinghe; Sudha Jayaraman Journal: World J Emerg Surg Date: 2019-02-15 Impact factor: 5.469