Zoe Co1, A Jay Holmgren2, David C Classen3, Lisa P Newmark4, Diane L Seger4, Jessica M Cole5, Barbara Pon6, Karen P Zimmer7, David W Bates1,4,8. 1. Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States. 2. Harvard Business School, Boston, Massachusetts, United States. 3. Department of Clinical Epidemiology, University of Utah, Salt Lake City, Utah, United States. 4. Clinical and Quality Analysis, Mass General Brigham, Somerville, Massachusetts, United States. 5. Department of Internal Medicine, Division of Epidemiology, University of Utah, Salt Lake City, Utah, United States. 6. Collaborative Healthcare Patient Safety Organization, Sacramento, California, United States. 7. Department of Pediatrics, Thomas Jefferson University, Philadelphia, Pennsylvania, United States. 8. Harvard Medical School, Boston, Massachusetts, United States.
Abstract
BACKGROUND: Substantial research has been performed about the impact of computerized physician order entry on medication safety in the inpatient setting; however, relatively little has been done in ambulatory care, where most medications are prescribed. OBJECTIVE: To outline the development and piloting process of the Ambulatory Electronic Health Record (EHR) Evaluation Tool and to report the quantitative and qualitative results from the pilot. METHODS: The Ambulatory EHR Evaluation Tool closely mirrors the inpatient version of the tool, which is administered by The Leapfrog Group. The tool was piloted with seven clinics in the United States, each using a different EHR. The tool consists of a medication safety test and a medication reconciliation module. For the medication test, clinics entered test patients and associated test orders into their EHR and recorded any decision support they received. An overall percentage score of unsafe orders detected, and order category scores were provided to clinics. For the medication reconciliation module, clinics demonstrated how their EHR electronically detected discrepancies between two medication lists. RESULTS: For the medication safety test, the clinics correctly alerted on 54.6% of unsafe medication orders. Clinics scored highest in the drug allergy (100%) and drug-drug interaction (89.3%) categories. Lower scoring categories included drug age (39.3%) and therapeutic duplication (39.3%). None of the clinics alerted for the drug laboratory or drug monitoring orders. In the medication reconciliation module, three (42.8%) clinics had an EHR-based medication reconciliation function; however, only one of those clinics could demonstrate it during the pilot. CONCLUSION: Clinics struggled in areas of advanced decision support such as drug age, drug laboratory, and drub monitoring. Most clinics did not have an EHR-based medication reconciliation function and this process was dependent on accessing patients' medication lists. Wider use of this tool could improve outpatient medication safety and can inform vendors about areas of improvement. Thieme. All rights reserved.
BACKGROUND: Substantial research has been performed about the impact of computerized physician order entry on medication safety in the inpatient setting; however, relatively little has been done in ambulatory care, where most medications are prescribed. OBJECTIVE: To outline the development and piloting process of the Ambulatory Electronic Health Record (EHR) Evaluation Tool and to report the quantitative and qualitative results from the pilot. METHODS: The Ambulatory EHR Evaluation Tool closely mirrors the inpatient version of the tool, which is administered by The Leapfrog Group. The tool was piloted with seven clinics in the United States, each using a different EHR. The tool consists of a medication safety test and a medication reconciliation module. For the medication test, clinics entered test patients and associated test orders into their EHR and recorded any decision support they received. An overall percentage score of unsafe orders detected, and order category scores were provided to clinics. For the medication reconciliation module, clinics demonstrated how their EHR electronically detected discrepancies between two medication lists. RESULTS: For the medication safety test, the clinics correctly alerted on 54.6% of unsafe medication orders. Clinics scored highest in the drug allergy (100%) and drug-drug interaction (89.3%) categories. Lower scoring categories included drug age (39.3%) and therapeutic duplication (39.3%). None of the clinics alerted for the drug laboratory or drug monitoring orders. In the medication reconciliation module, three (42.8%) clinics had an EHR-based medication reconciliation function; however, only one of those clinics could demonstrate it during the pilot. CONCLUSION: Clinics struggled in areas of advanced decision support such as drug age, drug laboratory, and drub monitoring. Most clinics did not have an EHR-based medication reconciliation function and this process was dependent on accessing patients' medication lists. Wider use of this tool could improve outpatient medication safety and can inform vendors about areas of improvement. Thieme. All rights reserved.
Authors: Zoe Co; A Jay Holmgren; David C Classen; Lisa Newmark; Diane L Seger; Melissa Danforth; David W Bates Journal: J Am Med Inform Assoc Date: 2020-08-01 Impact factor: 4.497
Authors: D W Bates; J M Teich; J Lee; D Seger; G J Kuperman; N Ma'Luf; D Boyle; L Leape Journal: J Am Med Inform Assoc Date: 1999 Jul-Aug Impact factor: 4.497
Authors: D W Bates; L L Leape; D J Cullen; N Laird; L A Petersen; J M Teich; E Burdick; M Hickey; S Kleefield; B Shea; M Vander Vliet; D L Seger Journal: JAMA Date: 1998-10-21 Impact factor: 56.272
Authors: Alemayehu B Mekonnen; Tamrat B Abebe; Andrew J McLachlan; Jo-Anne E Brien Journal: BMC Med Inform Decis Mak Date: 2016-08-22 Impact factor: 2.796