Allison B McCoy1, Adam Wright2, Dean F Sittig3. 1. Department of Biostatistics and Bioinformatics, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA amccoy1@tulane.edu. 2. Division of General Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA Partners HealthCare, Boston, MA, USA Harvard Medical School, Boston, MA, USA. 3. The University of Texas School of Biomedical Informatics at Houston, Houston, TX, USA.
Abstract
OBJECTIVE: Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems. METHODS: We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin. RESULTS: Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules. CONCLUSION: Significant improvements in the EHR certification and implementation procedures are necessary.
OBJECTIVE: Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems. METHODS: We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin. RESULTS: Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules. CONCLUSION: Significant improvements in the EHR certification and implementation procedures are necessary.
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