Jalal Soleimani1, Yuliya Pinevich1, Amelia K Barwise2, Chanyan Huang1,3, Yue Dong1, Vitaly Herasevich1, Ognjen Gajic2, Brian W Pickering1. 1. Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, United States. 2. Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, Minnesota, United States. 3. Department of Anesthesiology, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Abstract
BACKGROUND: Although diagnostic error (DE) is a significant problem, it remains challenging for clinicians to identify it reliably and to recognize its contribution to the clinical trajectory of their patients. The purpose of this work was to evaluate the reliability of real-time electronic health record (EHR) reviews using a search strategy for the identification of DE as a contributor to the rapid response team (RRT) activation. OBJECTIVES: Early and accurate recognition of critical illness is of paramount importance. The objective of this study was to test the feasibility and reliability of prospective, real-time EHR reviews as a means of identification of DE. METHODS: We conducted this prospective observational study in June 2019 and included consecutive adult patients experiencing their first RRT activation. An EHR search strategy and a standard operating procedure were refined based on the literature and expert clinician inputs. Two physician-investigators independently reviewed eligible patient EHRs for the evidence of DE within 24 hours after RRT activation. In cases of disagreement, a secondary review of the EHR using a taxonomy approach was applied. The reviewers categorized patient experience of DE as Yes/No/Uncertain. RESULTS: We reviewed 112 patient records. DE was identified in 15% of cases by both reviewers. Kappa agreement with the initial review was 0.23 and with the secondary review 0.65. No evidence of DE was detected in 60% of patients. In 25% of cases, the reviewers could not determine whether DE was present or absent. CONCLUSION: EHR review is of limited value in the real-time identification of DE in hospitalized patients. Alternative approaches are needed for research and quality improvement efforts in this field. Georg Thieme Verlag KG Stuttgart · New York.
BACKGROUND: Although diagnostic error (DE) is a significant problem, it remains challenging for clinicians to identify it reliably and to recognize its contribution to the clinical trajectory of their patients. The purpose of this work was to evaluate the reliability of real-time electronic health record (EHR) reviews using a search strategy for the identification of DE as a contributor to the rapid response team (RRT) activation. OBJECTIVES: Early and accurate recognition of critical illness is of paramount importance. The objective of this study was to test the feasibility and reliability of prospective, real-time EHR reviews as a means of identification of DE. METHODS: We conducted this prospective observational study in June 2019 and included consecutive adult patients experiencing their first RRT activation. An EHR search strategy and a standard operating procedure were refined based on the literature and expert clinician inputs. Two physician-investigators independently reviewed eligible patient EHRs for the evidence of DE within 24 hours after RRT activation. In cases of disagreement, a secondary review of the EHR using a taxonomy approach was applied. The reviewers categorized patient experience of DE as Yes/No/Uncertain. RESULTS: We reviewed 112 patient records. DE was identified in 15% of cases by both reviewers. Kappa agreement with the initial review was 0.23 and with the secondary review 0.65. No evidence of DE was detected in 60% of patients. In 25% of cases, the reviewers could not determine whether DE was present or absent. CONCLUSION: EHR review is of limited value in the real-time identification of DE in hospitalized patients. Alternative approaches are needed for research and quality improvement efforts in this field. Georg Thieme Verlag KG Stuttgart · New York.
Authors: Richard Chalwin; Lynne Giles; Amy Salter; Victoria Eaton; Karoline Kapitola; Jonathan Karnon Journal: Jt Comm J Qual Patient Saf Date: 2018-12-03
Authors: Ali S Saber Tehrani; HeeWon Lee; Simon C Mathews; Andrew Shore; Martin A Makary; Peter J Pronovost; David E Newman-Toker Journal: BMJ Qual Saf Date: 2013-04-22 Impact factor: 7.035