James Gatenby1, Magnus Blomqvist2, Rosemary Burke3, Angus Ritchie4, Kathy Gibson5, Asad E Patanwala6. 1. The University of Notre Dame Sydney, Sydney, New South Wales, Australia. Electronic address: james.gatenby1@my.nd.edu.au. 2. Health Informatics Unit, Sydney Local Health District, Sydney, New South Wales, Australia. Electronic address: Magnus.Blomqvist@health.nsw.gov.au. 3. Health Informatics Unit, Sydney Local Health District, Sydney, New South Wales, Australia. Electronic address: Rosemary.Burke@health.nsw.gov.au. 4. Health Informatics Unit, Sydney Local Health District, Sydney, New South Wales, Australia; The University of Sydney, Faculty of Medicine and Health, Concord Clinical School, Sydney, New South Wales, Australia. Electronic address: Angus.Ritchie@health.nsw.gov.au. 5. Liverpool Hospital, Sydney, New South Wales, Australia. Electronic address: Kathy.Gibson@health.nsw.gov.au. 6. Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia; The University of Sydney, Faculty of Medicine and Health, Sydney Pharmacy School, Sydney, New South Wales, Australia. Electronic address: asad.patanwala@sydney.edu.au.
Abstract
OBJECTIVE: To identify the types of adverse drug events (ADEs) that drug-drug interaction (DDI) alerts are trying to prevent in hospitalized patients. METHODS: This was a retrospective cross-sectional study conducted in a tertiary referral hospital in Australia. All DDI alerts encountered by prescribers during a 1-month period were evaluated for potential ADEs targeted for prevention. If the same DDI alert occurred for the same patient multiple times during hospitalization, it was counted only once (i.e. first alert). This was termed a 'unique DDI alert' for a given patient. The primary outcome was the type of ADE the alerts were trying to prevent. RESULTS: There were 715 patients who had 1599 unique DDI alerts. The two most common potential ADEs (not mutually exclusive) that the alerts attempted to prevent were QTc prolongation or torsades de pointes (n = 1028/1599, 64 %), followed by extrapyramidal symptoms or neuroleptic malignant syndrome (n = 463/1599, 29 %). Either of these two potential ADEs were present in 83 % (n = 1329/1599) of unique DDI alerts. CONCLUSION: Alerting systems are primarily trying to prevent two types of potential ADEs, which were included in more than 80 % of DDI alerts. This has important implications for patient monitoring in hospitals.
OBJECTIVE: To identify the types of adverse drug events (ADEs) that drug-drug interaction (DDI) alerts are trying to prevent in hospitalized patients. METHODS: This was a retrospective cross-sectional study conducted in a tertiary referral hospital in Australia. All DDI alerts encountered by prescribers during a 1-month period were evaluated for potential ADEs targeted for prevention. If the same DDI alert occurred for the same patient multiple times during hospitalization, it was counted only once (i.e. first alert). This was termed a 'unique DDI alert' for a given patient. The primary outcome was the type of ADE the alerts were trying to prevent. RESULTS: There were 715 patients who had 1599 unique DDI alerts. The two most common potential ADEs (not mutually exclusive) that the alerts attempted to prevent were QTc prolongation or torsades de pointes (n = 1028/1599, 64 %), followed by extrapyramidal symptoms or neuroleptic malignant syndrome (n = 463/1599, 29 %). Either of these two potential ADEs were present in 83 % (n = 1329/1599) of unique DDI alerts. CONCLUSION: Alerting systems are primarily trying to prevent two types of potential ADEs, which were included in more than 80 % of DDI alerts. This has important implications for patient monitoring in hospitals.
Authors: Tyler Gallo; C William Heise; Raymond L Woosley; James E Tisdale; Malinda S Tan; Sheila M Gephart; Corneliu C Antonescu; Daniel C Malone Journal: J Am Heart Assoc Date: 2022-06-03 Impact factor: 6.106