共 2 条
Optimising computerised decision support to transform medication safety and reduce prescriber burden: study protocol for a mixed-methods evaluation of drug-drug interaction alerts
被引:5
|作者:
Baysari, Melissa T.
Zheng, Wu Yi
Li, Ling
Westbrook, Johanna
Day, Richard O.
Hilmer, Sarah
Van Dort, Bethany Annemarie
Hargreaves, Andrew
Kennedy, Peter
Monaghan, Corey
Doherty, Paula
Draheim, Michael
Nair, Lucy
Samson, Ruby
机构:
[1] Faculty of Health Sciences, University of Sydney, Sydney, NSW
[2] Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW
[3] St Vincent's Clinical School, UNSW Medicine, UNSW Sydney, Sydney, NSW
[4] Department of Clinical Pharmacology and Toxicology, St Vincent's Hospital, Sydney, NSW
[5] Kolling Institute of Medical Researc, Northern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW
[6] Departments of Clinical Pharmacology and Aged Care, Royal North Shore Hospital, Sydney, NSW
[7] EHealth NSW, Sydney, NSW
[8] EHealth QLD, Queensland Department of Health, Brisbane, QLD
[9] John Hunter Hospital, Hunter New England Local Health District, Newcastle, NSW
[10] Metro South Health Service District, Brisbane, QLD
[11] Bankstown-Lidcombe Hospital, Bankstown, NSW
[12] Nepean Hospital, Blue Mountains, NSW
来源:
BMJ OPEN
|
2019年
/
9卷
/
08期
基金:
英国医学研究理事会;
关键词:
drug-drug interaction;
decision support;
alert;
alert fatigue;
KNOWLEDGE;
SYSTEMS;
ENTRY;
D O I:
10.1136/bmjopen-2018-026034
中图分类号:
R5 [内科学];
学科分类号:
1002 ;
100201 ;
摘要:
Introduction Drug-drug interaction (DDI) alerts in hospital electronic medication management (EMM) systems are generated at the point of prescribing to warn doctors about potential interactions in their patients' medication orders. This project aims to determine the impact of DDI alerts on DDI rates and on patient harm in the inpatient setting. It also aims to identify barriers and facilitators to optimal use of alerts, quantify the alert burden posed to prescribers with implementation of DDI alerts and to develop algorithms to improve the specificity of DDI alerting systems. Methods and analysis A controlled pre-post design will be used. Study sites include six major referral hospitals in two Australian states, New South Wales and Queensland. Three hospitals will act as control sites and will implement an EMM system without DDI alerts, and three as intervention sites with DDI alerts. The medical records of 280 patients admitted in the 6months prior to and 6months following implementation of the EMM system at each site (total 3360 patients) will be retrospectively reviewed by study pharmacists to identify potential DDIs, clinically relevant DDIs and associated patient harm. To identify barriers and facilitators to optimal use of alerts, 10-15 doctors working at each intervention hospital will take part in observations and interviews. Non-identifiable DDI alert data will be extracted from EMM systems 6-12 months after system implementation in order to quantify alert burden on prescribers. Finally, data collected from chart review and EMM systems will be linked with clinically relevant DDIs to inform the development of algorithms to trigger only clinically relevant DDI alerts in EMM systems. Ethics and dissemination This research was approved by the Hunter New England Human Research Ethics Committee (18/02/21/4.07). Study results will be published in peer-reviewed journals and presented at local and international conferences and workshops.
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