A decision support system for demand and capacity modelling of an accident and emergency department

BACKGROUND Physicians’ alert overriding behavior is considered to be the most important factor leading to failure of computerized provider order entry (CPOE) combined with a clinical decision support system (CDSS) in achieving its potential adverse drug events prevention effect. Previous studies on this subject have focused on specific diseases or alert types for well-defined targets and particular settings. The emergency department is an optimal environment to examine physicians’ alert overriding behaviors from a broad perspective because patients have a wider range of severity, and many receive interdisciplinary care in this environment. However, less than one-tenth of related studies have targeted this physician behavior in an emergency department setting. OBJECTIVE The aim of this study was to describe alert override patterns with a commercial medication CDSS in an academic emergency department. METHODS This study was conducted at a tertiary urban academic hospital in the emergency department with an annual census of 80,000 visits. We analyzed data on the patients who visited the emergency department for 18 months and the medical staff who treated them, including the prescription and CPOE alert log. We also performed descriptive analysis and logistic regression for assessing the risk factors for alert overrides. RESULTS During the study period, 611 physicians cared for 71,546 patients with 101,186 visits. The emergency department physicians encountered 13.75 alerts during every 100 orders entered. Of the total 102,887 alerts, almost two-thirds (65,616, 63.77%) were overridden. Univariate and multivariate logistic regression analyses identified 21 statistically significant risk factors for emergency department physicians’ alert override behavior. CONCLUSIONS In this retrospective study, we described the alert override patterns with a medication CDSS in an academic emergency department. We found relatively low overrides and assessed their contributing factors, including physicians’ designation and specialty, patients’ severity and chief complaints, and alert and medication type.

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Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study

JMIR Medical Informatics ◽

10.2196/23351 ◽

2020 ◽

Vol 8 (11) ◽

pp. e23351 ◽

Cited By ~ 1

Author(s):

Junsang Yoo ◽

Jeonghoon Lee ◽

Poong-Lyul Rhee ◽

Dong Kyung Chang ◽

Mira Kang ◽

...

Keyword(s):

Risk Factors ◽

Emergency Department ◽

Logistic Regression ◽

Decision Support ◽

Decision Support System ◽

Clinical Decision Support ◽

Support System ◽

Clinical Decision Support System ◽

Clinical Decision ◽

Broad Perspective

Background Physicians’ alert overriding behavior is considered to be the most important factor leading to failure of computerized provider order entry (CPOE) combined with a clinical decision support system (CDSS) in achieving its potential adverse drug events prevention effect. Previous studies on this subject have focused on specific diseases or alert types for well-defined targets and particular settings. The emergency department is an optimal environment to examine physicians’ alert overriding behaviors from a broad perspective because patients have a wider range of severity, and many receive interdisciplinary care in this environment. However, less than one-tenth of related studies have targeted this physician behavior in an emergency department setting. Objective The aim of this study was to describe alert override patterns with a commercial medication CDSS in an academic emergency department. Methods This study was conducted at a tertiary urban academic hospital in the emergency department with an annual census of 80,000 visits. We analyzed data on the patients who visited the emergency department for 18 months and the medical staff who treated them, including the prescription and CPOE alert log. We also performed descriptive analysis and logistic regression for assessing the risk factors for alert overrides. Results During the study period, 611 physicians cared for 71,546 patients with 101,186 visits. The emergency department physicians encountered 13.75 alerts during every 100 orders entered. Of the total 102,887 alerts, almost two-thirds (65,616, 63.77%) were overridden. Univariate and multivariate logistic regression analyses identified 21 statistically significant risk factors for emergency department physicians’ alert override behavior. Conclusions In this retrospective study, we described the alert override patterns with a medication CDSS in an academic emergency department. We found relatively low overrides and assessed their contributing factors, including physicians’ designation and specialty, patients’ severity and chief complaints, and alert and medication type.

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Using trigger tools to identify triage errors by ambulance dispatch nurses in Sweden: an observational study

BMJ Open ◽

10.1136/bmjopen-2019-035004 ◽

2020 ◽

Vol 10 (3) ◽

pp. e035004 ◽

Cited By ~ 1

Author(s):

Douglas Spangler ◽

Lennart Edmark ◽

Ulrika Winblad ◽

Jessica Colldén-Benneck ◽

Helena Borg ◽

...

Keyword(s):

Primary Care ◽

Emergency Department ◽

Decision Support ◽

Observational Study ◽

Decision Support System ◽

Support System ◽

Emergency Care ◽

Incident Reporting Systems ◽

Dispatch Centre ◽

Reporting Systems

ObjectivesThis study aimed to assess whether trigger tools were useful identifying triage errors among patients referred to non-emergency care by emergency medical dispatch nurses, and to describe the characteristics of these patients.DesignAn observational study of patients referred by dispatch nurses to non-emergency care.SettingDispatch centres in two Swedish regions.ParticipantsA total of 1089 adult patients directed to non-emergency care by dispatch nurses between October 2016 and February 2017. 53% were female and the median age was 61 years.Primary and secondary outcome measuresThe primary outcome was a visit to an emergency department within 7 days of contact with the dispatch centre. Secondary outcomes were (1) visits related to the primary contact with the dispatch centre, (2) provision of care above the primary level (ie, interventions not available at a typical local primary care centre) and (3) admission to hospital in-patient care.ResultsOf 1089 included patients, 260 (24%) visited an emergency department within 7 days. Of these, 209 (80%) were related to the dispatch centre contact, 143 (55%) received interventions above the primary care level and 99 (38%) were admitted to in-patient care. Elderly (65+) patients (OR 1.45, 95% CI 1.05 to 1.98) and patients referred onwards to other healthcare providers (OR 1.58, 95% CI 1.15 to 2.19) had higher likelihoods of visiting an emergency department. Six avoidable patient harms were identified, none of which were captured by existing incident reporting systems, and all of which would have received an ambulance if the decision support system had been strictly adhered to.ConclusionThe use of these patient outcomes in the framework of a Global Trigger Tool-based review can identify patient harms missed by incident reporting systems in the context of emergency medical dispatching. Increased compliance with the decision support system has the potential to improve patient safety.

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