scholarly journals Effect of Computerized Physician Order Entry and Clinical Decision Support System on Adverse Drug Events Prevention in the Emergency Department: A Systematic Review

2020 ◽  
pp. 875512252095816
Author(s):  
Sadrieh Hajesmaeel Gohari ◽  
Kambiz Bahaadinbeigy ◽  
Shahrad Tajoddini ◽  
Sharareh R. Niakan Kalhori
Keyword(s):  
Emergency Department ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Computerized Physician Order Entry ◽  
Order Entry ◽  
Physician Order Entry

Objective: An adverse drug event (ADE) is an injury resulting from a medical intervention related to a drug. The emergency department (ED) is a ward vulnerable to more ADEs because of overcrowding. Information technologies such as computerized physician order entry (CPOE) and clinical decision support system (CDSS) may decrease the occurrence of ADEs. This study aims to review research that reported the evaluation of the effectiveness of CPOE and CDSS on lowering the occurrence of ADEs in the ED. Data Sources: PubMed, EMBASE, and Web of Science databases were used to find studies published from 2003 to 2018. The search was conducted in November 2018. Study Selection and Data Extraction: The search resulted in 1700 retrieved articles. After applying inclusion and exclusion criteria, 11 articles were included. Data on the date, country, type of system, medication process stages, study design, participants, sample size, and outcomes were extracted. Data Synthesis: Results showed that CPOE and CDSS may prevent ADEs in the ED through significantly decreasing the rate of errors, ADEs, excessive dose, and inappropriate prescribing (in 54.5% of articles); furthermore, CPOE and CDSS may significantly increase the rate of appropriate prescribing and dosing in compliance with established guidelines (45.5% of articles). Conclusion: This study revealed that the use of CPOE and CDSS can lower the occurrence of ADEs in the ED; however, further randomized controlled trials are needed to address the effect of a CDSS, with basic or advanced features, on the occurrence of ADEs in the ED.

Verhindern von unerwünschten Arzneimittelereignissen mit Hilfe von elektronischen Entscheidungsunterstützungssystemen

2015 ◽  
Vol 72 (11/12) ◽  
pp. 693-700
Author(s):  
Ali Reza Salili ◽  
Felix Hammann ◽  
Anne B. Taegtmeyer
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Computerized Physician Order Entry ◽  
Order Entry ◽  
Computerized Provider Order Entry ◽  
Unerwünschte Arzneimittelereignisse ◽  
Physician Order Entry

Zusammenfassung. Unerwünschte Arzneimittelereignisse sind ein grosses Risiko für Patienten und ein alltägliches klinisches Problem mit potentiellen Haftungsfolgen. CPOE-Systeme („Computerized Physician Order Entry“ bzw. „Computerized Provider Order Entry“-Systeme) in Kombination mit elektronischen Systemen zur klinischen Entscheidungsunterstützung („Clinical Decision Support System“ = „CDSS“) sind im Trend und zielen nicht nur auf die Reduktion von Verordnungsfehlern, sondern ermöglichen eine rasche Reaktion auf potentiell vermeidbare Arzneimittelinteraktionen. Der effektive Nutzen solcher Systeme ist aber bis dato noch nicht definitiv geklärt. Dieser Artikel fokussiert auf den aktuellen Stand der Entwicklung von CPOE-/CDS-Systemen, deren Nutzen und Risiken, Zukunftsperspektiven und Verbesserungsmöglichkeiten.

scholarly journals Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study (Preprint)

2020 ◽  
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.

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

10.2196/23351 ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. e23351 ◽  
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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