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

Abstract

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.

Computerized clinical decision support systems for prescribing in primary care: main characteristics and implementation impact—protocol of an evidence and gap map

“…bubble plot) will be used to display the evidence landscape and to elucidate clusters and gaps. We have developed a conceptual model of system categories through a process of debate and consensus taking into account the characteristics described in the literature cited in the introduction, regarding prescribing support systems in hospitals [5][6][7][8][9][10][11][12][13][14] and primary care [15][16][17][18][19][20][21][22].…”

“…Several systematic reviews about CDSS for prescribing (CDSS-P) in hospital settings describe a wide focus of these systems ranging from assisting clinicians in drug selection and dosing suggestions, alerting potential adverse drug reactions and drug allergies, identifying duplication of therapy, and advising change prescribing in accordance with guidelines. They also identified a wide range of levels of complexity and interactions between the information in the patient's clinical record and the information relating to the prescribed medication [5][6][7][8][9][10][11][12][13]. However, meta-analyses of CDSS-P about clinical effectiveness have proved to be challenging [14].…”

Computerized Clinical Decision Support Systems for Prescribing in Primary Care: Main Characteristics and Implementation Impact. Protocol of an Evidence and Gap Map.

“…Tables and gures (ie, bubble plot) will be used to display the evidence landscape and to elucidate clusters and gaps. We have developed a conceptual model of system categories through a process of debate and consensus taking into account the characteristics described in the literature cited in the introduction, regarding prescribing support systems in hospitals (5)(6)(7)(8)(9)(10)(11)(12)(13)(14) and primary care (15)(16)(17)(18)(19)(20)(21)(22).…”

“…Several systematic reviews about CDSS for prescribing (CDSS-P) in hospital settings, describe a wide focus of these systems ranging from assisting clinicians in drug selection and dosing suggestions, alerting potential adverse drug reactions and drug allergies, identifying duplication of therapy and advising change prescribing in accordance with guideline. They also identi ed a wide range of levels of complexity and interactions between the information in the patient's clinical record and the information relating to the prescribed medication (5)(6)(7)(8)(9)(10)(11)(12)(13). However, meta-analyses of CDSS-P about clinical effectiveness have proved to be challenging (14).…”

The effect of electronic error-reporting forms on nurse’s stress and the rate of error-reporting

“…17 Due to lack of an official source for reporting medical errors in Iran, no accurate data exist on the errors occurring, but according to the Ministry of Health, annually several billion Dollars are spent on additional hospital fees due to medical errors. 18 Some countries use CPOE (Computerized Physician Order Entry), 19 EHR (Electronic Health Record), 20 RFID (Radio Frequency Identification), 21 CDSS (Clinical Decision Support System), 19 and HIS (Hospital Information Systems) [21][22][23] to reduce medical errors. Because of the importance of medical errors, the IOM (Institute Of Medicine) has proposed solutions to reduce the amount of these errors, including the development of a medical error-reporting system and encouraging individuals to report errors voluntarily.…”