Specifications of Computerized Provider Order Entry and Clinical Decision Support Systems for Cancer Patients Undergoing Chemotherapy: A Systematic Review

Chemotherapy ◽  
2018 ◽  
Vol 63 (3) ◽  
pp. 162-171 ◽  
Author(s):  
Rezvan Rahimi ◽  
Alireza Kazemi ◽  
Hamid Moghaddasi ◽  
Khadijeh Arjmandi Rafsanjani ◽  
Gholamreza Bahoush
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Medication Errors ◽  
Clinical Decision Support ◽  
Safety Information ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Order Entry ◽  
Computerized Provider Order Entry ◽  
Physician Order Entry

Objective: Chemotherapy medication errors are catastrophic. The prescription phase in the chemotherapy process plays a key role in the creation of medication errors, and therefore the use of computerized physician order entry (CPOE) and clinical decision support system (CDS) systems is recommended to reduce chemotherapy medication errors. The purpose of this study was to carry out a systematic review on the specifications of the CPOE and CDS systems for chemotherapy prescription. Materials and Methods: A systematic review on articles published in English up to September 22, 2017, using the 3 databases PubMed, Embase, and Medline was conducted. Those articles that focused on the specifications of CPOE and CDSS in chemotherapy prescription were included in this review. Findings: Of the 2,471 articles identified, 58 articles met the inclusion criteria and were included in this study. Specifications related to chemotherapy CPOE systems were categorized into the following 6 groups: automation and facilitation of the chemotherapy prescription phase, hospital workflow support, documentation and reporting, drug safety, information security, and system communications. The specifications of chemotherapy CDSS were also divided into 4 categories: embedding chemotherapy protocols, automated dose calculations and adjustment, providing alerts/reminders at the time of prescribing, and guiding or asking the user to complete the important prescription parameters. In 12 articles, the chemotherapy prescription CDSS were designed and evaluated independently of the CPOE; 45 articles provided prescription chemotherapy CDSS as part of the CPOE system, and in 1 article CPOE was introduced with no CDSS. Conclusion: In complicated settings such as chemotherapy, simplification of the processes is more imperative. The use of chemotherapy CPOE, which includes specifications for helping the medical staff with their workload, encourages the professionals to use such systems and increases the likelihood for success of these systems.

scholarly journals Impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay, and mortality in intensive care units: a systematic review and meta-analysis

2016 ◽  
Vol 24 (2) ◽  
pp. 413-422 ◽  
Author(s):  
Mirela Prgomet ◽  
Ling Li ◽  
Zahra Niazkhani ◽  
Andrew Georgiou ◽  
Johanna I Westbrook
Keyword(s):  
Systematic Review ◽  
Intensive Care ◽  
Medication Errors ◽  
Meta Analysis ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Order Entry ◽  
Icu Mortality ◽  
Computerized Provider Order Entry ◽  
The Impact

Objective: To conduct a systematic review and meta-analysis of the impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay (LOS), and mortality in intensive care units (ICUs). Methods: We searched for English-language literature published between January 2000 and January 2016 using Medline, Embase, and CINAHL. Titles and abstracts of 586 unique citations were screened. Studies were included if they: (1) reported results for an ICU population; (2) evaluated the impact of CPOE or the addition of CDSSs to an existing CPOE system; (3) reported quantitative data on medication errors, ICU LOS, hospital LOS, ICU mortality, and/or hospital mortality; and (4) used a randomized controlled trial or quasi-experimental study design. Results: Twenty studies met our inclusion criteria. The transition from paper-based ordering to commercial CPOE systems in ICUs was associated with an 85% reduction in medication prescribing error rates and a 12% reduction in ICU mortality rates. Overall meta-analyses of LOS and hospital mortality did not demonstrate a significant change. Discussion and Conclusion: Critical care settings, both adult and pediatric, involve unique complexities, making them vulnerable to medication errors and adverse patient outcomes. The currently limited evidence base requires research that has sufficient statistical power to identify the true effect of CPOE implementation. There is also a critical need to understand the nature of errors arising post-CPOE and how the addition of CDSSs can be used to provide greater benefit to delivering safe and effective patient care.

scholarly journals A systematic analysis of the optimization of computerized physician order entry and clinical decision support systems: A qualitative study in English hospitals

2019 ◽  
Vol 26 (2) ◽  
pp. 1118-1132 ◽  
Author(s):  
Valeri Wiegel ◽  
Abby King ◽  
Hajar Mozaffar ◽  
Kathrin Cresswell ◽  
Robin Williams ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision Support Systems ◽  
Extended Period ◽  
Clinical Decision ◽  
System Optimization ◽  
Computerized Physician Order Entry ◽  
Order Entry ◽  
Systematic Analysis ◽  
Physician Order Entry

This article analyzes the range of system optimization activities taking place over an extended period following the implementation of computerized physician order entry and clinical decision support systems. We undertook 207 qualitative semi-structured interviews, 24 rounds of non-participant observations of meetings and system use, and collected 17 organizational documents in five hospitals over three time periods between 2011 and 2016. We developed a systematic analysis of system optimization activities with eight sub-categories grouped into three main categories. This delineates the range of system optimization activities including resolving misalignments between technology and clinical practices, enhancing the adopted system, and improving user capabilities to utilize/further optimize systems. This study highlights the optimization efforts by user organizations adopting multi-user, organization-spanning information technologies. Hospitals must continue to attend to change management for an extended period (up to 5 years post-implementation) and develop a strategy for long-term system optimization including sustained user engagement, training, and broader capability development to ensure smoother and quicker realization of benefits.

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 A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care

2016 ◽  
Vol 24 (2) ◽  
pp. 432-440 ◽  
Author(s):  
Clare L Brown ◽  
Helen L Mulcaster ◽  
Katherine L Triffitt ◽  
Dean F Sittig ◽  
Joan S Ash ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Error Rates ◽  
Free Text ◽  
Prescribing Errors ◽  
Order Entry ◽  
Computerized Provider Order Entry ◽  
Computer Screen

Objective: To understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems. Materials and Methods: We conducted a systematic review of the literature published between January 2004 and June 2015 using three large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Studies that reported qualitative data about the types and causes of these errors were included. A narrative synthesis of all eligible studies was undertaken. Results: A total of 1185 publications were identified, of which 34 were included in the review. We identified 8 key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, nonintuitive or inflexible ordering, repeat prescriptions and automated processes, users’ work processes, and clinical decision support systems. Displaying an incomplete list of a patient’s medications on the computer screen often contributed to prescribing errors. Lack of system flexibility resulted in users employing error-prone workarounds, such as the addition of contradictory free-text comments. Users’ misinterpretations of how text was presented in CPOE systems were also linked with the occurrence of prescribing errors. Discussion and Conclusions: Human factors design is important to reduce error rates. Drop-down menus should be designed with safeguards to decrease the likelihood of selection errors. Development of more sophisticated clinical decision support, which can perform checks on free-text, may also prevent errors. Further research is needed to ensure that systems minimize error likelihood and meet users’ workflow expectations.

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