scholarly journals Inpatient verbal orders and the impact of computerized provider order entry

2006 ◽  
Vol 149 (4) ◽  
pp. A2
Author(s):  
Thomas P. Green
2010 ◽  
Vol 4 (1) ◽  
pp. 206-213 ◽  
Author(s):  
Zahra Niazkhani ◽  
Habibollah Pirnejad ◽  
Antoinette de Bont ◽  
Jos Aarts

Background: Computerized provider order entry (CPOE) systems are implemented in various clinical contexts of a hospital. To identify the role of the clinical context in CPOE use, we compared the impact of a CPOE system on the medication process in both non-surgical and surgical specialties. Methods: We conducted a qualitative study of surgical and non-surgical specialties in a 1237-bed, academic hospital in the Netherlands. We interviewed the clinical end users of a computerized medication order entry system in both specialty types and analyzed the interview transcripts to elicit qualitative differences between the clinical contexts, clinicians’ attitudes, and specialty-specific requirements. Results: Our study showed that the differences in clinical contexts between non-surgical and surgical specialties resulted in a disparity between clinicians’ requirements when using CPOE. Non-surgical specialties had a greater medication workload, greater and more diverse information needs to be supported in a timely manner by the system, and thus more intensive interaction with the CPOE system. In turn these factors collectively influenced the perceived impact of the CPOE system on the clinicians’ practice. The non-surgical clinicians expressed less positive attitudes compared to the surgical clinicians, who perceived their interaction with the system to be less intensive and less problematic. Conclusion: Our study shows that clinicians’ different attitudes towards the system and the perceived impact of the system were largely grounded in the clinical context of the units. The study suggests that not merely the CPOE system, the technology itself, influences the perceptions of its users and workflow-related outcomes. The interplay between technology and clinical context of the implementation environment also matters. System design and redesigning efforts should take account of different units’ specific requirements in their particular clinical contexts.


CJEM ◽  
2016 ◽  
Vol 18 (4) ◽  
pp. 264-269 ◽  
Author(s):  
Andrew Gray ◽  
Christopher M.B. Fernandes ◽  
Kristine Van Aarsen ◽  
Melanie Columbus

AbstractObjectivesComputerized provider order entry (CPOE) has been established as a method to improve patient safety by avoiding medication errors; however, its effect on emergency department (ED) flow remains undefined. We examined the impact of CPOE implementation on three measures of ED throughput: wait time (WT), length of stay (LOS), and the proportion of patients that left without being seen (LWBS).MethodsWe conducted a retrospective cohort study of all ED patients of 18 years and older presenting to London Health Sciences Centre during July and August 2013 and 2014, before and after implementation of a CPOE system. The three primary variables were compared between time periods. Subgroup analyses were also conducted within each Canadian Triage and Acuity Scale (CTAS) level (1–5) individually, as well as for admitted patients only.ResultsA significant increase in WT of 5 minutes (p=0.036) and LOS of 10 minutes (p=0.001), and an increase in LWBS from 7.2% to 8.1% (p=0.002) was seen after CPOE implementation. Admitted patients’ LOS increased by 63 minutes (p<0.001), the WT of CTAS 3 and 5 patients increased by 6 minutes (p=0.001) and 39 minutes (p=0.005), and LWBS proportion increased significantly for CTAS 3–5 patients, from 24.3% to 42.0% (p<0.001) for CTAS 5 patients specifically.ConclusionsCPOE implementation detrimentally impacted all patient flow throughput measures that we examined. The most striking clinically relevant result was the increase in LOS of 63 minutes for admitted patients. This raises the question as to whether the potential detrimental effects to patient safety of CPOE implementation outweigh its benefits.


2010 ◽  
Vol 17 (1) ◽  
pp. 78-84 ◽  
Author(s):  
Emily Beth Devine ◽  
Ryan N Hansen ◽  
Jennifer L Wilson-Norton ◽  
N M Lawless ◽  
Albert W Fisk ◽  
...  

2016 ◽  
Vol 24 (2) ◽  
pp. 413-422 ◽  
Author(s):  
Mirela Prgomet ◽  
Ling Li ◽  
Zahra Niazkhani ◽  
Andrew Georgiou ◽  
Johanna I Westbrook

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.


Healthcare ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1187
Author(s):  
Jungwon Cho ◽  
Sangmi Shin ◽  
Youngmi Jeong ◽  
Eunsook Lee ◽  
Soyeon Ahn ◽  
...  

Evaluation of sustainability after quality improvement (QI) projects in healthcare settings is an essential part of monitoring and future QI planning. With limitations in adopting quasi-experimental study design in real-world practice, healthcare professionals find it challenging to present the sustained effect of QI changes effectively. To provide quantitative methodological approaches for demonstrating the sustainability of QI projects for healthcare professionals, we conducted data analyses based on a QI project to improve the computerized provider order entry system to reduce patients’ dosing frequencies in Korea. Data were collected for 5 years: 24-month pre-intervention, 12-month intervention, and 24-month post-intervention. Then, analytic approaches including control chart, Analysis of Variance (ANOVA), and segmented regression were performed. The control chart intuitively displayed how the outcomes changed over the entire period, and ANOVA was used to test whether the outcomes differed between groups. Last, segmented regression analysis was conducted to evaluate longitudinal effects of interventions over time. We found that the impact of QI projects in healthcare settings should be initiated following the Plan–Do–Study–Act cycle and evaluated long-term effects while widening the scope of QI evaluation with sustainability. This study can serve as a guide for healthcare professionals to use a number of statistical methodologies in their QI evaluations.


2011 ◽  
Vol 18 (3) ◽  
pp. 335-340 ◽  
Author(s):  
Andrew Georgiou ◽  
Mirela Prgomet ◽  
Andrew Markewycz ◽  
Edwina Adams ◽  
Johanna I Westbrook

Author(s):  
Swaminathan Kandaswamy ◽  
Aaron Z Hettinger ◽  
Raj M. Ratwani

Computerized Provider Order Entry (CPOE) is a critical component of electronic health records (EHR). Although widely adopted, the usability of these systems is not well understood. A cross-sectional usability study was conducted at four healthcare systems using two commercially available EHRs. This research aims to predict the accuracy of an order placed in the EHR by emergency medicine physicians. Physician-EHR interactions were recorded during six simulated task scenarios in a test environment. The data from 222 interactions were used to predict the accuracy of the order placed. Multiple models were developed, and their performance was compared. The Random Forest model had the best performance with F1 score 0.82 and AUC of 0.89. These results demonstrate the utility of using keystroke, time and user demographics as variables in predicting accurate order placement. Applying such models to passively monitor EHR usage in real world clinical environments may help improve patient safety and care.


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