Factors contributing to medication errors made when using computerized order entry in pediatrics: a systematic review

Tolley, Clare L.; Forde, Niamh E.; Coffey, Katherine L.; Sittig, Dean F.; Ash, Joan S.; Husband, Andy; Bates, David W.; Slight, Sarah P

doi:10.1093/jamia/ocx124

Cited by 29 publications

(36 citation statements)

References 85 publications

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“…The primary motivation for our redesigned ordering system was the need to more efficiently and effectively capture and display the indication for the prescription. 24 , 25 By doing so, the indications could be both communicated to the pharmacist and likely placed on the patient’s medication bottle label. Doing so could help with patient and caregiver understanding of the medication and thereby potentially improve medication safety through preventing medication mix-ups and aiding adherence.…”

Section: Discussionmentioning

confidence: 99%

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems

et al. 2019

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Key Points Question Is a redesigned electronic prescribing workflow to better support the incorporation of the indication in the outpatient prescribing process associated with reduced errors and improved clinician experience? Findings This quality improvement study compared an indications-based electronic prescribing prototype with that of 2 leading electronic health record vendors and found that the usability of the prototype system substantially outperformed both vendors’ prescribing systems in terms of efficiency, error rate, and satisfaction. Meaning Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way and may be associated with saved time and effort, reduced errors, and increased clinician satisfaction.

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Section: Discussionmentioning

confidence: 99%

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems

et al. 2019

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“…To the best of our knowledge, this is the first study to investigate factors contributing to changes on a broad set of quality, productivity, and safety outcomes during an EHR implementation guided by the results of a large longitudinal evaluation. Although previous studies attempted to identify factors contributing to changes introduced by HIT adoption, they have focused on specific functionality such as CPOE [16] or specific outcomes such as medication errors [17]. The diversity of factors identified indicates that the need for organizational adaptation to take full advantage of new technologies is as important for health care as it is for other services sectors.…”

Section: Discussionmentioning

confidence: 99%

Looking Behind the Curtain: Identifying Factors Contributing to Changes on Care Outcomes During a Large Commercial EHR Implementation

Colicchio

Borbolla

Colicchio

et al. 2019

eGEMs

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Objective: To identify factors contributing to changes on quality, productivity, and safety outcomes during a large commercial electronic health record (EHR) implementation and to guide future research. Methods: We conducted a mixed-methods study assessing the impact of a commercial EHR implementation. The method consisted of a quantitative longitudinal evaluation followed by qualitative semi-structured, in-depth interviews with clinical employees from the same implementation. Fourteen interviews were recorded and transcribed. Three authors independently coded interview narratives and via consensus identified factors contributing to changes on 15 outcomes of quality, productivity, and safety. Results: We identified 14 factors that potentially affected the outcomes previously monitored. Our findings demonstrate that several factors related to the implementation (e.g., incomplete data migration), partially related (e.g., intentional decrease in volume of work), and not related (e.g., health insurance changes) may affect outcomes in different ways. Discussion: This is the first study to investigate factors contributing to changes on a broad set of quality, productivity, and safety outcomes during an EHR implementation guided by the results of a large longitudinal evaluation. The diversity of factors identified indicates that the need for organizational adaptation to take full advantage of new technologies is as important for health care as it is for other services sectors. Conclusions: We recommend continuous identification and monitoring of these factors in future evaluations to hopefully increase our understanding of the full impact of health information technology interventions.

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“…In another systematic review, CPOE was used with pediatrics. The aim of this study was to nd the errors, and the results demonstrated the usefulness of the system [15].…”

Section: Introductionmentioning

confidence: 90%

The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis

Moghadam

Sadoughi

Velayati

et al. 2020

Preprint

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Background: The clinical decision support systems (CDSSs) for prescribing is one of the technologies aimed at improving physician practice performance and patient outcomes by reducing medication prescription errors. This study, thus, was conducted to investigate the effect of various CDSSs on physician practice performance and patient outcomes.Methods: This systematic review was conducted by searching in PubMed, EMBASE, Web of Science, Scopus, and Cochrane Library from 2005 to 2019. Two researchers independently evaluated the studies. Any discrepancies over the eligibility of the studies between the two researchers were then resolved by consulting a third researcher. Finally, we extracted data from the articles. Then, we conducted a meta-analysis based on medication subgroups, CDSS type subgroups, and outcome categories. Also, we presented a narrative form of the findings. In the meantime, we applied random-effects model to estimate the effects of CDSS on patient outcomes and physician practice performance with 95% confidence interval. Q statistics and I2 were then used to measure heterogeneity.Results: Based on the inclusion criteria, 45 studies were considered eligible for the analysis in this review. The CDSS for prescribing medications/COPE were used for various diseases such as cardiovascular diseases, hypertension, diabetes, gastrointestinal and respiratory diseases, AIDS, appendicitis, kidney disease, malaria, high blood potassium, and mental diseases. Meanwhile, other cases such as the concurrent prescription of multiple drugs for patients and its effects on the above-mentioned outcomes were evaluated. The analysis shows that in some cases the application of CDSS provides positive effects on patient outcomes and physician practice performance (std diff in means = 0.114, 95% CI: 0.090 to 0.138). Also, it was statistically significant for outcome groups such as those showing improved outcomes on physician practice performance and patient outcome or both. However, no significant difference was observed between some other cases and conventional methods. We think that this could be due to the disease type, the quantity, and the type of CDSS requirements that influenced the comparison. Overall, all types of CDSSs have positive effects on outcomes including combinational types and other types that only cause messages when appropriate and necessary.Conclusions: Our findings suggest that positive effects of the CDSS can be attributed to factors such as user-friendliness, compliance with clinical guidelines, patient and physician cooperation, integration of electronic health records, CDSS and pharmaceutical systems, consideration of the views of physicians in assessing the importance of CDSS alerts, and the real-time alerts in the prescription.

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Factors contributing to medication errors made when using computerized order entry in pediatrics: a systematic review

Abstract: This review highlights 5 key factors that contributed to the occurrence of CPOE-related medication errors in pediatrics. Dosing support is the most important. More advanced clinical decision support that can suggest doses based on the drug indication is needed.

Cited by 29 publications

References 85 publications

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems

Looking Behind the Curtain: Identifying Factors Contributing to Changes on Care Outcomes During a Large Commercial EHR Implementation

The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis

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Factors contributing to medication errors made when using computerized order entry in pediatrics: a systematic review

Abstract: This review highlights 5 key factors that contributed to the occurrence of CPOE-related medication errors in pediatrics. Dosing support is the most important. More advanced clinical decision support that can suggest doses based on the drug indication is needed.

Cited by 29 publications

References 85 publications

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems

Looking Behind the Curtain: Identifying Factors Contributing to Changes on Care Outcomes During a Large Commercial EHR Implementation

­The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis

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The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis