Case Not Closed: Prescription Errors 12 Years after Computerized Physician Order Entry Implementation

Kadmon, Gili; Pinchover, Michal; Weissbach, Avichai; Hazan, Shirley Kogan; Nahum, Elhanan

doi:10.1016/j.jpeds.2017.08.013

Cited by 15 publications

(17 citation statements)

References 30 publications

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“…Also, inappropriate use of the free-text field (caused by duplication or discrepancies between the structured template and the free-text comments) was another common type of CPOE-related errors and was accounted for 14.4 percent. In a study by Kadmon et al, 31 the authors estimated that 42-58 percent of all MEs were facilitated by CPOE implementation (1.8% and 0.4% of all prescriptions in 2015 and 2016, respectively). In another study that was conducted to quantify medication incidents related to electronic medication management systems (eMMS), a total of 93 of 5826 medication-related incidents were reported over a 3-month period (May-July 2014).…”

Section: Cpoe-related Mes: Rates and Statisticsmentioning

confidence: 99%

Computerized provider order entry–related medication errors among hospitalized patients: An integrative review

Elshayib

Pawola

2020

Health Informatics J

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The Institute of Medicine estimates that 7,000 lives are lost yearly as a result of medication errors. Computerized physician and/or provider order entry was one of the proposed solutions to overcome this tragic issue. Despite some promising data about its effectiveness, it has been found that computerized provider order entry may facilitate medication errors. The purpose of this review is to summarize current evidence of computerized provider order entry -related medication errors and address the sociotechnical factors impacting the safe use of computerized provider order entry. By using PubMed and Google Scholar databases, a systematic search was conducted for articles published in English between 2007 and 2019 regarding the unintended consequences of computerized provider order entry and its related medication errors. A total of 288 articles were screened and categorized based on their use within the review. One hundred six articles met our pre-defined inclusion criteria and were read in full, in addition to another 27 articles obtained from references. All included articles were classified into the following categories: rates and statistics on computerized provider order entry -related medication errors, types of computerized provider order entry -related unintended consequences, factors contributing to computerized provider order entry failure, and recommendations based on addressing sociotechnical factors. Identifying major types of computerized provider order entry -related unintended consequences and addressing their causes can help in developing appropriate strategies for safe and effective computerized provider order entry. The interplay between social and technical factors can largely affect its safe implementation and use. This review discusses several factors associated with the unintended consequences of this technology in healthcare settings and presents recommendations for enhancing its effectiveness and safety within the context of sociotechnical factors.

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Section: Cpoe-related Mes: Rates and Statisticsmentioning

confidence: 99%

Computerized provider order entry–related medication errors among hospitalized patients: An integrative review

Elshayib

Pawola

2020

Health Informatics J

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“…35 Hospital electronic prescribing/CPOE systems are diverse, with local implementation and system maintenance strongly affecting performance. 21,36 Some studies have reported significant error reductions in PICU: both Potts et al and Kadmon et al report overall error rate reductions of 39.1 to 1.6%, and 8.2 to 1.4%, respectively on CPOE implementation. 6,37 Substantial differences in system functionality-as discussed below-are likely to explain the contrast between the results and our findings.…”

Section: Discussion Error Ratesmentioning

confidence: 99%

“…37 Eight years later, having reviewed their system due to increasing error rates, further error reductions were identified on addition of weight-based dosing limits and default doses. 36 In ICCA, the inability to set frequency limits and lack of clinical parameter or drug level alerts are likely contributors to the increased antiinfective prescribing error risk identified in Epoch 4 (relative risk: 2.96, 95% confidence interval: 1.39-6.3). Other possible explanations include: mis-selection from standard order dropdown menus, transcribing orders on admission to PICU, obligatory formulation selection, and poor dose-rounding functionality.…”

Section: Error Typesmentioning

confidence: 99%

The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study

et al. 2020

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Background Increased use of health information technology (HIT) has been advocated as a medication error reduction strategy. Evidence of its benefits in the pediatric setting remains limited. In 2012, electronic prescribing (ICCA, Philips, United Kingdom) and standard concentration infusions (SCIs)—facilitated by smart-pump technology—were introduced into the pediatric intensive care unit (PICU) of an Irish tertiary-care pediatric hospital. Objective The aim of this study is to assess the impact of the new technology on the rate and severity of PICU prescribing errors and identify technology-generated errors. Methods A retrospective, before and after study design, was employed. Medication orders were reviewed over 24 weeks distributed across four time periods: preimplementation (Epoch 1); postimplementation of SCIs (Epoch 2); immediate postimplementation of electronic prescribing (Epoch 3); and 1 year postimplementation (Epoch 4). Only orders reviewed by a clinical pharmacist were included. Prespecified definitions, multidisciplinary consensus and validated grading methods were utilized. Results A total of 3,356 medication orders for 288 patients were included. Overall error rates were similar in Epoch 1 and 4 (10.2 vs. 9.8%; p = 0.8), but error types differed (p < 0.001). Incomplete and wrong unit errors were eradicated; duplicate orders increased. Dosing errors remained most common. A total of 27% of postimplementation errors were technology-generated. Implementation of SCIs alone was associated with significant reductions in infusion-related prescribing errors (29.0% [Epoch 1] to 14.6% [Epoch 2]; p < 0.001). Further reductions (8.4% [Epoch 4]) were identified after implementation of electronically generated infusion orders. Non-infusion error severity was unchanged (p = 0.13); fewer infusion errors reached the patient (p < 0.01). No errors causing harm were identified. Conclusion The limitations of electronic prescribing in reducing overall prescribing errors in PICU have been demonstrated. The replacement of weight-based infusions with SCIs was associated with significant reductions in infusion prescribing errors. Technology-generated errors were common, highlighting the need for on-going research on HIT implementation in pediatric settings.

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“…A questão da eficiência é complicada pelo uso ao longo prazo, um estudo recente [Kadmon et al 2017] investigou a eficiência uma década após a implementação de um sistema de prescrição eletrônica e concluiu que atualizações periódicas deveriam ser realizadas no sistema para minimizar ou evitar erros.…”

Section: Discussão E Conclusãounclassified

Efetividade dos Sistemas Computadorizados de Prescrição Eletrônica e de Apoio à Decisão sobre os erros de prescrição em Pediatria

Santos¹,

Passos²,

Barbosa³

et al. 2021

Anais Estendidos Do XXI Simpósio Brasileiro De Computação Aplicada À Saúde (SBCAS Estendido 2021)

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Revisão Sistemática com metanálise, até dezembro de 2020. Objetivo comparar incidência de erros de prescrição antes e após introdução de Sistemas de Prescrição Eletrônica associados ou não a Sistemas de Apoio à Decisão em diferentes settings pediátricos. Em dez estudos em UTI a redução em erros de dosagem (um tipo de erro de prescrição) variou de 15% a 30%. Dois estudos com supressão total de erros. Em enfermaria as reduções foram de 36%, 45%, 67% e 74%. A redução foi de 7,4 de erros gerais de prescrição. Evidenciou-se redução de risco de erros de dosagem em pediatria com o uso de sistemas de prescrição eletrônica para UTI, enfermaria e ambulatório.

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Case Not Closed: Prescription Errors 12 Years after Computerized Physician Order Entry Implementation

Cited by 15 publications

References 30 publications

Computerized provider order entry–related medication errors among hospitalized patients: An integrative review

Computerized provider order entry–related medication errors among hospitalized patients: An integrative review

The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study

Efetividade dos Sistemas Computadorizados de Prescrição Eletrônica e de Apoio à Decisão sobre os erros de prescrição em Pediatria

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