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Objectives: To compare medication errors identified at audit and via direct observation with medication errors reported to an incident reporting system at paediatric hospitals and to investigate differences in types and severity of errors detected and reported by staff., Methods: This is a comparison study at two tertiary referral paediatric hospitals between 2016 and 2020 in Australia. Prescribing errors were identified from a medication chart audit of 7785 patient records. Medication administration errors were identified from a prospective direct observational study of 5137 medication administration doses to 1530 patients. Medication errors reported to the hospitals' incident reporting system were identified and matched with errors identified at audit and observation., Results: Of 11 302 clinical prescribing errors identified at audit, 3.2 per 1000 errors (95% CI 2.3 to 4.4, n=36) had an incident report. Of 2224 potentially serious prescribing errors from audit, 26.1% (95% CI 24.3 to 27.9, n=580) were detected by staff and 11.2 per 1000 errors (95% CI 7.6 to 16.5, n=25) were reported to the incident system. Although the prescribing error detection rates varied between the two hospitals, there was no difference in incident reporting rates regardless of error severity. Of 40 errors associated with actual patient harm, only 7 (17.5%; 95% CI 8.7% to 31.9%) were detected by staff and 4 (10.0%; 95% CI 4.0% to 23.1%) had an incident report. None of the 2883 clinical medication administration errors observed, including 903 potentially serious errors and 144 errors associated with actual patient harm, had incident reports., Conclusion: Incident reporting data do not provide an accurate reflection of medication errors and related harm to children in hospitals. Failure to detect medication errors is likely to be a significant contributor to low error reporting rates. In an era of electronic health records, new automated approaches to monitor medication safety should be pursued to provide real-time monitoring., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: The objective of this study was to examine associations between patient age and medication errors among pediatric inpatients., Study Design: Secondary analysis of data sets generated from 2 tertiary pediatric hospitals: (1) prescribing errors identified from chart reviews for patients on 9 general wards at hospital A during April 22 to July 10, 2016, June 20 to September 20, 2017, and June 20 to September 30, 2020; prescribing errors from 5 wards at hospital B in the same periods and (2) medication administration errors assessed by direct prospective observation of 5137 administrations on 9 wards at hospital A. Multilevel models examined the association between patient age and medication errors. Age was modeled using restricted cubic splines to allow for nonlinearity., Results: Prescribing errors increased nonlinearly with patient age (P = .01), showing little association from ages 0 to 3 years and then increasing with age until around 10 years and remaining constant through the teenage years. Administration errors increased with patient age, with no association from 0 to around 8 years and then a steady rise with increasing age (P = .03). The association differed by route: linear for oral, no association for intravenous infusions, and U-shaped for intravenous injections., Conclusions: Older age is an unrecognized risk factor for medication error on general wards in pediatric hospitals. Contributors to risk may be the clinical profiles of these older children or the general level of attention paid to medication practices for this group. Further investigation may allow the design of more targeted interventions to reduce errors., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest relevant to this article to disclose. This research was funded by a National Health and Medical Research Council (NHMRC) partnership project grant with the Sydney Children's Hospital Network (1094878). Johanna Westbrook holds an NHMRC Leadership Investigator Grant (1174021), and Magdalena Raban holds an NHMRC Early Career Fellowship (1143941)., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Aims: The potential harm associated with medication errors is widely reported, but data on actual harm are limited. When actual harm has been measured, assessment processes are often poorly described, limiting their ability to be reproduced by other studies. Our aim was to design and implement a new process to assess actual harm resulting from medication errors in paediatric inpatient care., Methods: Prescribing errors were identified through retrospective medical record reviews (n = 26 369 orders) and medication administration errors through direct observation (n = 5137 administrations) in a tertiary paediatric hospital. All errors were assigned potential harm severity ratings on a 5-point scale. Multidisciplinary panels reviewed case studies for patients assigned the highest three potential severity ratings and determined the following: actual harm occurrence and severity level, plausibility of a link between the error(s) and identified harm(s) and a confidence rating if no harm had occurred., Results: Multidisciplinary harm panels (n = 28) reviewed 566 case studies (173 prescribing related and 393 administration related) and found evidence of actual harm in 89 (prescribing = 22, administration = 67). Eight cases of serious harm cases were found (prescribing = 1, administration = 7) and no cases of severe harm. The panels were very confident in 65% of cases (n = 302) where no harm was found. Potential and actual harm ratings varied., Conclusions: This harm assessment process provides a systematic method for determining actual harm from medication errors. The multidisciplinary nature of the panels was critical in evaluating specific clinical, therapeutic and contextual considerations including care delivery pathways, therapeutic dose ranges and drug-drug and drug-disease interactions., (© 2024 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Introduction: Limited evidence exists regarding medication administration errors (MAEs) on general paediatric wards or associated risk factors exists., Objective: The aim of this study was to identify nurse, medication, and work-environment factors associated with MAEs among paediatric inpatients., Methods: This was a prospective, direct observational study of 298 nurses in a paediatric referral hospital in Sydney, Australia. Trained observers recorded details of 5137 doses prepared and administered to 1530 children between 07:00 h and 22:00 h on weekdays and weekends. Observation data were compared with medication charts to identify errors. Clinical errors, potential severity and actual harm were assessed. Nurse characteristics (e.g. age, sex, experience), medication type (route, high-risk medications, use of solvent/diluent), and work variables (e.g. time of administration, weekday/weekend, use of an electronic medication management system [eMM], presence of a parent/carer) were collected. Multivariable models assessed MAE risk factors for any error, errors by route, potentially serious errors, and errors involving high-risk medication or causing actual harm., Results: Errors occurred in 37.0% (n = 1899; 95% confidence interval [CI] 35.7-38.3) of administrations, 25.8% (n = 489; 95% CI 23.8-27.9) of which were rated as potentially serious. Intravenous infusions and injections had high error rates (64.7% [n = 514], 95% CI 61.3-68.0; and 77.4% [n = 188], 95% CI 71.7-82.2, respectively). For intravenous injections, 59.7% (95% CI 53.4-65.6) had potentially serious errors. No nurse characteristics were associated with MAEs. Intravenous route, early morning and weekend administrations, patient age ≥ 11 years, oral medications requiring solvents/diluents and eMM use were all significant risk factors. MAEs causing actual harm were 45% lower using an eMM compared with paper charts., Conclusion: Medication error prevention strategies should target intravenous administrations and not neglect older children in hospital. Attention to nurses' work environments, including improved design and integration of medication technologies, is warranted., (© 2024. The Author(s).)

Objective: To conduct a systematic review and meta-analysis to assess: 1) changes in medication error rates and associated patient harm following electronic medication system (EMS) implementation; and 2) evidence of system-related medication errors facilitated by the use of an EMS., Materials and Methods: We searched Medline, Scopus, Embase, and CINAHL for studies published between January 2005 and March 2019, comparing medication errors rates with or without assessments of related harm (actual or potential) before and after EMS implementation. EMS was defined as a computer-based system enabling the prescribing, supply, and/or administration of medicines. Study quality was assessed., Results: There was substantial heterogeneity in outcomes of the 18 included studies. Only 2 were strong quality. Meta-analysis of 5 studies reporting change in actual harm post-EMS showed no reduced risk (RR: 1.22, 95% CI: 0.18-8.38, P = .8) and meta-analysis of 3 studies reporting change in administration errors found a significant reduction in error rates (RR: 0.77, 95% CI: 0.72-0.83, P = .004). Of 10 studies of prescribing error rates, 9 reported a reduction but variable denominators precluded meta-analysis. Twelve studies provided specific examples of system-related medication errors; 5 quantified their occurrence., Discussion and Conclusion: Despite the wide-scale adoption of EMS in hospitals around the world, the quality of evidence about their effectiveness in medication error and associated harm reduction is variable. Some confidence can be placed in the ability of systems to reduce prescribing error rates. However, much is still unknown about mechanisms which may be most effective in improving medication safety and design features which facilitate new error risks., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Introduction: The risk of medication errors is high in paediatric inpatient settings. However, estimates of the prevalence of medication errors have not accounted for heterogeneity across studies in error identification methods and definitions, nor contextual differences across wards and the use of electronic or paper medication charts., Objective: Our aim was to conduct a systematic review and meta-analysis to provide separate estimates of the prevalence of medication errors among paediatric inpatients, depending on hospital ward and the use of electronic or paper medication charts, that address differences in error identification methods and definitions., Methods: We systematically searched five databases to identify studies published between January 2000 and December 2018 that assessed medication error rates by medication chart audit, direct observation or a combination of methods., Results: We identified 71 studies, 19 involved paediatric wards using electronic charts. Most studies assessed prescribing errors with few studies assessing administration errors. Estimates varied by ward type. Studies of paediatric wards using electronic charts generally reported a reduced error prevalence compared to those using paper, although there were some inconsistencies. Error detection methods impacted the rate of administration errors in studies of multiple wards, however, no other difference was found. Definition of medication error did not have a consistent impact on reported error rates., Conclusions: Medication errors are a frequent occurrence in paediatric inpatient settings, particularly in intensive care wards and emergency departments. Hospitals using electronic charts tended to have a lower rate of medication errors compared to those using paper charts. Future research employing controlled designs is needed to determine the true impact of electronic charts and other interventions on medication errors and associated harm among hospitalized children.

Classifying harm associated with a medication error can be time consuming and labour intensive and limited studies undertake this step. There is no standardised process, and few studies that report harm assessment provide adequate methods to allow for study replication. Studies typically mention that a clinical review panel classified patient harm and provide a reference to a classification tool. Moreover, in many studies it is unclear whether potential or actual harm was classified as studies refer only to 'error severity'. The tools used to categorise the severity of patient harm vary widely across studies and few have been assessed for inter-rater reliability and criterion validity. In this paper, we describe the systematic process we undertook to synthesise the defining elements and strengths, while mitigating the limitations, of existing harm classification tools to derive the Harm Associated with Medication Error Classification (HAMEC). This new tool provides a harm classification for use across clinical and research settings. The provision of an explicit process for its application and guiding category descriptors are designed to reduce the risk of misclassification and produce results that are comparable across studies. As the World Health Organisation embarks on its international safety challenge of reducing medication-related harm by 50%, accompanying methodological advances are required to measure progress.

Background: Interruptions and multitasking have been demonstrated in experimental studies to reduce individuals' task performance. These behaviours are frequently used by clinicians in high-workload, dynamic clinical environments, yet their effects have rarely been studied., Objective: To assess the relative contributions of interruptions and multitasking by emergency physicians to prescribing errors., Methods: 36 emergency physicians were shadowed over 120 hours. All tasks, interruptions and instances of multitasking were recorded. Physicians' working memory capacity (WMC) and preference for multitasking were assessed using the Operation Span Task (OSPAN) and Inventory of Polychronic Values. Following observation, physicians were asked about their sleep in the previous 24 hours. Prescribing errors were used as a measure of task performance. We performed multivariate analysis of prescribing error rates to determine associations with interruptions and multitasking, also considering physician seniority, age, psychometric measures, workload and sleep., Results: Physicians experienced 7.9 interruptions/hour. 28 clinicians were observed prescribing 239 medication orders which contained 208 prescribing errors. While prescribing, clinicians were interrupted 9.4 times/hour. Error rates increased significantly if physicians were interrupted (rate ratio (RR) 2.82; 95% CI 1.23 to 6.49) or multitasked (RR 1.86; 95% CI 1.35 to 2.56) while prescribing. Having below-average sleep showed a >15-fold increase in clinical error rate (RR 16.44; 95% CI 4.84 to 55.81). WMC was protective against errors; for every 10-point increase on the 75-point OSPAN, a 19% decrease in prescribing errors was observed. There was no effect of polychronicity, workload, physician gender or above-average sleep on error rates., Conclusion: Interruptions, multitasking and poor sleep were associated with significantly increased rates of prescribing errors among emergency physicians. WMC mitigated the negative influence of these factors to an extent. These results confirm experimental findings in other fields and raise questions about the acceptability of the high rates of multitasking and interruption in clinical environments., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Background: Clinical decision support (CDS) in e-prescribing can improve safety by alerting potential errors, but introduces new sources of risk. Automation bias (AB) occurs when users over-rely on CDS, reducing vigilance in information seeking and processing. Evidence of AB has been found in other clinical tasks, but has not yet been tested with e-prescribing. This study tests for the presence of AB in e-prescribing and the impact of task complexity and interruptions on AB., Methods: One hundred and twenty students in the final two years of a medical degree prescribed medicines for nine clinical scenarios using a simulated e-prescribing system. Quality of CDS (correct, incorrect and no CDS) and task complexity (low, low + interruption and high) were varied between conditions. Omission errors (failure to detect prescribing errors) and commission errors (acceptance of false positive alerts) were measured., Results: Compared to scenarios with no CDS, correct CDS reduced omission errors by 38.3% (p < .0001, n = 120), 46.6% (p < .0001, n = 70), and 39.2% (p < .0001, n = 120) for low, low + interrupt and high complexity scenarios respectively. Incorrect CDS increased omission errors by 33.3% (p < .0001, n = 120), 24.5% (p < .009, n = 82), and 26.7% (p < .0001, n = 120). Participants made commission errors, 65.8% (p < .0001, n = 120), 53.5% (p < .0001, n = 82), and 51.7% (p < .0001, n = 120). Task complexity and interruptions had no impact on AB., Conclusions: This study found evidence of AB omission and commission errors in e-prescribing. Verification of CDS alerts is key to avoiding AB errors. However, interventions focused on this have had limited success to date. Clinicians should remain vigilant to the risks of CDS failures and verify CDS.

Medication administration errors (MAEs) in hospital are frequent and significantly more likely to result in serious harm to patients than other medication error types. Many interventions have been proposed in order reduce MAEs and the amount of harm associated with these errors. A major limitation in assessing the effectiveness of these interventions has been the lack of robust measures for assessing changes in MAEs and associated harms. Drawing upon extensive foundational research we have developed a robust approach and data collection software to be applied in direct observational studies of nurses to allow measurement of changes in MAE rates. We report how this approach is being applied in a large stepped-wedge cluster randomised controlled trial to assess the effectiveness of an electronic medication management system to reduce MAEs in a paediatric hospital.

Introduction: Interruptions and multitasking are frequent in clinical settings, and have been shown in the cognitive psychology literature to affect performance, increasing the risk of error. However, comparatively less is known about their impact on errors in clinical work. This study will assess the relationship between prescribing errors, interruptions and multitasking in an emergency department (ED) using direct observations and chart review., Methods and Analysis: The study will be conducted in an ED of a 440-bed teaching hospital in Sydney, Australia. Doctors will be shadowed at proximity by observers for 2 h time intervals while they are working on day shift (between 0800 and 1800). Time stamped data on tasks, interruptions and multitasking will be recorded on a handheld computer using the validated Work Observation Method by Activity Timing (WOMBAT) tool. The prompts leading to interruptions and multitasking will also be recorded. When doctors prescribe medication, type of chart and chart sections written on, along with the patient's medical record number (MRN) will be recorded. A clinical pharmacist will access patient records and assess the medication orders for prescribing errors. The prescribing error rate will be calculated per prescribing task and is defined as the number of errors divided by the number of medication orders written during the prescribing task. The association between prescribing error rates, and rates of prompts, interruptions and multitasking will be assessed using statistical modelling., Ethics and Dissemination: Ethics approval has been obtained from the hospital research ethics committee. Eligible doctors will be provided with written information sheets and written consent will be obtained if they agree to participate. Doctor details and MRNs will be kept separate from the data on prescribing errors, and will not appear in the final data set for analysis. Study results will be disseminated in publications and feedback to the ED., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Background: Medication administration errors are frequent and lead to patient harm. Interruptions during medication administration have been implicated as a potential contributory factor., Objective: To assess evidence of the effectiveness of interventions aimed at reducing interruptions during medication administration on interruption and medication administration error rates., Methods: In September 2012 we searched MEDLINE, EMBASE, CINAHL, PsycINFO, Cochrane Effective Practice and Organisation of Care Group reviews, Google and Google Scholar, and hand searched references of included articles. Intervention studies reporting quantitative data based on direct observations of at least one outcome (interruptions, or medication administration errors) were included., Results: Ten studies, eight from North America and two from Europe, met the inclusion criteria. Five measured significant changes in interruption rates pre and post interventions. Four found a significant reduction and one an increase. Three studies measured changes in medication administration error rates and showed reductions, but all implemented multiple interventions beyond those targeted at reducing interruptions. No study used a controlled design pre and post. Definitions for key outcome indicators were reported in only four studies. Only one study reported κ scores for inter-rater reliability and none of the multi-ward studies accounted for clustering in their analyses., Conclusions: There is weak evidence of the effectiveness of interventions to significantly reduce interruption rates and very limited evidence of their effectiveness to reduce medication administration errors. Policy makers should proceed with great caution in implementing such interventions until controlled trials confirm their value. Research is also required to better understand the complex relationship between interruptions and error to support intervention design.

Electronic medication management (eMM) systems are designed to improve safety, but there is little evidence of their effectiveness in paediatrics. This study assesses the short-term (first 70 days of eMM use) and long-term (one-year) effectiveness of an eMM system to reduce prescribing errors, and their potential and actual harm. We use a stepped-wedge cluster randomised controlled trial (SWCRCT) at a paediatric referral hospital, with eight clusters randomised for eMM implementation. We assess long-term effects from an additional random sample of medication orders one-year post-eMM. In the SWCRCT, errors that are potential adverse drug events (ADEs) are assessed for actual harm. The study comprises 35,260 medication orders for 4821 patients. Results show no significant change in overall prescribing error rates in the first 70 days of eMM use (incident rate ratio [IRR] 1.05 [95%CI 0.92–1.21], but a 62% increase (IRR 1.62 [95%CI 1.28–2.04]) in potential ADEs suggesting immediate risks to safety. One-year post-eMM, errors decline by 36% (IRR 0.64 [95%CI 0.56–0.72]) and high-risk medication errors decrease by 33% (IRR 0.67 [95%CI 0.51–0.88]) compared to pre-eMM. In all periods, dose error rates are more than double that of other error types. Few errors are associated with actual harm, but 71% [95%CI 50–86%] of patients with harm experienced a dose error. In the short-term, eMM implementation shows no improvement in error rates, and an increase in some errors. A year after eMM error rates significantly decline suggesting long-term benefits. eMM optimisation should focus on reducing dose errors due to their high frequency and capacity to cause harm. [ABSTRACT FROM AUTHOR]

Background Double-checking the administration of medications has been standard practice in paediatric hospitals around the world for decades. While the practice is widespread, evidence of its effectiveness in reducing errors or harm is scarce. Objectives To measure the association between double-checking, and the occurrence and potential severity of medication administration errors (MAEs); check duration; and factors associated with doublechecking adherence. Methods Direct observational study of 298 nurses, administering 5140 medication doses to 1523 patients, across nine wards, in a paediatric hospital. Independent observers recorded details of administrations and double-checking (independent; primed--one nurse shares information which may influence the checking nurse; incomplete; or none) in real time during weekdays and weekends between 07:00 and 22:00. Observational medication data were compared with patients' medical records by a reviewer (blinded to checking-status), to identify MAEs. MAEs were rated for potential severity. Observations included administrations where double-checking was mandated, or optional. Multivariable regression examined the association between doublechecking, MAEs and potential severity; and factors associated with policy adherence. Results For 3563 administrations double-checking was mandated. Of these, 36 (1.0%) received independent double-checks, 3296 (92.5%) primed and 231 (6.5%) no/incomplete double-checks. For 1577 administrations double-checking was not mandatory, but in 26.3% (n=416) nurses chose to double-check. Where double-checking was mandated there was no significant association between double-checking and MAEs (OR 0.89 (0.65-1.21); p=0.44), or potential MAE severity (OR 0.86 (0.65-1.15); p=0.31). Where double-checking was not mandated, but performed, MAEs were less likely to occur (OR 0.71 (0.54-0.95); p=0.02) and had lower potential severity (OR 0.75 (0.57-0.99); p=0.04). Each double-check took an average of 6.4 min (107 hours/1000 administrations). Conclusions Compliance with mandated double-checking was very high, but rarely independent. Primed double-checking was highly prevalent but compared with single-checking conferred no benefit in terms of reduced errors or severity. Our findings raise questions about if, when and how double-checking policies deliver safety benefits and warrant the considerable resource investments required in modern clinical settings. [ABSTRACT FROM AUTHOR]

Medication prescribing in paediatrics is complex and compounded by the need to provide age and weight related doses, and errors continue to be problematic. Electronic medication systems (EMS) can reduce errors through dosing calculators and computerised decision support. However, evidence on costs and benefits of these systems is limited, particularly in paediatric hospitals. This paper presents the development of a cost-benefit analysis (CBA) framework to assess the impact of an EMS implementation in a paediatric tertiary hospital. An innovative component of the framework is the incorporation of the impact of the effects of the EMS for both the health system as well as for patients and their wider family networks, allowing a net social benefit assessment. We describe the impact of non-clinical out-of-pocket costs of admission and use discrete choice experiments to measure both medication related harm and the importance of medication safety to families and members of the community. [ABSTRACT FROM AUTHOR]

The implementation of computerised prescribing can result in large reductions in prescribing error rates. The flow-on effects to patient outcomes are not well studied. The reduction in errors is dependent on prescribers becoming proficient in using the electronic prescribing system. All potential safety benefits are therefore not expected to be achieved immediately. Electronic prescribing systems introduce new types of errors, most frequently errors in selection. Some of these errors can be prevented if the system is well designed. Computerised decision support embedded in electronic prescribing systems has enormous potential to improve medication safety. However, current support systems have a limited capacity to provide context-relevant advice to prescribers. [ABSTRACT FROM AUTHOR]