Dataset Information

Use of Pediatric Injectable Medicines Guidelines and Associated Medication Administration Errors: A Human Reliability Analysis.

ABSTRACT:

Background

In a recent human reliability analysis (HRA) of simulated pediatric resuscitations, ineffective retrieval of preparation and administration instructions from online injectable medicines guidelines was a key factor contributing to medication administration errors (MAEs).

Objective

The aim of the present study was to use a specific HRA to understand where intravenous medicines guidelines are vulnerable to misinterpretation, focusing on deviations from expected practice (discrepancies) that contributed to large-magnitude and/or clinically significant MAEs.

Methods

Video recordings from the original study were reanalyzed to identify discrepancies in the steps required to find and extract information from the NHS Injectable Medicines Guide (IMG) website. These data were combined with MAE data from the same original study.

Results

In total, 44 discrepancies during use of the IMG were observed across 180 medication administrations. Of these discrepancies, 21 (48%) were associated with an MAE, 16 of which (36% of 44 discrepancies) made a major contribution to that error. There were more discrepancies (31 in total, 70%) during the steps required to access the correct drug webpage than there were in the steps required to read this information (13 in total, 30%). Discrepancies when using injectable medicines guidelines made a major contribution to 6 (27%) of 22 clinically significant and 4 (15%) of 27 large-magnitude MAEs.

Conclusion and relevance

Discrepancies during the use of an online injectable medicines guideline were often associated with subsequent MAEs, including those with potentially significant consequences. This highlights the need to test the usability of guidelines before clinical use.

SUBMITTER: Jones MD

PROVIDER: S-EPMC7611785 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Use of Pediatric Injectable Medicines Guidelines and Associated Medication Administration Errors: A Human Reliability Analysis.

Jones Matthew D MD Clarke Jonathan J Feather Calandra C Franklin Bryony Dean BD Sinha Ruchi R Maconochie Ian I Darzi Ara A Appelbaum Nicholas N

The Annals of pharmacotherapy 20210301 11

<h4>Background</h4>In a recent human reliability analysis (HRA) of simulated pediatric resuscitations, ineffective retrieval of preparation and administration instructions from online injectable medicines guidelines was a key factor contributing to medication administration errors (MAEs).<h4>Objective</h4>The aim of the present study was to use a specific HRA to understand where intravenous medicines guidelines are vulnerable to misinterpretation, focusing on deviations from expected practice (< ...[more]

PMID: 33641479

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Project description:BackgroundLiquid medication dosing errors (LMDE) made by caregivers affect treatment in children, but this is not a well-studied topic in many low-and middle-income countries including in India.MethodsAn intervention study was conducted among mothers attending a pediatric outpatient clinic of a tertiary care setting in Ujjain, India. The mothers randomly measured 12 volumes of a paracetamol liquid preparation by using a dropper (0.5 and 1 mL), measuring cup (2.5 and 5 mL), and calibrated spoon (2.5 and 5 mL) each with two instructions-oral-only measurement session (OMS) and oral plus pictogram measurement session (OPMS, the intervention). The main outcome was dosing error prevalence. The effectiveness of the intervention was assessed by measuring effect size. Risk factors for maximum LMDE were explored using backward multivariate logistic regression models. A P value of < 0.05 was considered statistically significant.ResultsIn total, 310 mothers [mean (± SD) age, 30.2 (± 4.18) years] were included. LMDE prevalence in the OMS versus OPMS for dropper 0.5 mL was 60% versus 48%; for l mL dropper was 63% versus 54%; for 2.5 mL cup 62% versus 54%; for 2.5 calibrated spoon 66% versus 59%; 5 mL cup 69% versus 57%; and 5 mL calibrated spoon 68% versus 55%. Comparing OMS with OPMS, underdosing was minimum with the calibrated spoon for 2.5 mL (OR 4.39) and maximum with the dropper for 1 mL (OR 9.40), and overdosing was minimum with the dropper for 0.5 mL (OR 7.12) and maximum with the calibrated spoon for 2.5 mL (OR 13.24). The effect size (dCohen) of the intervention OPMS was 1.86-6.4. Risk factors for the most prevalent dosing error, that is, with the calibrated spoon for 2.5 mL, were increasing age of the mother (aOR 1.08; P = 0.026) and nuclear family (aOR 2.83; P = 0.002). The risk of dosing errors decreased with higher education of the mothers.ConclusionsPictograms can effectively minimize LMDE even in less educated mothers.

Project description:Introduction: Pediatric patients cared for in professional healthcare settings are at high risk of medication errors. Interventions to improve patient safety often focus on prescribing; however, the subsequent stages in the medication use process (dispensing, drug administration, and monitoring) are also error-prone. This systematic review aims to identify and analyze interventions to reduce dispensing, drug administration, and monitoring errors in professional pediatric healthcare settings. Methods: Four databases were searched for experimental studies with separate control and intervention groups, published in English between 2011 and 2019. Interventions were classified for the first time in pediatric medication safety according to the "hierarchy of controls" model, which predicts that interventions at higher levels are more likely to bring about change. Higher-level interventions aim to reduce risks through elimination, substitution, or engineering controls. Examples of these include the introduction of smart pumps instead of standard pumps (a substitution control) and the introduction of mandatory barcode scanning for drug administration (an engineering control). Administrative controls such as guidelines, warning signs, and educational approaches are lower on the hierarchy and therefore predicted by this model to be less likely to be successful. Results: Twenty studies met the inclusion criteria, including 1 study of dispensing errors, 7 studies of drug administration errors, and 12 studies targeting multiple steps of the medication use process. A total of 44 interventions were identified. Eleven of these were considered higher-level controls (four substitution and seven engineering controls). The majority of interventions (n = 33) were considered "administrative controls" indicating a potential reliance on these measures. Studies that implemented higher-level controls were observed to be more likely to reduce errors, confirming that the hierarchy of controls model may be useful in this setting. Heterogeneous study methods, definitions, and outcome measures meant that a meta-analysis was not appropriate. Conclusions: When designing interventions to reduce pediatric dispensing, drug administration, and monitoring errors, the hierarchy of controls model should be considered, with a focus placed on the introduction of higher-level controls, which may be more likely to reduce errors than the administrative controls often seen in practice. Trial Registration Prospero Identifier: CRD42016047127.

Project description:ObjectiveTo improve neonatal patient safety through automated detection of medication administration errors (MAEs) in high alert medications including narcotics, vasoactive medication, intravenous fluids, parenteral nutrition, and insulin using the electronic health record (EHR); to evaluate rates of MAEs in neonatal care; and to compare the performance of computerized algorithms to traditional incident reporting for error detection.MethodsWe developed novel computerized algorithms to identify MAEs within the EHR of all neonatal patients treated in a level four neonatal intensive care unit (NICU) in 2011 and 2012. We evaluated the rates and types of MAEs identified by the automated algorithms and compared their performance to incident reporting. Performance was evaluated by physician chart review.ResultsIn the combined 2011 and 2012 NICU data sets, the automated algorithms identified MAEs at the following rates: fentanyl, 0.4% (4 errors/1005 fentanyl administration records); morphine, 0.3% (11/4009); dobutamine, 0 (0/10); and milrinone, 0.3% (5/1925). We found higher MAE rates for other vasoactive medications including: dopamine, 11.6% (5/43); epinephrine, 10.0% (289/2890); and vasopressin, 12.8% (54/421). Fluid administration error rates were similar: intravenous fluids, 3.2% (273/8567); parenteral nutrition, 3.2% (649/20124); and lipid administration, 1.3% (203/15227). We also found 13 insulin administration errors with a resulting rate of 2.9% (13/456). MAE rates were higher for medications that were adjusted frequently and fluids administered concurrently. The algorithms identified many previously unidentified errors, demonstrating significantly better sensitivity (82% vs. 5%) and precision (70% vs. 50%) than incident reporting for error recognition.ConclusionsAutomated detection of medication administration errors through the EHR is feasible and performs better than currently used incident reporting systems. Automated algorithms may be useful for real-time error identification and mitigation.

Project description:BackgroundOlder people in long-term residential care are at increased risk of medication prescribing and administration errors. The main aim of this study was to measure the incidence of medication administration errors in nursing and residential homes using a barcode medication administration (BCMA) system.MethodsA prospective study was conducted in 13 care homes (9 residential and 4 nursing). Data on all medication administrations for a cohort of 345 older residents were recorded in real-time using a disguised observation technique. Every attempt by social care and nursing staff to administer medication over a 3-month observation period was analysed using BCMA records to determine the incidence and types of potential medication administration errors (MAEs) and whether errors were averted. Error classifications included attempts to administer medication at the wrong time, to the wrong person or discontinued medication. Further analysis compared data for residential and nursing homes. In addition, staff were surveyed prior to BCMA system implementation to assess their awareness of administration errors.ResultsA total of 188,249 medication administration attempts were analysed using BCMA data. Typically each resident was receiving nine different drugs and was exposed to 206 medication administration episodes every month. During the observation period, 2,289 potential MAEs were recorded for the 345 residents; 90% of residents were exposed to at least one error. The most common (n = 1,021, 45% of errors) was attempting to give medication at the wrong time. Over the 3-month observation period, half (52%) of residents were exposed to a serious error such as attempting to give medication to the wrong resident. Error incidence rates were 1.43 as high (95% CI 1.32-1.56 p < 0.001) in nursing homes as in residential homes. The level of non-compliance with system alerts was very low in both settings (0.075% of administrations). The pre-study survey revealed that only 12/41 staff administering drugs reported they were aware of potential administration errors in their care home.ConclusionsThe incidence of medication administration errors is high in long-term residential care. A barcode medication administration system can capture medication administration errors and prevent these from occurring.

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Dataset Information

Use of Pediatric Injectable Medicines Guidelines and Associated Medication Administration Errors: A Human Reliability Analysis.

Background

Objective

Methods

Results

Conclusion and relevance

Publications

Use of Pediatric Injectable Medicines Guidelines and Associated Medication Administration Errors: A Human Reliability Analysis.

Similar Datasets

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