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Automated detection of medication administration errors in neonatal intensive care.

ABSTRACT: To 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.We 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.In 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.Automated 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.

SUBMITTER: Li Q

PROVIDER: S-EPMC4715992 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Automated detection of medication administration errors in neonatal intensive care.

Li Qi Q Kirkendall Eric S ES Hall Eric S ES Ni Yizhao Y Lingren Todd T Kaiser Megan M Lingren Nataline N Zhai Haijun H Solti Imre I Melton Kristin K

Journal of biomedical informatics 20150717

<h4>Objective</h4>To 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.<h4>Methods</h4>We developed novel computerized algori ...[more]

PMID: 26190267

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Project description:ImportanceIncoming text messages and calls on nurses' mobile telephones may interrupt medication administration, but whether such interruptions are associated with errors has not been established.ObjectiveTo assess whether a temporal association exists between mobile telephone interruptions and subsequent errors by pediatric intensive care unit (PICU) nurses during medication administration.Design, setting, and participantsA retrospective cohort study was performed using telecommunications and electronic health record data from a PICU in a children's hospital. Data were collected from August 1, 2016, through September 30, 2017. Participants included 257 nurses and the 3308 patients to whom they administered medications.ExposuresPrimary exposures were incoming telephone calls and text messages received on the institutional mobile telephone assigned to the nurse in the 10 minutes leading up to a medication administration attempt. Secondary exposures were the nurse's PICU experience, work shift (day vs night), nurse to patient ratio, and level of patient care required.Main outcomes and measuresPrimary outcome, errors during medication administration, was a composite of reported medication administration errors and bar code medication administration error alerts generated when nurses attempted to give medications without active orders for the patient whose bar code they scanned.ResultsParticipants included 257 nurses, of whom 168 (65.4%) had 6 months or more of PICU experience; and 3308 patients, of whom 1839 (55.6%) were male, 1539 (46.5%) were white, and 2880 (87.1%) were non-Hispanic. The overall rate of errors during 238 540 medication administration attempts was 3.1% (95% CI, 3.0%-3.3%) when nurses were uninterrupted by incoming telephone calls and 3.7% (95% CI, 3.4%-4.0%) when they were interrupted by such calls. During day shift, the odds ratios (ORs) for error when interrupted by calls (compared with uninterrupted) were 1.02 (95% CI, 0.92-1.13; P = .73) among nurses with 6 months or more of PICU experience and 1.22 (95% CI, 1.00-1.47; P = .046) among nurses with less than 6 months of experience. During night shift, the ORs for error when interrupted by calls were 1.35 (95% CI, 1.16-1.57; P < .001) among nurses with 6 months or more of PICU experience and 1.53 (95% CI, 1.16-2.03; P = .003) among nurses with less than 6 months of experience. Nurses administering medications to 1 or more patients receiving mechanical ventilation and arterial catheterization while caring for at least 1 other patient had an increased risk of error (OR, 1.21; 95% CI, 1.03-1.42; P = .02). Incoming text messages were not associated with error (OR, 0.97; 95% CI, 0.92-1.02; P = .22).Conclusions and relevanceThis study's findings suggest that incoming telephone call interruptions may be temporally associated with medication administration errors among PICU nurses. Risk of error varied by shift, experience, nurse to patient ratio, and level of patient care required.

Project description:BACKGROUND: Older 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. METHODS: A 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. RESULTS: A 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. CONCLUSIONS: The 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.

Project description:IntroductionChildren admitted to paediatric and neonatal intensive care units may be at high risk from medication errors and preventable adverse drug events.ObjectiveThe objective of this systematic review was to review empirical studies examining the prevalence and nature of medication errors and preventable adverse drug events in paediatric and neonatal intensive care units.Data sourcesSeven electronic databases were searched between January 2000 and March 2019.Study selectionQuantitative studies that examined medication errors/preventable adverse drug events using direct observation, medication chart review, or a mixture of methods in children ??18 years of age admitted to paediatric or neonatal intensive care units were included.Data extractionData on study design, detection method used, rates and types of medication errors/preventable adverse drug events, and medication classes involved were extracted.ResultsThirty-five unique studies were identified for inclusion. In paediatric intensive care units, the median rate of medication errors was 14.6 per 100 medication orders (interquartile range 5.7-48.8%, n?=?3) and between 6.4 and 9.1 per 1000 patient-days (n?=?2). In neonatal intensive care units, medication error rates ranged from 4 to 35.1 per 1000 patient-days (n?=?2) and from 5.5 to 77.9 per 100 medication orders (n?=?2). In both settings, prescribing and medication administration errors were found to be the most common medication errors, with dosing errors the most frequently reported error subtype. Preventable adverse drug event rates were reported in three paediatric intensive care unit studies as 2.3 per 100 patients (n?=?1) and 21-29 per 1000 patient-days (n?=?2). In neonatal intensive care units, preventable adverse drug event rates from three studies were 0.86 per 1000 doses (n?=?1) and 0.47-14.38 per 1000 patient-days (n?=?2). Anti-infective agents were commonly involved with medication errors/preventable adverse drug events in both settings.ConclusionsMedication errors occur frequently in critically ill children admitted to paediatric and neonatal intensive care units and may lead to patient harm. Important targets such as dosing errors and anti-infective medications were identified to guide the development of remedial interventions.

Project description:Medication administration errors (MAEs) occur frequently in hospitals and may compromise patient safety. Preventive strategies are needed to reduce the risk of MAEs. The primary aim of this study was to assess the effect of central automated unit dose dispensing with barcode-assisted medication administration on the prevalence of MAEs. Secondary aims were to assess the effect on the type and potential severity of MAEs. Furthermore, compliance with procedures regarding scanning of patient and medication barcodes and nursing staff satisfaction with the medication administration system were assessed. We performed a prospective uncontrolled before-and-after study in six clinical wards in a Dutch university hospital from 2018 to 2020. MAE data were collected by observation. The primary outcome was the proportion of medication administrations with one or more MAEs. Secondary outcomes were the type and potential severity of MAEs, rates of compliance with patient identification and signing of administered medication by scanning and nursing staff satisfaction with the medication administration system. Multivariable mixed-effects logistic regression analyses were used for the primary outcome to adjust for confounding and for clustering on nurse and patient level. One or more MAEs occurred in 291 of 1490 administrations (19.5%) pre-intervention and in 258 of 1630 administrations (15.8%) post-intervention (adjusted odds ratio 0.70, 95% confidence interval 0.51-0.96). The rate of omission fell from 4.6% to 2.0% and of wrong dose from 3.8% to 2.1%, whereas rates of other MAE types were similar. The rate of potentially harmful MAEs fell from 3.0% (n = 44) to 0.3% (n = 5). The rates of compliance with scanning of patient and medication barcode post-intervention were 13.6% and 55.9%, respectively.The median overall satisfaction score of the nurses with the medication administration system on a 100-point scale was 70 (interquartile range 63-75, n = 193) pre-intervention and 70 (interquartile range 60-78, n = 145) post-intervention (P = 0.626, Mann-Whitney U test). The implementation of central automated unit dose dispensing with barcode-assisted medication administration was associated with a lower probability of MAEs, including potentially harmful errors, but more compliance with scanning procedures is needed. Nurses were moderately satisfied with the medication administration system, both before and after implementation. In conclusion, despite low compliance with scanning procedures, this study shows that this intervention contributes to the improvement of medication safety in hospitals.

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Automated detection of medication administration errors in neonatal intensive care.

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Automated detection of medication administration errors in neonatal intensive care.

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