Dataset Information

Qualitative exploration of practices to prevent medication errors in neonatal intensive care units: a focus group study.

ABSTRACT:

Background

Medication errors (MEs) in neonates are frequent and associated with increased potential for harm compared with adults. The effect of learning from reported MEs is potentially lacking due to underreporting, lack of feedback and missing actions to improve medication safety. A new approach involving positive recognition of current and future strategies may facilitate greater exploration of how to improve medication safety in neonates. We aimed to explore current and potential future practices to prevent MEs in neonatal intensive care units (NICUs).

Methods

Focus group interviews of physicians and nurses were conducted at three Danish NICUs. Participants were included if they had at least 1 month of working experience and provided direct patient care. A semistructured interview guide involving three questions was used: (a) how do you feel about discussing prevention of MEs? (b) how do you currently prevent MEs from occurring? and (c) how can we become better at preventing MEs in the future? Content analysis was used to identify themes in the interviews.

Results

Participants commented that MEs still occur and that action must be taken to improve medication safety. Current practices to prevent MEs involved technology, procedures, education, skills and hospital pharmacy services. Potential future practices to prevent MEs included customizing the computerized physician order entry systems to support optimal prescribing, standardizing the double-check process, training of calculation skills and teamwork and increased use of hospital pharmacy services.

Conclusions

Several current and potential future practices to reduce MEs in NICUs were identified, highlighting the complexity of MEs. Our findings support an interdisciplinary multifaceted intervention involving both technical and nontechnical elements to improve medication safety in NICUs.

SUBMITTER: Rishoej RM

PROVIDER: S-EPMC6048629 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Publications

Qualitative exploration of practices to prevent medication errors in neonatal intensive care units: a focus group study.

Rishoej Rikke Mie RM Lai Nielsen Henriette H Strzelec Stina Maria SM Fritsdal Refer Jane J Allermann Beck Sanne S Gramstrup Hanne Marie HM Thybo Christesen Henrik H Juel Kjeldsen Lene L Hallas Jesper J Almarsdóttir Anna Birna AB

Therapeutic advances in drug safety 20180423 7

<h4>Background</h4>Medication errors (MEs) in neonates are frequent and associated with increased potential for harm compared with adults. The effect of learning from reported MEs is potentially lacking due to underreporting, lack of feedback and missing actions to improve medication safety. A new approach involving positive recognition of current and future strategies may facilitate greater exploration of how to improve medication safety in neonates. We aimed to explore current and potential fu ...[more]

PMID: 30034776

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Project description:BackgroundNeonatal intensive care units are high-risk settings where medication errors can occur and cause harm to this fragile segment of patients. This multicenter qualitative study was conducted to describe medication errors that occurred in neonatal intensive care units in Palestine from the perspectives of healthcare providers.MethodsThis exploratory multicenter qualitative study was conducted and reported in adherence to the consolidated criteria for reporting qualitative research checklist. Semi-structured in-depth interviews were conducted with healthcare professionals (4 pediatricians/neonatologists and 11 intensive care unit nurses) who provided care services for patients admitted to neonatal intensive care units in Palestine. An interview schedule guided the semi-structured in-depth interviews. The qualitative interpretive description approach was used to thematically analyze the data.ResultsThe total duration of the interviews was 282 min. The healthcare providers described their experiences with 41 different medication errors. These medication errors were categorized under 3 categories and 10 subcategories. Errors that occurred while preparing/diluting/storing medications were related to calculations, using a wrong solvent/diluent, dilution errors, failure to adhere to guidelines while preparing the medication, failure to adhere to storage/packaging guidelines, and failure to adhere to labeling guidelines. Errors that occurred while prescribing/administering medications were related to inappropriate medication for the neonate, using a different administration technique from the one that was intended, and administering a different dose from the one that was intended. Errors that occurred after administering the medications were related to failure to adhere to monitoring guidelines.ConclusionIn this multicenter study, pediatricians/neonatologists and neonatal intensive care unit nurses described medication errors occurring in intensive care units in Palestine. Medication errors occurred in different stages of the medication process: preparation/dilution/storage, prescription/administration, and monitoring. Further studies are still needed to quantify medication errors occurring in the neonatal intensive care units and investigate if the designed strategies could be effective in minimizing the medication errors.

Project description: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.

Project description:BackgroundMedication errors, including dispensing errors, represent a substantial worldwide health risk with significant implications in terms of morbidity, mortality, and financial costs. Although pharmacists use methods like barcode scanning and double-checking for dispensing verification, these measures exhibit limitations. The application of artificial intelligence (AI) in pharmacy verification emerges as a potential solution, offering precision, rapid data analysis, and the ability to recognize medications through computer vision. For AI to be embraced, it must be designed with the end user in mind, fostering trust, clear communication, and seamless collaboration between AI and pharmacists.ObjectiveThis study aimed to gather pharmacists' feedback in a focus group setting to help inform the initial design of the user interface and iterative designs of the AI prototype.MethodsA multidisciplinary research team engaged pharmacists in a 3-stage process to develop a human-centered AI system for medication dispensing verification. To design the AI model, we used a Bayesian neural network that predicts the dispensed pills' National Drug Code (NDC). Discussion scripts regarding how to design the system and feedback in focus groups were collected through audio recordings and professionally transcribed, followed by a content analysis guided by the Systems Engineering Initiative for Patient Safety and Human-Machine Teaming theoretical frameworks.ResultsA total of 8 pharmacists participated in 3 rounds of focus groups to identify current challenges in medication dispensing verification, brainstorm solutions, and provide feedback on our AI prototype. Participants considered several teaming scenarios, generally favoring a hybrid teaming model where the AI assists in the verification process and a pharmacist intervenes based on medication risk level and the AI's confidence level. Pharmacists highlighted the need for improving the interpretability of AI systems, such as adding stepwise checkmarks, probability scores, and details about drugs the AI model frequently confuses with the target drug. Pharmacists emphasized the need for simplicity and accessibility. They favored displaying only essential information to prevent overwhelming users with excessive data. Specific design features, such as juxtaposing pill images with their packaging for quick comparisons, were requested. Pharmacists preferred accept, reject, or unsure options. The final prototype interface included (1) checkmarks to compare pill characteristics between the AI-predicted NDC and the prescription's expected NDC, (2) a histogram showing predicted probabilities for the AI-identified NDC, (3) an image of an AI-provided "confused" pill, and (4) an NDC match status (ie, match, unmatched, or unsure).ConclusionsIn partnership with pharmacists, we developed a human-centered AI prototype designed to enhance AI interpretability and foster trust. This initiative emphasized human-machine collaboration and positioned AI as an augmentative tool rather than a replacement. This study highlights the process of designing a human-centered AI for dispensing verification, emphasizing its interpretability, confidence visualization, and collaborative human-machine teaming styles.

Project description:BackgroundWe aimed to examine current bedside analgesia/sedation (A/S) and pain assessment (PA) practices in Italian neonatal intensive care units (NICUs) in relation to the findings of an epidemiological European study and recently-introduced national guidelines.MethodsWe analyzed the Italian data from the EUROPAIN (EUROpean-Pain-Audit-In-Neonates) prospective observational study on A/S practices that involved 6680 newborns admitted to tertiary-level NICUs in 18 European countries. Demographics, type of assisted ventilation, type and mode of A/S administration and PA were analyzed. Multivariate linear regression models were used to identify factors predicting A/S and PA practices.ResultsFrom October 1st, 2012 to June 30th, 2013, thirty Italian NICUs gathered data on 422 newborn: 131 on invasive ventilation (IV); 150 on noninvasive ventilation (NIV); and 141 on spontaneous ventilation (SV). A/S was documented for 35.3% of all infants admitted (86.3% IV; 17.3% NIV; 7.1% SV [p = 0.0001]), and varied considerably between NICUs (as reported in other European countries). Strong analgesics were used in 32.5% of cases, sedatives in 10.2%, mild analgesics in 3.8%. Fentanyl was used in 78.6% of cases, morphine in 8.4%, neuromuscular blockers in 5.3%, midazolam in 22.1%. The performance of PA was documented in 67.5% of all newborn (85.5% IV; 67.3% NIV; 51.1% SV [p = 0.001]). Illness severity, type of ventilation, bedside PA, and number of NICU beds were all factors associated with A/S use on multivariate analysis, while gestational age ≤ 32 weeks, and type of ventilation and presence of a pain team were associated with PA.ConclusionsWe documented a generally widespread, but still highly variable use of A/S and PA at Italian NICUs, despite the diffusion of national guidelines. There is an urgent need to improve routine PA to enable customized pain and stress control (and prevention) in all infants.Trial registrationClinical Trials.gov # NCT01694745 .

Project description:BackgroundDespite extensive research carried out on medication administration errors (MAEs) in the domain of infusion therapy, there is limited knowledge on nurse's perceptions on the occurrence of MAEs during infusion therapy. Since nurses are responsible for medication preparation and administration in Dutch hospitals, it is vital to understand their perspectives on the risk factors for MAEs.AimThe purpose of this study is to investigate the perception of nurses, working in adult ICUs, on the occurrence of MAEs during continuous infusion therapies.MethodsA digital web-based survey was distributed among 373 ICU nurses working in Dutch hospitals. The survey investigated nurses' perceptions on the frequency, severity of consequences and preventability of MAEs, factors for the occurrence of MAEs, and infusion pump and smart infusion safety technology.ResultsA total of 300 nurses started to fill out the survey but only 91 of them (30.3%) fully completed it and were included in analyses. Medication-related factors and Care professional-related factors were perceived as the two most important risk categories for the occurrence of MAEs. Important risk factors contributing to the occurrence of MAEs included high patient-nurse ratio, problems in communication between caregivers, frequent staff changes and transfers of care, and no/incorrect dosage/concentration on labels. Drug library was reported as the most important infusion pump feature and both Bar Code Medication Administration (BCMA) and medical device connectivity as the two most important smart infusion safety technologies. Nurses perceived the majority of MAEs as preventable.ConclusionsBased on ICU nurses' perceptions, the present study suggests that strategies to reduce MAEs in these units should focus on, among other factors, the high patient-to-nurse ratio, problems in communication between nurses, frequent staff changes and transfers of care, and no/incorrect dosage/concentration on drug labels.

Project description:BackgroundThe Indian government supports both public- and private-sector provision of hospital care for neonates: neonatal intensive care is offered in public facilities alongside a rising number of private-for-profit providers. However, there are few published reports about mortality levels and care practices in these facilities. We aimed to assess care practices, causes of admission, and outcomes from neonatal intensive care units (NICUs) in public secondary and private tertiary hospitals and both public and private medical colleges enrolled in a quality improvement collaborative in Telangana and Andhra Pradesh-2 Indian states with a respective population of 35 and 50 million.Methods and findingsWe conducted a cross-sectional study between 30 May and 26 August 2016 as part of a baseline evaluation in 52 consenting hospitals (26 public secondary hospitals, 5 public medical colleges, 15 private tertiary hospitals, and 6 private medical colleges) offering neonatal intensive care. We assessed the availability of staff and services, adherence to evidence-based practices at admission, and case fatality after admission to the NICU using a range of tools, including facility assessment, observations of admission, and abstraction of registers and telephone interviews after discharge. Our analysis is adjusted for clustering and weighted for caseload at the hospital level and presents findings stratified by type and ownership of hospitals. In total, the NICUs included just over 3,000 admissions per month. Staffing and infrastructure provision were largely according to government guidelines, except that only a mean of 1 but not the recommended 4 paediatricians were working in public secondary NICUs per 10 beds. On admission, all neonates admitted to private hospitals had auscultation (100%, 19 of 19 observations) but only 42% (95% confidence interval [CI] 25%-62%, p-value for difference is 0.361) in public secondary hospitals. The most common single cause of admission was preterm birth (25%) followed by jaundice (23%). Case-fatality rates at age 28 days after admission to a NICU were 4% (95% CI 2%-8%), 15% (9%-24%), 4% (2%-8%) and 2% (1%-5%) (Chi-squared p = 0.001) in public secondary hospitals, public medical colleges, private tertiary hospitals, and private medical colleges, respectively, according to facility registers. Case fatality according to postdischarge telephone interviews found rates of 12% (95% CI 7%-18%) for public secondary hospitals. Roughly 6% of admitted neonates were referred to another facility. Outcome data were missing for 27% and 8% of admissions to private tertiary hospitals and private medical colleges. Our study faced the limitation of missing data due to incomplete documentation. Further generalizability was limited due to the small sample size among private facilities.ConclusionsOur findings suggest differences in quality of neonatal intensive care and 28-day survival between the different types of hospitals, although comparison of outcomes is complicated by differences in the case mix and referral practices between hospitals. Uniform reporting of outcomes and risk factors across the private and public sectors is required to assess the benefits for the population of mixed-care provision.

Project description:OBJECTIVES:The aim of this study was to explore the experiences of doctors and nurses caring for patients with delirium in the intensive care unit (ICU) and to describe the process of delirium management. SETTING:This study was performed in 5 ICUs located within 4 hospitals in Madrid (Spain). PARTICIPANTS:Purposeful sampling was performed which included (1) doctors and nurses working in ICUs, (2) with >1 year experience in the ICU and (3) clinical experience with delirium. 38 professionals participated (19 doctors, 19 nurses), including 22 women and 16 men. The total mean age was 39 years. DESIGN:A qualitative study using focus groups. METHODS:7 focus groups were held to collect data: 3 nurse focus groups, 3 doctor focus groups and 1 mixed focus group. Each group comprised 6-10 participants. A semistructured questions guide was used. Thematic analysis methods were used to analyse the data. RESULTS:3 themes were identified: (1) the professional perspective on delirium; (2) implementing pharmacological and non-pharmacological treatment for delirium and (3) work organisation in the ICU. The professionals regarded patients with delirium with uncertainty, and felt they were often underdiagnosed and poorly managed. Doctors displayed discrepancies regarding pharmacological prescriptions and decision-making. The choice of medication was determined by experience. Nurses felt that, for many doctors, delirium was not considered a matter of urgency in the ICU. Nurses encountered difficulties when applying verbal restraint, managing sleep disorders and providing early mobilisation. The lack of a delirium protocol generates conflicts regarding what type of care management to apply, especially during the night shift. A degree of group pressure exists which, in turn, influences the decision-making process and patient care. CONCLUSIONS:Patients with delirium represent complex cases, requiring the implementation of specific protocols. These results serve to improve the process of care in patients with delirium.

Dataset Information

Qualitative exploration of practices to prevent medication errors in neonatal intensive care units: a focus group study.

Background

Methods

Results

Conclusions

Publications

Qualitative exploration of practices to prevent medication errors in neonatal intensive care units: a focus group study.

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