Association Between Workarounds and Medication Administration Errors in Bar Code-Assisted Medication Administration: Protocol of a Multicenter Study.
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ABSTRACT: Background
Information technology-based methods such as bar code-assisted medication administration (BCMA) systems have the potential to reduce medication administration errors (MAEs) in hospitalized patients. In practice, however, systems are often not used as intended, leading to workarounds. Workarounds may result in MAEs that may harm patients.Objective
The primary aim is to study the association of workarounds with MAEs in the BCMA process. Second, we will determine the frequency and type of workarounds and MAEs and explore the potential risk factors (determinants) for workarounds.Methods
This is a multicenter prospective study on internal medicine and surgical wards of 4 Dutch hospitals using BCMA systems to administer medication. We will include a total of 6000 individual drug administrations using direct observation to collect data.Results
The project was funded in 2014 and enrollment was completed at the end of 2016. Data analysis is under way and the first results are expected to be submitted for publication at the end of 2017.Conclusions
If an association between workarounds and MAEs is established, this information can be used to reduce the frequency of MAEs. Information on determinants of workarounds can aid in a focused approach to reduce workarounds and thus increase patient safety.Trial registration
Netherlands Trial Register NTR4355; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4355 (Archived by WebCite at http://www.webcitation.org/6pqTLxc6i).
SUBMITTER: van der Veen W
PROVIDER: S-EPMC5429431 | biostudies-literature | 2017 Apr
REPOSITORIES: biostudies-literature
Publications
Association Between Workarounds and Medication Administration Errors in Bar Code-Assisted Medication Administration: Protocol of a Multicenter Study.
van der Veen Willem W van den Bemt Patricia Mla PM Bijlsma Maarten M de Gier Han J HJ Taxis Katja K
JMIR research protocols 20170428 4
<h4>Background</h4>Information technology-based methods such as bar code-assisted medication administration (BCMA) systems have the potential to reduce medication administration errors (MAEs) in hospitalized patients. In practice, however, systems are often not used as intended, leading to workarounds. Workarounds may result in MAEs that may harm patients.<h4>Objective</h4>The primary aim is to study the association of workarounds with MAEs in the BCMA process. Second, we will determine the freq ...[more]
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Project description:AIMS AND OBJECTIVES:To identify that workarounds (defined as "informal temporary practices for handling exceptions to normal procedures or workflow") by nurses using information technology potentially compromise medication safety. Therefore, we aimed to identify potential risk factors associated with workarounds performed by nurses in Barcode-assisted Medication Administration in hospitals. BACKGROUND:Medication errors occur during the prescribing, distribution and administration of medication. Errors could harm patients and be a tragedy for both nurses and medical doctors involved. Interventions to prevent errors have been developed, including those based on information technology. To cope with shortcomings in information technology-based interventions as Barcode-assisted Medication Administration, nurses perform workarounds. Identification of workarounds in information technology is essential to implement better-designed software and processes which fit the nurse workflow. DESIGN:We used the data from our previous prospective observational study, performed in four general hospitals in the Netherlands using Barcode techniques, to administer medication to inpatients. METHODS:Data were collected from 2014-2016. The disguised observation was used to gather information on potential risk factors and workarounds. The outcome was a medication administration with one or more workarounds. Logistic mixed models were used to determine the association between potential risk factors and workarounds. The STROBE checklist was used for reporting our data. RESULTS:We included 5,793 medication administrations among 1,230 patients given by 272 nurses. In 3,633 (62.7%) of the administrations, one or more workarounds were observed. In the multivariate analysis, factors significantly associated with workarounds were the medication round at 02 p.m.-06 p.m. (adjusted odds ratio [OR]: 1.60, 95% CI: 1.05-2.45) and 06 p.m.-10 p.m. (adjusted OR: 3.60, 95% CI: 2.11-6.14) versus the morning shift 06 a.m.-10 a.m., the workdays Monday (adjusted OR: 2.59, 95% CI: 1.51-4.44), Wednesday (adjusted OR: 1.92, 95% CI: 1.2-3.07) and Saturday (adjusted OR: 2.24, 95% CI: 1.31-3.84) versus Sunday, the route of medication, nonoral (adjusted OR: 1.28, 95% CI: 1.05-1.57) versus the oral route of drug administration, the Anatomic Therapeutic Chemical classification-coded medication "other" (consisting of the irregularly used Anatomic Therapeutic Chemical classes [D, G, H, L, P, V, Y, Z]) (adjusted OR: 1.49, 95% CI: 1.05-2.11) versus Anatomic Therapeutic Chemical class A (alimentary tract and metabolism), and the patient-nurse ratio ≥6-1 (adjusted OR: 5.61, 95% CI: 2.9-10.83) versus ≤5-1. CONCLUSIONS:We identified several potential risk factors associated with workarounds performed by nurses that could be used to target future improvement efforts in Barcode-assisted Medication Administration. RELEVANCE TO CLINICAL PRACTICE:Nurses administering medication in hospitals using Barcode-assisted Medication Administration frequently perform workarounds, which may compromise medication safety. In particular, nurse workload and the patient-nurse ratio could be the focus for improvement measures as these are the most clearly modifiable factors identified in this study.
| S-EPMC7328795 | biostudies-literature
Project description:ObjectiveTo assess the impact of implementing bar-code medication administration (BCMA) technology on the rate of medication administration errors in the inpatient setting, specifically those that affect the patient and result in harm.Patients and MethodsImplementation of the new technology began in September 2008 in a staged rollout of 4 or 5 units at a time in 11 separate waves. All corresponding medication administrations and voluntarily reported medication-related adverse events from March 1, 2007, through September 30, 2013, were included for analyses. Adherence to the use of BCMA technology and the number of adverse events were tracked and compared across the preimplementation period through follow-up. Actual errors, not potential errors, were included in the analysis.ResultsAfter the BCMA technology was introduced, reported medication administration errors decreased by 43.5%. More importantly, the rate of harmful medication errors decreased from 0.65 per 100,000 medications preintervention to 0.29 per 100,000 medications postintervention. This resulted in a 55.4% decrease in actual patient harm events. None of the errors at category E or higher was caused by BCMA factors.ConclusionConsistent use of BCMA technology improves patient safety by decreasing the number of patients harmed by medication administration errors.
| S-EPMC6257885 | biostudies-other
Project description:BackgroundThe use of a 'do not interrupt' vest during medication administration rounds is recommended but there have been no controlled randomized studies to evaluate its impact on reducing administration errors. We aimed to evaluate the impact of wearing such a vest on reducing such errors. The secondary objectives were to evaluate the types and potential clinical impact of errors, the association between errors and several risk factors (such as interruptions), and nurses' experiences.MethodsThis was a multicenter, cluster, controlled, randomized study (March-July 2017) in 29 adult units (4 hospitals). Data were collected by direct observation by trained observers. All nurses from selected units were informed. A 'Do not interrupt' vest was implemented in all units of the experimental group. A poster was placed at the entrance of these units to inform patients and relatives. The main outcome was the administration error rate (number of Opportunities for Error (OE), calculated as one or more errors divided by the Total Opportunities for Error (TOE) and multiplied by 100).ResultsWe enrolled 178 nurses and 1346 patients during 383 medication rounds in 14 units in the experimental group and 15 units in the control group. During the intervention period, the administration error rates were 7.09% (188 OE with at least one error/2653 TOE) for the experimental group and 6.23% (210 OE with at least one error/3373 TOE) for the control group (p = 0.192). Identified risk factors (patient age, nurses' experience, nurses' workload, unit exposition, and interruption) were not associated with the error rate. The main error type observed for both groups was wrong dosage-form. Most errors had no clinical impact for the patient and the interruption rates were 15.04% for the experimental group and 20.75% for the control group.ConclusionsThe intervention vest had no impact on medication administration error or interruption rates. Further studies need to be performed taking into consideration the limitations of our study and other risk factors associated with other interventions, such as nurse's training and/or a barcode system.Trial registrationThe PERMIS study protocol (V2-1, 11/04/2017) was approved by institutional review boards and ethics committees (CPP Ile de France number 2016-A00211-50, CNIL 21/03/2017, CCTIRS 11/04/2016). It is registered at ClinicalTrials.gov (registration number: NCT03062852 , date of first registration: 23/02/2017).
| S-EPMC8383384 | biostudies-literature
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.
| S-EPMC6990809 | biostudies-literature
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.
| S-EPMC4715992 | biostudies-literature
Project description:BackgroundAdministering medication through an enteral feeding tube (FT) is a frequent cause of errors resulting in increased morbidity and cost. Studies on interventions to prevent these errors in hospitalized patients, however, are limited.ObjectiveThe objective was to study the effect of a clinical decision support system (CDSS)-assisted pharmacy intervention on the incidence of FT-related medication errors (FTRMEs) in hospitalized patients.MethodsA pre-post intervention study was conducted between October 2014 and May 2015 in Catharina Hospital, the Netherlands. Patients who were admitted to the wards of bowel and liver disease, oncology, or neurology; using oral medication; and had an enteral FT were included. Preintervention patients were given care as usual. The intervention consisted of implementing a CDSS-assisted pharmacy check while also implementing standard operating procedures and educating personnel. An FTRME was defined as the administration of inappropriate medication through an enteral FT. The incidence was expressed as the number of FTRMEs per medication administration. Multivariate Poisson regression was used to calculate the incidence ratio (IR) comparing both phases.ResultsEighty-one patients were included, 38 during preintervention and 43 during the intervention phase. Incidence of FTRMEs in the preintervention phase was 0.15 (95% CI, 0.07-0.23) vs 0.02 (95% CI, 0.00-0.04) in the intervention phase, resulting in an adjusted IR of 0.13 (95% CI, 0.10-0.18).DiscussionIncidence of FTRMEs, as well as the IR, is comparable to previous studies.ConclusionThe intervention resulted in a substantial reduction in the incidence of FTRMEs.
| S-EPMC8048796 | biostudies-literature
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.
| S-EPMC3254134 | biostudies-literature
Project description:PurposeMedications are mostly taken in patients' own homes, increasingly administered by carers, yet studies of medication safety have been largely conducted in the hospital setting. We aimed to review studies of how carers cause and/or prevent medication administration errors (MAEs) within the patient's home; to identify types, prevalence and causes of these MAEs and any interventions to prevent them.MethodsA narrative systematic review of literature published between 1 Jan 1946 and 23 Sep 2013 was carried out across the databases EMBASE, MEDLINE, PSYCHINFO, COCHRANE and CINAHL. Empirical studies were included where carers were responsible for preventing/causing MAEs in the home and standardised tools used for data extraction and quality assessment.ResultsThirty-six papers met the criteria for narrative review, 33 of which included parents caring for children, two predominantly comprised adult children and spouses caring for older parents/partners, and one focused on paid carers mostly looking after older adults. The carer administration error rate ranged from 1.9 to 33% of medications administered and from 12 to 92.7% of carers administering medication. These included dosage errors, omitted administration, wrong medication and wrong time or route of administration. Contributory factors included individual carer factors (e.g. carer age), environmental factors (e.g. storage), medication factors (e.g. number of medicines), prescription communication factors (e.g. comprehensibility of instructions), psychosocial factors (e.g. carer-to-carer communication), and care-recipient factors (e.g. recipient age). The few interventions effective in preventing MAEs involved carer training and tailored equipment.ConclusionThis review shows that home medication administration errors made by carers are a potentially serious patient safety issue. Carers made similar errors to those made by professionals in other contexts and a wide variety of contributory factors were identified. The home care setting should be a priority for the development of patient safety interventions.
| S-EPMC5132322 | biostudies-literature
Project description:OBJECTIVES:The primary aim of this article was to identify the latent failures that are perceived to underpin medication errors. STUDY SETTING:The study was conducted within three medical wards in a hospital in the United Kingdom. STUDY DESIGN:The study employed a cross-sectional qualitative design. DATA COLLECTION METHODS:Interviews were conducted with 12 nurses and eight managers. Interviews were transcribed and subject to thematic content analysis. A two-step inter-rater comparison tested the reliability of the themes. PRINCIPAL FINDINGS:Ten latent failures were identified based on the analysis of the interviews. These were ward climate, local working environment, workload, human resources, team communication, routine procedures, bed management, written policies and procedures, supervision and leadership, and training. The discussion focuses on ward climate, the most prevalent theme, which is conceptualized here as interacting with failures in the nine other organizational structures and processes. CONCLUSIONS:This study is the first of its kind to identify the latent failures perceived to underpin medication errors in a systematic way. The findings can be used as a platform for researchers to test the impact of organization-level patient safety interventions and to design proactive error management tools and incident reporting systems in hospitals.
| S-EPMC3401393 | biostudies-literature
Project description:BackgroundMedication administration errors (MAEs) are a frequent cause of morbidity and mortality in acute care settings and can result in a prolonged hospital stay. The WHO estimated that medication errors cost up to $42 billion globally per a year. Therefore, MAEs was among the most common medical errors to occur in acute care settings. Studies of medication error usually focus on system factors, thus creating a gap between what researchers know about the causes of MAEs, and what frontline nurses actually do in the clinical setting. The purpose of this review is to fill a gap in the existing literature by focusing on the relationship between nurses' characteristics and MAEs.MethodsOnline databases were accessed, including CINAHL, PsycINFO, PubMed, Scopus, and Google Scholar from 2007-2020 period. This review was guided by the methods described by Whittemore and Knafl. Studies that addressed the occurrence of medication errors based on RN demographics were included in this review. The included studies were reviewed and analyzed by the two authors.ResultsOf the 1141 publications retrieved, 19 studies met inclusion criteria. The result provided strong evidence that nurses' level of education, length of experience, and attendance at training courses, are directly associated with the occurrence of MAEs. There is weak evidence of MAEs being influenced by the age and gender of nurses. Other nurse characteristics, such as cognitive load, frustration with technology, negligence, lack of attentiveness, and nurse ethnicity, are not adequately examined across the reviewed studies necessitates further research.ConclusionFocusing on nurses' characteristics might facilitate other researchers to suggest appropriate interventions that may reduce the incidence of MAEs. Interventional studies may provide convincing evidence as to whether one variable has a causal effect on another variable, and control the influence of confounding variables to enhance the generalizability of the findings.
| S-EPMC8223601 | biostudies-literature