Tubes for pretransfusion testing should be collected by blood bank staff and hand labelled until the implementation of new technology for improved sample labelling. Results of a prospective study

How do we ensure a safe ABO recheck process?

BACKGROUND

Collecting a patient's blood in a correctly labeled pretransfusion specimen tube is essential for accurate ABO typing and safe transfusion. Noncompliance with specimen collection procedures can lead to wrong blood in tube (WBIT) incidents with potentially fatal consequences. Recent WBIT events inspired the investigation of how various institutions currently reduce the risk of these errors and ensure accurate ABO typing of patient samples.

MATERIALS AND METHODS

This article describes the techniques employed at various institutions across the United States to mitigate the risk of misidentified pretransfusion patient specimens. Details and considerations for each of these measures are provided.

RESULTS

Several institutions require the order for an ABO confirmation specimen, if indicated, to be generated from the transfusion medicine (TM) laboratory. Others issue a dedicated collection tube that is available exclusively from the TM service. Many institutions employ barcoding for electronic positive patient identification. Some use a combination of these strategies, depending on the locations or service lines from which the specimens are collected.

CONCLUSION

The description of various WBIT mitigation strategies will inform TM services on practices that may be effective at their respective institutions. Irrespective of the method(s) utilized, institutions should continue to monitor and mitigate specimen misidentification errors to promote sustained safe transfusion practices.

Prevalence of Near-miss Events of Transfusion Practice and Its Associated Factors amongst House Officers in a Teaching Hospital

Objectives

A near miss in transfusion practice is defined as a deviation from standard procedures discovered before transfusion and can lead to a transfusion error. Information on near-miss events provides pivotal data on areas of improvement to prevent actual errors in the future. Our study sought to determine the prevalence and rate of near-miss events and their associated factors amongst house officers (HO) in Hospital Universiti Sains Malaysia.

Methods

The initial part of this study is a descriptive cross-sectional study involving data collection from all requests sent for group, screen, and hold (GSH) and group and cross match (GXM) tests from 2011 to 2017. The association between sociodemographic, workplace, and experience factors with near-miss events amongst HO was analyzed with a case-control study using logistic regression.

Results

We reported 83 near-miss events with a prevalence of 0.034% (95% confidence interval 0.027–0.042). The rate of near-miss events was one in every 2916 requests. The mean reporting rate was 11.9 events per year. Clinical near miss predominated at 89.2% compared to 10.8% laboratory near miss. Mislabeled events (33.7%) were more than miscollected events (10.8%). HO were implicated with most events (83.1%). Most events were predominantly in the medical and obstetrics and gynecology wards amounting to 31.3% each. We found a significant association between the ages of HO with near-miss events.

Conclusions

The prevalence of near-miss events in our hospital was relatively low. Our study has shown areas for improvement include improving sampling practices in clinical areas, adequate training of laboratory technicians, and providing proper transfusion education. Interventions such as encouraging compliance to guidelines and training in clinical and laboratory areas to minimize the risk of mistransfusion should be considered.

Human Factors and Quality Improvement in the Emergency Department: Reducing Potential Errors in Blood Collection

OBJECTIVES

Adverse events in blood collection procedures such as mismatched or unlabeled samples may have critical implications on patient safety (such as wrong diagnosis and treatments). The current study examined blood collection procedures in an emergency department before and after the application of a human factors approach for improving performance quality and preventing adverse events.

METHODS

In the emergency department of a community care hospital, 190 blood collection events were observed in 2 phases: preintervention and postintervention. Two quality measures were tested as follows: quality measure 1, performing all 7 stages in the procedure of blood collection according to protocol, and quality measure 2, performing the stages of the procedure in the correct sequence according to the protocol. In addition, medical staff anonymously answered questionnaires about their procedure for collecting blood.

RESULTS

Analyses of data collected before the intervention revealed only 2 events in which all 7 stages in the protocol of the procedure were performed and only 1 event in which the 7 stages of the procedure were performed in the correct sequence. In 91% of the events, the patient was not fully identified. Based on these findings, we developed an intervention using a human factors approach to improve the quality of performance. Analyses of data collected after the intervention revealed significant differences (t188 = -14.9, ρ < 0.01) in quality measure 1 before (mean [SD], 4.8 [0.6]) and after (mean [SD], 6.4 [0.8]) the intervention was initiated, which implies improvement on efficiency subsequent to the implementation of the intervention. Improvement also appeared in quality measure 2.

CONCLUSIONS

This study illustrates the nature of potential errors in blood collection performance, offering a proactive approach to improve the rate of proper performance.

Transfusions in the Emergency department: More than a blood transfusion

Increasing haemoglobin and haematocrit levels with blood transfusions has been the gold standard for treating severe anaemia; however, the indication for transfusing concentrated red blood cells is based merely on a few laboratory markers, such as haemoglobin and haematocrit levels, rather than based on the symptoms according to clinical practice guidelines, the implementation of legal regulations and the consensus achieved by the hospitals' transfusion committees. The aim of this multicentre study was to reassess the suitability of the indication for transfusing concentrated red blood cells and the volumes transfused in emergency departments. We established an observational, multicentre, cross-sectional design with 2 participating centres: the La Paz University Hospital and the Hospital of Salamanca. In total, we obtained data from 381 patients, 220 (57.74%) of whom were men with an average age of 71.4±14.0 years and 161 (42.26%) of whom were women with an average age of 75.3±15.3 years (P<.001). The most prevalent underlying diseases in the patients who underwent transfusions were heart disease, which included haemorrhaging due to antiplatelet or anticoagulant therapy (57.7%), haemato-oncologic (15.3%) diseases and neurological disease. Only 54.9% (209/381) of the prescriptions for transfusion were considered appropriate, with significant differences according to the indication.

The dichotomy of the application of a systems approach in UK healthcare the challenges and priorities for implementation

There is increasing demand for a systems approach within national healthcare guidelines to provide a systematic and sustainable framework for improvements in patient safety. Supported by this is the growing body of evidence within Human Factors/Ergonomics (HFE) healthcare literature for the inclusion of this approach in health service design, provision and evaluation. This paper considers the current interpretation of this within UK healthcare systems and the dichotomy which exists in the challenge to implement a systems approach. Three case studies, from primary and secondary care, present a systems approach, offering a novel perspective of primary care and blood sampling. These provide practical illustrations of how HFE methods have been used in collaboration with healthcare staff to understand the system for the purpose of professional education, design and safety of clinical activities. The paper concludes with the challenge for implementation and proposes five roles for systems HFE to support patient safety. Practitioner Summary: healthcare is classified as a complex and dynamic system within this paper and as such HFE system methods are presented as desirable to understand the system, to develop HFE tools, to deliver education and integrate HFE within healthcare systems.

Effectiveness of Laboratory Practices to Reducing Patient Misidentification Due to Specimen Labeling Errors at the Time of Specimen Collection in Healthcare Settings: LMBP™ Systematic Review

Background

Specimen labeling errors have long plagued the laboratory industry putting patients at risk of transfusion-related death, medication errors, misdiagnosis, and patient mismanagement. Many interventions have been implemented and deemed to be effective in reducing sample error rates. The objective of this review was to identify and evaluate the effectiveness of laboratory practices/ interventions to develop evidence based recommendations for the best laboratory practices to reduce labeling errors.

Content

The standardized LMBP™ A-6 methods were used to conduct this systematic review. Total evidence included 12 studies published during the time periods of 1980 to September 2015. Combined data from seven studies found that the interventions developed as a result of improved communication and collaboration between the laboratory and clinical staff resulted in substantial decrease in specimen labeling errors (Median relative percent change in labeling errors: -75.86; IQI: -84.77, -58.00). Further data from subset of four studies showed a significant decrease in specimen labeling errors after the institution of the standardized specimen labeling protocols (Median relative percent decrease in specimen labeling errors: -72.45; IQI: -83.25, -46.50).

Summary

Based on the evidence included in this review, the interventions that enhance the communication and collaboration between laboratory and healthcare professionals can decrease the specimen identification errors in healthcare settings. However, more research is needed to make the conclusion on the effectiveness of other evaluated practices in this review including training and education of the specimen collection staff, audit and feedback of labeling errors, and implementation of new technology (other than barcoding).

Blood sampling - Two sides to the story

This study aimed to investigate why there is variability in taking blood. A multi method Pilot study was completed in four National Health Service Scotland hospitals. Human Factors/Ergonomics principles were applied to analyse data from 50 observations, 15 interviews and 12-months of incident data from all Scottish hospitals. The Functional Resonance Analysis Method (FRAM) was used to understand why variability may influence blood sampling functions. The analysis of the 61 pre blood transfusion sampling incidents highlighted limitations in the data collected to understand factors influencing performance. FRAM highlighted how variability in the sequence of blood sampling functions and the number of practitioners involved in a single blood sampling activity was influenced by the working environment, equipment, clinical context, work demands and staff resources. This pilot study proposes a realistic view of why blood sampling activities vary and proposes the need to consider the system's resilience in future safety management strategies.

Wrong blood in tube - potential for serious outcomes: can it be prevented?

'Wrong blood in tube' (WBIT) errors, where the blood in the tube is not that of the patient identified on the label, may lead to catastrophic outcomes, such as death from ABO-incompatible red cell transfusion. Transfusion is a multistep, multidisciplinary process in which the human error rate has remained unchanged despite multiple interventions (education, training, competency testing and guidelines). The most effective interventions are probably the introduction of end-to-end electronic systems and a group-check sample for patients about to receive their first transfusion, but neither of these eradicates all errors. Further longer term studies are required with assessment before and after introduction of the intervention. Although most focus has been on WBIT in relation to blood transfusion, all pathology samples should be identified and linked to the correct patient with the same degree of care. Human factors education and training could help to increase awareness of human vulnerability to error, particularly in the medical setting where there are many risk factors.

The role of comprehensive check at the blood bank reception on blood requisitions in detecting potential transfusion errors

Pre-transfusion testing includes proper requisitions, compatibility testing and pre-release checks. Proper labelling of samples and blood units and accurate patient details check helps to minimize the risk of errors in transfusion. This study was aimed to identify requisition errors before compatibility testing. The study was conducted in the blood bank of a tertiary care hospital in north India over a period of 3 months. The requisitions were screened at the reception counter and inside the pre-transfusion testing laboratory for errors. This included checking the Central Registration number (C.R. No.) and name of patient on the requisition form and the sample label; appropriateness of sample container and sample label; incomplete requisitions; blood group discrepancy. Out of the 17,148 blood requisitions, 474 (2.76 %) requisition errors were detected before the compatibility testing. There were 192 (1.11 %) requisitions where the C.R. No. on the form and the sample were not tallying and in 70 (0.40 %) requisitions patient's name on the requisition form and the sample were different. Highest number of requisitions errors were observed in those received from the Emergency and Trauma services (27.38 %) followed by Medical wards (15.82 %) and the lowest number (3.16 %) of requisition errors were observed from Hematology and Oncology wards. C.R. No. error was the most common error observed in our study. Thus a careful check of the blood requisitions at the blood bank reception counter helps in identifying the potential transfusion errors.

Interventions to reduce wrong blood in tube errors in transfusion: a systematic review

This systematic review addresses the issue of wrong blood in tube (WBIT). The objective was to identify interventions that have been implemented and the effectiveness of these interventions to reduce WBIT incidence in red blood cell transfusion. Eligible articles were identified through a comprehensive search of The Cochrane Library, MEDLINE, EMBASE, Cinahl, BNID, and the Transfusion Evidence Library to April 2013. Initial search criteria were wide including primary intervention or observational studies, case reports, expert opinion, and guidelines. There was no restriction by study type, language, or status. Publications before 1995, reviews or reports of a secondary nature, studies of sampling errors outwith transfusion, and articles involving animals were excluded. The primary outcome was a reduction in errors. Study characteristics, outcomes measured, and methodological quality were extracted by 2 authors independently. The principal method of analysis was descriptive. A total of 12,703 references were initially identified. Preliminary secondary screening by 2 reviewers reduced articles for detailed screening to 128 articles. Eleven articles were eventually identified as eligible, resulting in 9 independent studies being included in the review. The overall finding was that all the identified interventions reduced WBIT incidence. Five studies measured the effect of a single intervention, for example, changes to blood sample labeling, weekly feedback, handwritten transfusion requests, and an electronic transfusion system. Four studies reported multiple interventions including education, second check of ID at sampling, and confirmatory sampling. It was not clear which intervention was the most effective. Sustainability of the effectiveness of interventions was also unclear. Targeted interventions, either single or multiple, can lead to a reduction in WBIT; but the sustainability of effectiveness is uncertain. Data on the pre- and postimplementation of interventions need to be collected in future trials to demonstrate effectiveness, and comparative studies are needed of different interventions.

An Audit on Near-Miss Events in Transfusion Medicine: The Experience of the Teaching Hospital in Northeastern Malaysia

The rate of near misses in transfusion is important as it indicates situations with the potential of adverse outcome. The aim of this study was to assess the frequency of mislabeled and miscollected samples received by our transfusion medicine unit. This study was conducted from January to December 2009 in Transfusion Medicine Unit, Hospital Universiti Sains Malaysia. The total number of near-miss events reported and analysed over the 1-year period was 178 (0.40%). All mislabeled and miscollected samples and its location cases were identified. Mislabeled and miscollected (WBIT) samples were 66.3% and 33.7%, respectively. The highest number of mislabeled and miscollected samples was from accident and emergency unit and medical ward, respectively. Continuous monitoring and analysis of near misses data should be mandatory in order to improve the safety of transfusion.

Errors reported in cross match laboratory: a prospective data analysis

BACKGROUND

Human errors contribute to one half of all ABO-incompatible transfusions and transfusion-associated fatalities.

MATERIAL AND METHODS

We report distribution, type and frequency of errors through a prospective study designed specifically to determine errors reported in the cross match lab with their clinical outcome, and to investigate the contributing factors, and underlying system problems.

RESULTS

A total of 342 errors (6.2 per 1000 samples) were reported with majority of the errors being clerical (87.1%) and occurred outside the blood bank (86.5%). Labelling errors were the most frequent incidents encountered with bedside being the major site of deviation. The rate of labeling errors was 6.4 errors per 1000 samples (0.64%) in 32,189 samples studied. Among 80,100 components transfused, the frequency of incorrect blood component transfusion (IBCT) was estimated to be 22.5/100,000 blood components transfused. Miscollected samples (WBIT) occurred at a rate of 1 in 1532 samples (0.65 per 1000 samples). More than half of these errors occurred during the day shift (9 errors per 1000 request form) but more with urgent demands (11 errors per 1000 request form).

CONCLUSION

This study indicates the importance of proper specimen labeling and implemented cost-effective, non-compromising policy of rejecting each mislabelled specimen and realises the importance of ongoing quality monitoring to improve laboratory performance.

Strict adherence to a blood bank specimen labeling policy by all clinical laboratories significantly reduces the incidence of "wrong blood in tube"

Phlebotomy errors leading to incompatible transfusions are a leading cause of transfusion-related morbidity and mortality. Our institution's specimen-labeling policy requires the collection date, 2 unique patient identifiers, and the ability to identify the phlebotomist. This policy, however, was initially strictly enforced only by the blood bank. In fiscal year 2005, following an educational campaign on proper specimen labeling, all clinical laboratories began strictly adhering to the specimen-labeling policy. Compared with the preceding 4 years, in the 3 years following policy implementation, the incidence of wrong blood in tube (WBIT) and mislabeled specimens detected by the blood bank decreased by 73.5% (0.034% to 0.009%; P < or = .0001) and by 84.6% (0.026% to 0.004%; P < or = .0001), respectively. During a short period, a simple, low-cost educational initiative and policy change can lead to statistically significant decreases in WBIT and mislabeled specimens received by the blood bank.