‘Wrong blood in tube’: solutions for a persistent problem

Lost, mislabeled, and mishandled surgical and clinical pathology specimens: A systematic review of published literature

OBJECTIVES

To perform a systematic review of published academic literature related to lost, mislabeled, and mishandled surgical and clinical pathology specimens during the preanalytical stage.

METHODS

The authors used Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines to search PubMed, MEDLINE, Web of Science, and Scopus for relevant articles published from January 1, 1990, to May 1, 2023.

RESULTS

The authors screened 1313 articles and identified 44 peer-reviewed, English-language articles published between 1990 and 2021 for inclusion in the final systematic review. Most articles (n = 36) reported results from US-based facilities. Articles primarily focused on general clinical and general surgical pathology. Analysis of the articles revealed that articles reported a range of methodological approaches, including incident reports, implementation analyses, case studies, and commentary recommendations. Most articles focused on mislabeling errors (61.3%) and missing or lost specimens (18.2%), while several articles combined specimen errors (20.5%). Several implementation studies (22.7%) reported using multiple interventions to mitigate errors. Implementation efforts reported between 70% and 100% reduction in pathology errors.

CONCLUSIONS

The review highlights the limited research on the topic, with an average of 2 articles per year discussing lost, mislabeled, or mishandled specimens. Intervention studies addressed The Joint Commission's patient safety goals for laboratory practice. More research is needed about error incidents and reporting in non-Western countries to gain a more global perspective on the topic.

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.

How to improve issuing, transfusion and follow-up of blood components in Southern and Eastern Mediterranean countries? A benchmark assessment

To determine the existence of guidelines regarding the appropriate clinical use of blood and blood components, transfusion requests, and blood issuing/reception documents and procedures. The different bedside transfusion organizations/processes and hemovigilance are also analyzed. The ultimate objective is to identify safe potential options in order to improve blood safety at the lowest cost. Data emanating from eight Arabic eastern/southern Mediterranean countries who responded to five surveys were collected and tabulated. National recommendations for the clinical use of blood components especially for hemoglobinopathies are lacking in some countries. In matter of good practices in the prescription, issuing and reception of BCs, efforts were made either on national or local basis. Procedures regarding patient information and ethical issues are still lacking. Almost all Mediterranean countries apply two blood testing procedures on each patient sample. Only Morocco, Tunisia and Algeria perform bed side blood group testing; Egypt and Lebanon perform antibody screen and antiglobulin cross matching universally. Automation for blood testing is insufficiently implemented in almost all countries and electronic release is almost absent. National hemovigilance policy is implemented in Tunisia, Morocco, and Lebanon but the reporting system remains inoperative. Insufficient resources severely hinders the implementation of expensive procedures and programs; however, the present work identifies safe procedures that might save resources to improve other parts in the transfusion process (e.g. electronic release to improve safety in issuing). Moreover, setting up regulations regarding ethics in transfusing recipients along with local transfusion committees are crucially needed to implement hemovigilance in transfusion practice.

Sample collection for pre-transfusion crossmatching: Benefits of using an electronic identification system

BACKGROUND

Transfusion of ABO blood group-mismatched blood or administration to the wrong recipient may result in fatal adverse events. To prevent these types of errors, various strategies have been employed. Recently, we developed a novel sample collection workflow for the pre-transfusion crossmatching test and patient recognition. This study aimed to analyse the usage of the new workflow and improvements in outcomes.

METHODS

We analysed the number of crossmatching and wrong-patient errors among the blood transfusion cases during 3 years of data collection (from August 2018 to July 2021). From May 2021 to July 2021, the new workflow was implemented. Outcomes were calculated according to the department type, patient age and processing time. The sample processing time was defined as the time from placing the order to lab arrival.

RESULTS

The new workflow utilisation increased from 50.7% to 80.3% and wrong-patient errors decreased annually. The new workflow was used for more adults (3001/3680 samples, 81.5%) than paediatric cases (345/522 samples, 65.5%; p < 0.001) and in general wards than in the emergency room or intensive care unit. The sample processing time differed according to ward type and timing of the request (day: 28.80, 2.43-3889.43 min, night: 3.36, 2.72-1671.47 min; p < 0.001).

CONCLUSION

Wrong-patient errors were reduced without increasing sample-processing time after introducing the new workflow which included using an electronic identification system. The time needed for the blood processing differed according to the ward type, patient age, and timing of the request. Patient safety can be promoted by managing these factors and using an electronic identification system.

Benefits of VISION Max automated cross-matching in comparison with manual cross-matching: A multidimensional analysis

BACKGROUND

VISION Max (Ortho-Clinical Diagnostics, Raritan, NJ, USA) is a newly introduced automated blood bank system. Cross-matching (XM) is an important test confirming safety by simulating reaction between packed Red Blood Cells (RBCs) and patient blood in vitro before transfusion. We assessed the benefits of VISION Max automated XM (A-XM) in comparison with those of manual XM (M-XM) by using multidimensional analysis (cost-effectiveness and quality improvement).

MATERIALS AND METHODS

In a total of 327 tests (130 patients), results from A-XM and M-XM were compared. We assessed the concordance rate, risk priority number (RPN), turnaround time, hands-on time, and the costs of both methods. We further simulated their annual effects based on 37,937 XM tests in 2018.

RESULTS

The concordance rate between A-XM and M-XM was 97.9% (320/327, kappa = 0.83), and the seven discordant results were incompatible for transfusion in A-XM, while compatible for transfusion in M-XM. None of the results was incompatible for transfusion in A-XM, while compatible for transfusion in M-XM, meaning A-XM detect agglutination more sensitively and consequently provides a more safe result than M-XM. A-XM was estimated to have a 6.3-fold lower risk (229 vs. 1,435 RPN), shorter turnaround time (19.1 vs. 23.3 min, P < 0.0001), shorter hands-on time (1.1 vs. 5.3 min, P < 0.0001), and lower costs per single test than M-XM (1.44 vs. 2.70 USD). A-XM permitted annual savings of 46 million RPN, 15.1 months of daytime workers' labor, and 47,042 USD compared with M-XM.

CONCLUSION

This is the first attempt to implement A-XM using VISION Max. VISION Max A-XM appears to be a safe, practical, and reliable alternative for pre-transfusion workflow with the potential to improve quality and cost-effectiveness in the blood bank.

Evaluation of a two-sample process for prevention of ABO mistransfusions in a high volume academic hospital

Background

Acute haemolytic transfusion reactions due to ABO incompatible blood transfusion remain a leading cause of transfusion-associated morbidity and mortality in the USA. Erroneous patient identification and specimen labelling account for many errors that lead to ABO mistransfusions; these errors are largely preventable.

Methods

Our hospital requires a two-sample process of ABO/Rh typing prior to transfusion. Both samples must be drawn independently. To prevent simultaneous sample draw, our second sample tube has a unique pink top that is only available from the blood bank and can only be sent to the patient’s floor once the first sample arrives in the lab. We performed an audit of this process from 19 March to 30 July 2014 and 19 March to 30 July 2015.

Results

We reviewed type and crossmatch orders for 2702 new patients during the audit period and 824 patients (30.5%) required transfusion. All patients evaluated received compatible blood, and no mistransfusions were recorded using this method. Three per cent of testing was performed incorrectly, which safely defaulted to giving type O blood.

Conclusions

The two-sample protocol used by our institution can decrease the risk of mistransfusion. Our protocol was relatively inexpensive, safe, efficient and practical for adaptation by other hospitals.

Blood transfusion: patient identification and empowerment

Positive patient identification is pivotal to several steps of the transfusion process; it is integral to ensuring that the correct blood is given to the correct patient. If patient misidentification occurs, this has potentially fatal consequences for patients. Historically patient involvement in healthcare has focused on clinical decision making, where the patient, having been provided with medical information, is encouraged to become involved in the decisions related to their individualised treatment. This article explores the aspects of patient contribution to patient safety relating to positive patient identification in transfusion. When involving patients in their care, however, clinicians must recognise the diversity of patients and the capacity of the patient to be involved. It must not be assumed that all patients will be willing or indeed able to participate. Additionally, clinicians' attitudes to patient involvement in patient safety can determine whether cultural change is successful.

Report on errors in pretransfusion testing from a tertiary care center: A step toward transfusion safety

INTRODUCTION

Errors in the process of pretransfusion testing for blood transfusion can occur at any stage from collection of the sample to administration of the blood component. The present study was conducted to analyze the errors that threaten patients' transfusion safety and actual harm/serious adverse events that occurred to the patients due to these errors.

MATERIALS AND METHODS

The prospective study was conducted in the Department Of Transfusion Medicine, Shri Maharaja Gulab Singh Hospital, Government Medical College, Jammu, India from January 2014 to December 2014 for a period of 1 year. Errors were defined as any deviation from established policies and standard operating procedures. A near-miss event was defined as those errors, which did not reach the patient. Location and time of occurrence of the events/errors were also noted.

RESULTS

A total of 32,672 requisitions for the transfusion of blood and blood components were received for typing and cross-matching. Out of these, 26,683 products were issued to the various clinical departments. A total of 2,229 errors were detected over a period of 1 year. Near-miss events constituted 53% of the errors and actual harmful events due to errors occurred in 0.26% of the patients. Sample labeling errors were 2.4%, inappropriate request for blood components 2%, and information on requisition forms not matching with that on the sample 1.5% of all the requisitions received were the most frequent errors in clinical services. In transfusion services, the most common event was accepting sample in error with the frequency of 0.5% of all requisitions. ABO incompatible hemolytic reactions were the most frequent harmful event with the frequency of 2.2/10,000 transfusions.

CONCLUSION

Sample labeling, inappropriate request, and sample received in error were the most frequent high-risk errors.

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.

Blood transfusion sampling and a greater role for error recovery

INTRODUCTION

Patient identification errors in pre-transfusion blood sampling ('wrong blood in tube') are a persistent area of risk. These errors can potentially result in life-threatening complications. Current measures to address root causes of incidents and near misses have not resolved this problem and there is a need to look afresh at this issue. PROJECT PURPOSE: This narrative review of the literature is part of a wider system-improvement project designed to explore and seek a better understanding of the factors that contribute to transfusion sampling error as a prerequisite to examining current and potential approaches to error reduction.

SEARCH STRATEGY

A broad search of the literature was undertaken to identify themes relating to this phenomenon. KEY DISCOVERIES: Two key themes emerged from the literature. Firstly, despite multi-faceted causes of error, the consistent element is the ever-present potential for human error. Secondly, current focus on error prevention could potentially be augmented with greater attention to error recovery.

CONCLUSIONS

Exploring ways in which clinical staff taking samples might learn how to better identify their own errors is proposed to add to current safety initiatives.

Harmonization of pre-analytical quality indicators

Quality indicators (QIs) measure the extent to which set targets are attained and provide a quantitative basis for achieving improvement in care and, in particular, laboratory services. A body of evidence collected in recent years has demonstrated that most errors fall outside the analytical phase, while the pre- and post-analytical steps have been found to be more vulnerable to the risk of error. However, the current lack of attention to extra-laboratory factors and related QIs prevent clinical laboratories from effectively improving total quality and reducing errors. Errors in the pre-analytical phase, which account for 50% to 75% of all laboratory errors, have long been included in the ‘identification and sample problems’ category. However, according to the International Standard for medical laboratory accreditation and a patient-centered view, some additional QIs are needed. In particular, there is a need to measure the appropriateness of all test request and request forms, as well as the quality of sample transportation. The QIs model developed by a working group of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) is a valuable starting point for promoting the harmonization of available QIs, but further efforts should be made to achieve a consensus on the road map for harmonization.

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.

Effectiveness of barcoding for reducing patient specimen and laboratory testing identification errors: a Laboratory Medicine Best Practices systematic review and meta-analysis

OBJECTIVES

This is the first systematic review of the effectiveness of barcoding practices for reducing patient specimen and laboratory testing identification errors.

DESIGN AND METHODS

The CDC-funded Laboratory Medicine Best Practices Initiative systematic review methods for quality improvement practices were used.

RESULTS

A total of 17 observational studies reporting on barcoding systems are included in the body of evidence; 10 for patient specimens and 7 for point-of-care testing. All 17 studies favored barcoding, with meta-analysis mean odds ratios for barcoding systems of 4.39 (95% CI: 3.05-6.32) and for point-of-care testing of 5.93 (95% CI: 5.28-6.67).

CONCLUSIONS

Barcoding is effective for reducing patient specimen and laboratory testing identification errors in diverse hospital settings and is recommended as an evidence-based "best practice." The overall strength of evidence rating is high and the effect size rating is substantial. Unpublished studies made an important contribution comprising almost half of the body of evidence.