Sample collection and sample handling errors submitted to the transfusion error surveillance system, 2006 to 2015

Transfusion-related errors and associated adverse reactions and blood product wastage as reported to the National Healthcare Safety Network Hemovigilance Module, 2014-2022

BACKGROUND

Transfusion-related errors are largely preventable but may lead to blood product wastage and adverse reactions, resulting in patient harm. In the United States, the incidence of transfusion-related errors is poorly understood nationally. We used data from the National Healthcare Safety Network (NHSN) Hemovigilance Module to describe and quantify transfusion-related errors, as well as associated transfusion-related adverse reactions and blood product wastage.

METHODS

During 2014-2022, data from the NHSN Hemovigilance Module were used to analyze errors, including near misses (errors with no transfusion), incidents (errors with transfusion), and associated serious adverse reactions (severe, life-threatening, or death).

RESULTS

During 2014-2022, 80 acute care facilities (75 adult; 5 pediatric) reported 63,900 errors. Most errors occurred during patient blood sample collection (21,761, 34.1%) and blood sample handling (16,277, 25.5%). Less than one-fifth of reported errors (9822, 15.4%) had a completed incident form. Of those, 8780 (89.3%) were near misses and 1042 (10.7%) incidents. More than a third of near misses (3363, 38.3%) were associated with a discarded blood product, resulting in 4862 discarded components. Overall, 87 adverse reactions were associated with errors; six (7%) were serious.

CONCLUSIONS

Over half of the transfusion-related errors reported to the Hemovigilance Module occurred during blood sample collection or sample handling. Some serious adverse reactions identified were associated with errors, suggesting that additional safety interventions may be beneficial. Increased participation in the Hemovigilance Module could enhance generalizability and further inform policy development regarding error prevention.

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.

Adding Automation and Independent Dual Verification to Reduce Wrong Blood in Tube (WBIT) Events

OBJECTIVES

Transfusions remain a complicated procedure involving many disciplines performing various steps. Pretransfusion specimen identification errors remain a concern. Over the past two decades, system changes have been made and minimal improvements in the error rates have been seen. Wrong blood in tube (WBIT) events may lead to mistransfusions of components with life-threatening complications.

METHODS

A continuous quality improvement effort involving the introduction of electronic patient identification at the point of pretransfusion specimen collection (an automated system improvement), manual independent dual verification, and periodic education (human process system improvements) were implemented.

RESULTS

Both automated and human system process improvements resulted in greater than 10-fold reduction in WBIT events and a 47% reduction in mislabeled specimens.

CONCLUSIONS

Diligent improvement and implementation of combination automated system processes and human protocols with continuous monitoring led to great reductions in WBIT error rates and labeling discrepancies, leading to an increase in system safety. These combinations of improvement can lead to more decreased error rates if applied to other critical process steps in the transfusion process.

Implementation of a blood bank generated tube for second blood group determination: Challenges, yield, and cost

Background

The second blood group determination or group check sample is a process of verifying the ABO group with a second blood sample prior to transfusion. It has been used to detect errors related to wrong blood in tube (WBIT) events and reduce the risk of ABO‐incompatible transfusions. To prevent the clinical team from collecting the group check sample at the same time as the first sample, a tan top tube only available from the blood bank was introduced for second blood group determinations if drawn within 24 h of the first group and screen.

Study design and methods

This is a retrospective study analyzing data from 2005 to 2020 before and after the implementation of the blood bank supplied tan top tube for group check. The number of WBIT events, transfusion delays, and health care costs were determined.

Results

The number of WBIT events remained unchanged throughout the time period. No delays in transfusion or procedure were reported due to the tan top tube group check. There was no increase in group O transfusions over time. In comparison to using an ethylenediaminetetraacetic acid (EDTA) tube, the tan top tube was estimated to add an extra yearly cost of $790.79 Canadian dollars.

Conclusion

Second blood group determination using the blood bank supplied tan top tube did not increase the number of WBIT events detected but ensured an independent sample draw. A minimal incremental cost of implementing the tan top tube was noted with no delay in transfusions or procedures.

Proficiency-based progression intern training to reduce critical blood sampling errors including ‘wrong blood in tube’

Background: Blood sampling errors including ‘wrong blood in tube’ (WBIT) may have adverse effects on clinical outcomes. WBIT errors occur when the blood sample in the tube is not that of the patient identified on the label. This study aims to determine the effect of proficiency-based progression (PBP) training in phlebotomy on the rate of blood sampling errors (including WBIT). Methods: A non-randomised controlled trial compared the blood sampling error rate of 43 historical controls who had not undergone PBP training in 2016 to 44 PBP trained interventional groups in 2017. In 2018, the PBP training programme was implemented and the blood sampling error rate of 46 interns was compared to the 43 historical controls in 2016. Data analysis was performed using logistic regression analysis adjusting for sample timing. Results: In 2016, 43 interns had a total blood sample error rate of 2.4%, compared to 44 interns in 2017, who had error rate of 1.2% (adjusted OR=0.50, 95% CI 0.36-0.70; <0.01). In 2018, 46 interns had an error rate of 1.9% (adjusted OR=0.89, 95% CI 0.65-1.21; p=0.46) when compared to the 2016 historical controls. There were three WBITs in 2016, three WBITs in 2017 and five WBITs in 2018.  Conclusions: The study demonstrates that PBP training in phlebotomy has the potential to reduce blood sampling errors. Trial registration number: NCT03577561

Digital Microfluidic Hemagglutination Assays for Blood Typing, Donor Compatibility Testing, and Hematocrit Analysis

BACKGROUND

Blood typing, donor compatibility testing, and hematocrit analysis are common tests that are important in many clinical applications, including those found in high-stakes settings such as the trauma center. These tests are typically performed in centralized laboratories with sample batching; the minutes that are lost in this mode can lead to adverse outcomes, especially for critical-care patients. As a step toward providing rapid results at the bedside, we developed a point-of-care hemagglutination system relying on digital microfluidics (DMF) and a unique, automated readout tool, droplet agglutination assessment using digital microfluidics (DAAD).

METHODS

ABO and Rhesus blood grouping, donor crossmatching, and hematocrit assays were developed on a portable DMF platform that allowed for automated sample processing. The result of each assay could be determined by eye or automatically with the DAAD imaging tool.

RESULTS

DMF-DAAD was applied to 109 samples collected from different sources (including commercial samples, pinpricks from volunteers, and a hospital blood bank), with perfect fidelity to gold-standard results. Some of these tests were carried out by a nonexpert in a hospital trauma center. Proof-of-concept results were also collected from smaller sample sets for donor compatibility testing and hematocrit analysis.

CONCLUSION

DMF-DAAD shows promise for delivering rapid, reliable results in a format well suited for a trauma center and other settings where every minute counts.

Factors associated with wrong blood in tube errors: An international case series - The BEST collaborative study

BACKGROUND

A wrong blood in tube (WBIT) error signifies a blood sample that does not match the patient identified on the sample label. WBIT errors can result in ABO mistransfusions.

STUDY DESIGN AND METHODS

In this international, multicenter, descriptive study, healthcare facilities provided detailed information on WBIT errors occurring from 1/1/2019 to 12/31/2020. Factors contributing to WBIT errors were classified as protocol violations, knowledge gaps, and slips/lapses.

RESULTS

331 WBIT errors were compiled from 36 centers in 11 countries. WBIT errors were most frequently detected through pretransfusion sample testing (191, 58%), with 38 (20%) detected by a second ("check") sample. WBIT errors were divided almost evenly between intended patient drawn/wrong label applied (166, 50%) and wrong patient drawn/intended label applied (158, 48%). Information on contributing factors was available for 260 WBIT errors; most involved a combination of protocol violations and slips/lapses (139, 53%). The most frequent contributing factor was another patient's sample labels or tubes being available during phlebotomy (61%). Protocol violations were more likely to result in wrong patient being drawn (p = .0007). In 43 WBIT errors, electronic positive patient identification (ePPID) was not used when available or was used incorrectly.

CONCLUSIONS

Protocol violations and slips/lapses frequently contribute to WBIT errors. Sample collection processes should be designed to minimize error opportunities; staff should be educated on why protocol compliance is critical for patient safety. Using ePPID does not eliminate all WBIT errors. Institutions using ePPID may elect to require check sample verification as an added safety measure.

Proficiency-based progression intern training to reduce critical blood sampling errors including ‘wrong blood in tube’

Background: Blood sampling errors including ‘wrong blood in tube’ (WBIT) may have adverse effects on clinical outcomes. WBIT errors occur when the blood sample in the tube is not that of the patient identified on the label. This study aims to determine the effect of proficiency-based progression (PBP) training in phlebotomy on the rate of blood sampling errors (including WBIT). Methods: A non-randomised controlled trial compared the blood sampling error rate of 43 historical controls who had not undergone PBP training in 2016 to 44 PBP trained interventional groups in 2017. In 2018, the PBP training programme was implemented and the blood sampling error rate of 46 interns was compared to the 43 historical controls in 2016. Data analysis was performed using logistic regression analysis adjusting for sample timing. Results: In 2016, 43 interns had a total blood sample error rate of 2.4%, compared to 44 interns in 2017, who had error rate of 1.2% (adjusted OR=0.50, 95% CI 0.36-0.70; <0.01). In 2018, 46 interns had an error rate of 1.9% (adjusted OR=0.89, 95% CI 0.65-1.21; p=0.46) when compared to the 2016 historical controls. There were three WBITs in 2016, three WBITs in 2017 and five WBITs in 2018.  Conclusions: The study demonstrates that PBP training in phlebotomy has the potential to reduce blood sampling errors. Trial registration number: NCT03577561

Emergency departments are higher-risk locations for wrong blood in tube errors

BACKGROUND

Wrong blood in tube (WBIT) errors can lead to ABO mistransfusions. It is unknown if WBIT errors are more likely in specific healthcare locations or if specific collection practices influence the commission of WBIT errors.

STUDY DESIGN AND METHODS

Data on pretransfusion samples from calendar year 2019 were collected retrospectively by 39 transfusion services in nine countries. We compared the proportion of WBIT errors made in emergency departments (EDs), inpatient wards, and outpatient clinics.

RESULTS

In total, 143 WBIT errors were detected among 1,394,862 samples for an unadjusted aggregate WBIT proportion of 1.03/10,000 samples. Using a pooled random effects model, the WBIT proportion was estimated to be significantly higher in EDs (1.23/10,000 samples, 95% CI 0.62-2.43) than inpatient wards (0.71/10,000, 95% CI 0.44-1.14; p < .001) or outpatient clinics (0.24/10,000, 95% CI 0.08-0.65; p < .001) and significantly higher in inpatient wards than outpatient clinics (p = .043). The use of electronic positive patient identification (ePPID) systems was associated with a significantly lower WBIT proportion in the ED (odds ratio, OR: 0.32, 95% CI: 0.11-0.96, p = .041), but not in inpatient wards (OR: 0.45, 95% CI: 0.20-1.01, p = .054) or outpatient clinics (OR: 1.95, 95% CI: 0.39-9.74, p = .415).

DISCUSSION

Normalized for the number of samples drawn per location, the WBIT proportion in EDs was 1.7 times higher than inpatient wards and 5.1 times higher than outpatient clinics. EDs represent higher-risk clinical locations for WBIT errors, and electronic positive patient identification (ePPID) may provide a greater impact on safety in EDs relative to other clinical areas.

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.

Registration errors among patients receiving blood transfusions: a national analysis from 2008 to 2017

BACKGROUND AND OBJECTIVES

The key first step for a safe blood transfusion is patient registration for identification and linking to past medical and transfusion history. In Canada, any deviation from standard operating procedures in transfusion is an error voluntarily reportable to a national database (Transfusion Error Surveillance System [TESS]). We used this database to characterize the subset of registration-related errors impacting transfusion care, including where, when and why the errors occurred, and to identify frequent high-risk errors.

MATERIALS AND METHODS

A retrospective analysis was conducted on transfusion errors reported to TESS by sentinel reporting sites relating to patient registration and patient armbands, between 2008 and 2017. Free-text comments describing the error were coded to further categorize into common error types. The number of specimens received in the transfusion laboratory was used as the denominator for rates to allow for comparison between hospital sites.

RESULTS

Five hundred and fifty-four registration errors were reported from 10 hospitals, for a global error rate of 5·4/10 000 samples (median 5·0 [interquartile range 3·7-7·0]). The potential severity was high in 85·7% of errors (n = 475). The patient experienced a consequence in 10·8% of errors (n = 60), but none resulted in patient harm. Rates varied widely and differed by nature across sites. Errors most commonly occurred in outpatient clinics or procedure units (n = 160, 28·8%) and in emergency departments (n = 130, 23·5%).

CONCLUSION

Registration errors affect transfusion at every step and location in the hospital and are commonly high risk. Further research into common root causes is warranted to identify preventative strategies.

Proposing a Model for the National Hemovigilance Information System in Iran

The present study aimed to propose a model for the national hemovigilance information system with a database approach, considering the importance and necessity of developing an information system for such a network.

This is an applied, descriptive, and cross-sectional study, which was conducted in 2018. The research population comprised hemovigilance information systems in advanced countries, including the USA, UK, Australia, and France. Data were collected from library sources and the Internet from 2000 to 2018. The proposed model for the national hemovigilance information system was introduced using comparative tables and based on the similarities and differences of systems in the studied countries. The proposed model was then validated using the two-step Delphi technique through a researcher-made questionnaire whose validity was confirmed, and reliability was approved by a Cronbach’s alpha of 94%.

The final model of the national hemovigilance information system comprised five main components: goals, organizations involved in the blood transfusion process, databases of blood transfusion organizations, data transfer flow between the databases of blood transfusion organizations, and transferable datasets, and hemovigilance-related committees. This model was approved by experts with an >85% agreement coefficient.

The national hemovigilance information system with a database approach can improve blood transfusion health by providing access to reliable sources on blood transfusion complications to everyone, especially the medical community. Thus, it is essential to implement this standard accurately and precisely control the practical methods of this process based on international guidelines.

A survey of blood transfusion errors in Aichi Prefecture in Japan: Identifying major lapses threatening the safety of transfusion recipients

BACKGROUND

Despite recent progress in blood systems, transfusion errors can occur at any time from the moment of collection through to the transfusion of blood and blood products. This study investigated the actual statuses of blood transfusion errors at institutions of all sizes in Aichi prefecture.

MATERIALS AND METHODS

We investigated 104 institutions that perform 98 % of the blood transfusions in Aichi prefecture, and investigated the errors (incidents/accidents) that occurred at these facilities over 6 months (April to September, 2017). Incident/accident data were collected from responses to questionnaires sent to each institution; these were classified according to the categories and risk levels.

RESULTS

Ninety-seven of the 104 institutions (93.3 %) responded to the questionnaire; a total of 688 incidents/accidents were reported. Most (682 cases; 99.2 %), were classified as risk level 2; however, 6 were level 3 and over, which included problems with autologous transfusion and inventory control. Approximately one-half of the incidents/accidents (394 cases; 57.3 %), were related to verification and the actual administration of blood products at the bedside; more than half of these incidents/accidents occurred at large-volume institutions. Meanwhile, a high frequency of incidents/accidents related to transfusion examination and labeling of blood products was observed at small- or medium-sized institutions. The reasons for most of these errors were simple mistakes and carelessness by the medical staff.

CONCLUSIONS

Our results emphasize the importance of education, operational training, and compliance instruction for all members of the medical staff despite advances in electronic devices meant to streamline transfusion procedures.

Implementation and Effectiveness of a Bar Code-Based Transfusion Management System for Transfusion Safety in a Tertiary Hospital: Retrospective Quality Improvement Study

Background

Large-scale and long-term studies are not sufficient to determine the efficiency that IT solutions can bring to transfusion safety.

Objective

This quality-improvement report describes our continuous efforts to implement and upgrade a bar code–based transfusion management (BCTM) system since 2011 and examines its effectiveness and sustainability in reducing blood transfusion errors, in a 3000-bed tertiary hospital, where more than 60,000 prescriptions of blood transfusion are covered by 2500 nurses each year.

Methods

The BCTM system uses barcodes for patient identification, onsite labeling, and blood product verification, through wireless connection to the hospital information systems. Plan-Do-Study-Act (PDSA) cycles were used to improve the process. Process maps before and after implementation of the BCTM system in 2011 were drawn to highlight the changes. The numbers of incorrect labeling or wrong blood in tube incidents that occurred quarterly were plotted on a run chart to monitor the quality changes of each intervention introduced. The annual occurrences of error events from 2011 to 2017 were compared with the mean occurrence of 2008-2010 to determine whether implementation of the BCTM system could effectively reduce the number of errors in 2016 and whether this reduction could persist in 2017.

Results

The error rate decreased from 0.03% in 2008-2010 to 0.002% in 2016 (P<.001) and 0.001% in 2017 (P<.001) after implementation of the BTCM system. Only one incorrect labeling incident was noted among the 68,324 samples for blood typing, and no incorrect transfusions occurred among 67,423 transfusion orders in 2017.

Conclusions

This report demonstrates that continuous efforts to upgrade the existing process is critical to reduce errors in transfusion therapy, with support from information technology.

A regional massive hemorrhage protocol developed through a modified Delphi technique

BACKGROUND

A massive hemorrhage protocol (MHP) enables rapid delivery of blood components in a patient who is exsanguinating pending definitive hemorrhage control, but there is variability in MHP implementation rates, content and compliance owing to challenges presented by infrequent activation, variable team performance and patient acuity. The goal of this project was to identify the key evidence-based principles and quality indicators required to develop a standardized regional MHP.

METHODS

A modified Delphi consensus technique was performed in the spring and summer of 2018. Panellists used survey links to independently review and rate (on a 7-point Likert scale) 43 statements and 8 quality indicators drafted by a steering committee composed of transfusion medicine specialists and technologists, and trauma physicians. External stakeholder input from all hospitals in Ontario was sought.

RESULTS

Three rounds were held with 36 experts from diverse clinical backgrounds. Consensus was reached for 42 statements and 8 quality indicators. Additional modifications from external stakeholders were incorporated to form the foundation for the proposed MHP.

INTERPRETATION

This MHP template will provide the basis for the design of an MHP toolkit, including specific recommendations for pediatric and obstetrical patients, and for hospitals with limited availability of blood components or means to achieve definitive hemorrhage control. We believe that harmonization of MHPs in our region will simplify training, increase uptake of evidence-based interventions, enhance communication, improve patient comfort and safety, and, ultimately, improve patient outcomes.