Addressing sample identification errors in a multispecialty tertiary care hospital in Bangalore

Analysis of wrong blood in tube events at a hospital-based blood centre in a tertiary care referral hospital: A perspective from a lower middle-income country

BACKGROUND AND OBJECTIVES

Wrong blood in tube (WBIT) continues to be a preventable cause of unintended harm to the patient. The literature describing extent of the problem, its consequences and factors leading to WBIT from the perspective of lower middle-income countries (LMICs) is limited. The present study describes WBIT and its outcome in a hospital-based blood centre from an LMIC.

MATERIALS AND METHODS

WBIT events occurring during the study period were analysed to identify the root cause. In addition, they were analysed according to discipline, department and time of sample draw. Root causes were divided and compared with standard operating procedure (SOP) for sample collection for blood requests. All WBIT events were followed and their outcomes analysed.

RESULTS

WBIT events occurred at a rate of 4.8/10,000 blood requests, with a higher rate in urgent requests (5.2/10,000 requests). The average rate of WBIT was higher in surgical disciplines compared to medical and acute care services (6.58 vs. 4.43 vs. 3/10,000 requests). The highest rate of WBIT was observed when requests were received during 8:00 PM-2:00 AM (p = 0.02). Deviations from SOP with contribution from human and organizational elements were identified as the root cause. The consequences ranged from delay in providing blood to acute haemolytic transfusion reactions.

CONCLUSION

We found that WBITs occurred at a rate comparable to that reported from developed countries. Use of software and automation may reduce the rate of WBIT but not eliminate it completely. Strict adherence to SOPs and continuous training of phlebotomy staff would help reduce it to a minimum. Blood centres need to develop specific strategies with respect to their root causes.

Investigating the quality of hemovigilance process using the first two steps of Six Sigma model: a cross-sectional study

BACKGROUND AND PURPOSE

Hemovigilance is a set of monitoring methods that covers the blood transfusion chain, from collecting blood and blood products to monitoring the blood recipients. To this end, any error in this process can have serious and irreparable consequences for patients. The present study aimed to investigate the quality of hemovigilance process in Iran, using the first two steps of Six Sigma model.

METHODS

This was a quantitative cross-sectional study that was conducted over 6 months (from August 20, 2021, to February 20, 2022) at Afzalipour Hospital in Iran, using the first two steps of Six Sigma model. The study population comprised of all inpatients who needed blood or blood product transfusion in various departments of Afzalipour Hospital, among whom 477 patients were selected via stratified sampling in three shifts (morning, evening, and night). The datasheet was used to record errors in the three shifts. This research was conducted, using the DMAIC cycle's "define" and "measure" steps.

RESULTS

In the define step, the hemovigilance process at Afzalipour Hospital was divided into two categories of normal process and emergency process. Each of these processes consists of several sub-processes, including "phlebotomy," "requesting blood and blood products from the department," "preparation of application by the blood bank," " sending a request from the blood bank to the blood transfusion center," "transfusing blood and blood products," and "returning the blood and blood products to the blood bank and waste disposal." In the measure step, the quality of hemovigilance process was evaluated based on sub-processes and labels at morning, evening and night shifts. The sub-process of sending a request from the blood bank to the blood transfusion center had the highest error rate with a sigma level of 1.5. Also, the evening and night shifts had a sigma level of 1.875, and the clinical and registration labels had a sigma level of 1.875. The overall sigma level of hemovigilance process was calculated to be 2.

CONCLUSION

The results of this study showed that the quality of hemovigilance process at Afzalipour Hospital was poor. By employing the first two steps of Six Sigma method, we identified the existing errors in the hemovigilance process of Afzalipour hospital in order to assist hospital managers to take the necessary measures to improve this process.

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.

Administration Safety of Blood Products - Lessons Learned from a National Registry for Transfusion and Hemotherapy Practice

BACKGROUND

Compared to blood component safety, the administration of blood may not be as safe as intended. The German Interdisciplinary Task Force for Clinical Hemotherapy (IAKH) specialized registry for administration errors of blood products was chosen for a detailed analysis of reports.

METHODS

Voluntarily submitted critical incident reports (n = 138) from 2009 to 2013 were analyzed.

RESULTS

Incidents occurred in the operation room (34.1%), in the ICU (25.2%), and in the peripheral ward (18.5%). Procedural steps with errors were administration to the patient (27.2%), indication and blood order (17.1%), patient identification (17.1%), and blood sample withdrawal and tube labeling (18.0%). Bedside testing (BST) of blood groups avoided errors in only 2.6%. Associated factors were routine work conditions (66%), communication error (36%), emergency case (26%), night or weekend team (39%), untrained personnel (19%). Recommendations addressed process and quality (n = 479) as well as structure quality (n = 314). In 189 instances, an IT solution would have helped to avoid the error.

CONCLUSIONS

The administration process is prone to errors at the patient assessment for the need to transfuse and the application of blood products to patients. BST is only detecting a minority of handling errors. According to the expert recommendations for practice improvement, the potential to improve transfusion safety by a technical solution is considerable.

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.