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

Introduction

Errors during sampling, labelling and transport to the laboratory (pre-analytical errors) are a common problem in the laboratory and account for up to 70% of all laboratory mistakes¹. Frequent errors occurring in the pre-analytical phase include: i) identification errors, ii) errors in request procedures, iii) over- or under-filling of the specimen tube, iv) empty or missing tubes, v) contradictory demographic information on the tube and the request, (vi) ‘wrong blood in tube’ (WBIT)². The most serious error, WBIT errors, occur when the blood is taken from the wrong patient but labelled with the intended patient’s details (mis-collected) or blood is taken from the intended patient and labelled with the wrong patient’s details (mislabeled samples)³. Guidelines exist on the correct practice of phlebotomy^4–6. An observational study in 12 European countries demonstrated that compliance with phlebotomy procedures was low, with patient identification and tube labelling being the most critical steps requiring immediate action⁷.

The Testing the Utility of Collecting Blood Electronically (TUBE) study in the USA⁸, found a lower incidence of WBIT in electronically labelled samples than manually labelled samples (1:3046 compared to 1:14,606, respectively). Furthermore, the sample rejection rate for samples deviating from labelling policy was 1:67 samples, with 1:26 of mislabelled samples being possible WBIT events, therefore justifying policies which do not use mislabelled samples for analysis or cross match.

At our university hospital, the laboratory has been monitoring and recording details of the occurrence of WBIT and other sampling errors that result in the rejection of blood samples since 2010. Video recordings of doctors performing phlebotomy identified practices with the potential to lead to incorrect labelling of blood specimens⁹. Previous efforts to reduce mislabeling errors have included educational sessions with the haemovigilence officer, a zero-tolerance policy for transfusion samples, and educational campaigns to inform staff. These efforts failed to reduce the ‘baseline rate’ of sampling errors. Since the introduction of an online request clinical management system (isoft Clinical Manager, ICM) in the hospital, documented identification errors have increased despite standard education and training. This is a major concern.

Training and medical education can reduce the occurrence of pre-analytical errors including WBIT^3,10–12 but is not sufficient to eradicate WBIT. This study proposes proficiency-based progression (PBP) simulation training as a solution to reduce pre-analytical errors including WBIT. PBP is an approach demonstrated to be more effective than traditional training models in procedural skills^13–15. The study aims to compare the blood sampling error rate of interns who commenced work in Cork University Hospital (CUH) in July 2016 and did not receive PBP training in phlebotomy (historical controls) to PBP trained interventional groups who commenced work in July 2017 (intervention group 2017) and July 2018 (intervention group 2018) over three months.

Methods

Results

The baseline characteristics of the 2017 pilot study and 2018 follow-on study groups are provided in Table 2. Descriptive statistics are not available for the 2016 control group as they were not working in the hospital at the time the study started. Figure 1 provides a flow chart to illustrate the recruitment of interns and the analysis of blood tests which they performed in the trial.

Figure 1. Flow diagram of interns and the blood samples analysed in 2016 control group, 2017 intervention group, and 2018 intervention group.

There appeared to be an increase in the primary outcome, WBIT, (although the numbers detected are very small) from 0.7 per 1,000 in 2016 (three WBITs) and 0.66 per 1,000 in 2017 (three WBITs), increasing to 1.3 per 1,000 in 2018 (five WBITs). The absolute numbers make an interpretation of trends difficult. Each of the instances of WBIT was identified by the laboratory, but one of the WBITs in 2018 was identified when the doctor rang the laboratory to self-report that they had mislabeled the tube. It is possible that this type of event would have been undetected in 2016, unless there was a discrepancy with previous results available in the laboratory.

There were 4,016 blood tests performed by interns in the control group who did not receive PBP phlebotomy training from July 11^th, 2016, to September 10^th, 2016; 96 (2.4%) of the blood samples were rejected. For the same period in 2017, 4,560 tests were taken by PBP trained interns and 55 (1.2%) of the blood samples were rejected. In 2018, 3,724 tests were taken by PBP-trained interns and 72 (1.9%) were rejected. Table 3 describes the breakdown of errors that occurred.

Logistic regression analysis (Table 4) suggested that there was a 50% reduction in the odds of test rejection in the 2017 pilot study when interns underwent PBP phlebotomy training, in comparison to the 2016 control group, and this difference was statistically significant (adjusted OR=0.50, 95% CI 0.36-0.70, p<0.001). The results for 2018 showed a 11% reduction in the odds of a blood sample being rejected in the PBP trained group in comparison to 2016 control group, but this was not statistically significant (adjusted OR=0.89, 95% CI 0.65-1.21, p=0.46).

During mentorship on the wards, interns were observed performing blood sampling in their usual clinical environment. Dialogue between the mentor and the interns was structured as a series of open questions during PBP training/mentorship. Of the 45 interns who attend for PBP training on the wards, observations were recorded for 40 interns. Analysis using a theoretical domain framework revealed four themes:

Environmental context and resources: Written instructions given to the interns on the ward were noted to be poor with only one patient identifier provided. Time delays were commonly caused by label printers not working (seven cases) and unavailability of computers (eight cases). Essential equipment such as Azowipes®, tourniquets or blood tubes, were frequently missing (21 cases). Interns reported occasional instances of phlebotomy in patients who were not wearing an ID band.

Emotion: Nursing staff support on the wards contributed to calm and safe phlebotomy performance, while there were frequent interruptions by bleeps and time constraints contributed to stress, and multiple technical errors. Several interns expressed nervousness while somebody was watching them perform phlebotomy.

Knowledge: Interns had an average of 5.8 errors. They required prompting to ensure the steps of the metric were followed correctly.

Social influences: The interns appeared to be influenced by their senior colleagues, some of whom felt that labelling at the bedside and printing labels at the computer located away from the patient after taking bloods was time consuming and unnecessary extra work.

Discussion

This study demonstrated that interns who received PBP training in 2017 had significantly fewer samples rejected than in the control group. There was a 50% reduction in errors in 2017. A reduction in errors was recorded in 2018 (compared to historical controls), amounting to a 11% reduction in odds for a rejected sample which was not statistically significant. The diminished effectiveness is possibly multifactorial, including the lack of safety culture around mislabeling on the wards and environmental stressors. Due to difficulty recruiting and the large number of interns trained in July 2018, the ratio of tutors to students increased, with one tutor attempting to teach 6–12 students for some sessions. The enthusiasm around PBP training in the hospital was not as heightened in 2018, possibly due to familiarity and perceived lack of reduction in WBITs.

This study contrasts with previous research indicating the benefits of PBP training^13–15. It is a novel technique using technology-enhanced learning and simulation. Previous educational strategies tend to follow didactic-style teaching to improve phlebotomy technique and often rely on self-reported questionnaires to determine effect¹⁸. Educational strategies have been shown to reduce but not eliminate WBIT^10,11. Bar code systems that scan the patient’s wristband demonstrate a reduction in labelling errors and improve positive patient identification practices^8,19,20. Many organisations, however, do not have sufficient resources to deploy these devices; the device is aimed primarily at transfusion sampling and requires proper training to be effective. Multiple interventions and feedback are likely to be more effective than single interventions, but the sustainability of improvements is not certain from previous research¹¹. WBIT rates in mislabelled samples are estimated at 1.4%⁸, which is much higher than in correct samples, indicating that rejection of the sample due to any mislabelling event is indicative of an error-prone phlebotomy process that could have led to WBIT errors, and justifies the investigation of all blood sample errors to represent instances where there was a high risk of WBIT errors. This study demonstrates that, despite the introduction of comprehensive PBP training in phlebotomy, if the environment and process is error-prone, with the potential for shortcuts that can increase the risk of error, it is not possible to eliminate the risk of WBIT and other blood sampling errors even with optimal electronic systems. Healthcare organisations must adapt their systems to reduce distractions and tendency towards shortcuts which can lead to harm.

PBP training has robust evidence demonstrating a 40%-60% improvement in procedural performance^13–15,21. This study examines the effectiveness of the intervention for a three-month period over two years and gives a clear insight into the sustainability of the project. The development and design of the project was multidisciplinary and involved all stakeholders in developing a training programme that was highly relevant.

While in many cases the use of historical data is not ideal, the thorough, systematic nature of this data, which has been documented systematically since 2010, allows us to be confident that the 2016 historical control group is representative.

The study has several limitations. The study did not have a sufficient sample size in order to examine the effect of the intervention on WBITs, the primary outcome of interest. One doctor in the 2017 group did not attend the final assessment and three of the doctors in the study were discovered to not be using their own ICM login, and therefore these participants could not continue the study.

Interns may have been negatively influenced by mentors who had not undergone PBP training and this could have undermined and weakened the potential impact of PBP training. There was a concern that, although the interns were trained to proficiency, they did not always follow the process when unsupervised as it took longer to perform.

The qualitative element of the study identified a number of environmental factors which could potentially increase the risk of WBIT, including patients not wearing identification wristbands, difficulty accessing essential equipment, insufficient hardware and stress. These factors were persistent in all years; however, it was not possible to measure the level of these over the three years.

Given that the project was heavily promoted in the laboratory, it is possible that there was an increased awareness of WBIT, and this could have led to an increased detection rate amongst laboratory as well as ward staff. This detection bias has been described in previous studies involving WBIT, where errors increased despite the introduction of quality improvement initiatives²².

In conclusion, PBP training in phlebotomy can reduce blood sampling errors, but must take place in an environment that clearly acknowledges the importance of the training and the quality of the training must be properly resourced.

This study was unable to demonstrate if PBP training in phlebotomy influences the incidence of WBIT due to an inadequate sample size and possible detection bias.

Data availability

The underlying data (anonymised) will be made available on request for bona fide researchers, including researchers outside of UCC. Approval for data sharing was not sought at ethics approval stage nor was it included in the information sheets and consent forms provided to participants. Also, the sample size is small, and this raises the risk of potential reidentification of participants. To request access to the data please email the corresponding author, Dr Noirin O’ Herlihy- 100312258@umail.ucc.ie