review

Wrong blood in tube – potential for serious outcomes: can it be prevented? Paula H. B. Bolton-Maggs,1 Erica M. Wood2 and Johanna C. Wiersum-Osselton3 1

Serious Hazards of Transfusion UK National Haemovigilance Scheme, Manchester Blood Centre and the University of Manchester, Manchester, UK, 2Transfusion Research Unit, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Vic., Australia and 3TRIP National Hemovigilance and Biovigilance Office, The Hague, The Netherlands

Summary ‘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 ABOincompatible 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 endto-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. Keywords: wrong blood in tube, sampling error, blood transfusion, human factors. Blood sampling from patients, whether in hospital or in the community, is a regular and important part of healthcare. Nevertheless, as with all interventions, it is not without risk. Correctly linking the blood sample to the patient from whom it was taken is fundamental. If the sample in the tube does not belong to the patient whose name is on the tube, and this is not detected, then many different consequences may follow. This review focuses on transfusion-related consequences for patients, including the risk of incompatible blood transfusion. However, other wrongly labelled pathology samples

Correspondence: Dr Paula H. B. Bolton-Maggs, Serious Hazards of Transfusion UK National Haemovigilance Scheme, Manchester Blood Centre, Plymouth Grove, Manchester M13 9LL, UK. E-mail: [email protected]

ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

can lead to misinterpretation of a patient’s diagnosis or clinical status (Cooper & Blamey, 2003), and/or result in inappropriate actions with serious outcomes. Labelling errors on samples from blood donors can also occur and could potentially lead to adverse consequences for patients (Vuk et al, 2014). Even without actual patient harm, substantial time and effort is required to investigate and safely resolve these issues, and patients are frequently inconvenienced by requirements for sample re-collection and/or delay in therapy. Patients and staff may find their confidence in the safety of the system is undermined. Particular interest has been taken in sampling errors for transfusion because these have resulted in serious outcomes, including death due to ABO incompatibility, estimated at 1 in 600 000 red blood cell (RBC) transfusions (Sazama, 1990). Nineteen deaths have been reported to the UK haemovigilance scheme, Serious Hazards of Transfusion (SHOT), over the past 17 years, 15 between 1996 and 2004 (8 years) and only 4 between 2006 and 2013 (8 years). The current risk of an ABO-incompatible RBC transfusion is estimated at 1 in 263 157 components issued in the UK (Bolton-Maggs et al, 2014). Definitions used for sample errors are discussed below, together with detection methods and data on the frequency. It is clear that human factors (including working environment, training, communication and other factors contributing to errors) are responsible for all these events, but with increasing recognition that human factors are an unavoidable part of our human condition and healthcare delivery, the focus is on changing the process and systems in order to minimize if not eliminate them.

Definitions of wrong blood in tube Different definitions result in datasets that are not completely comparable making it difficult to monitor progress between systems and over time. The UK SHOT scheme defines ‘wrong blood in tube’ (WBIT) (SHOT, 2012) as events where: 1 Blood is taken from the wrong patient and is labelled with the intended patient’s details (in other schemes ‘miscollected’).

First published online 4 October 2014 doi:10.1111/bjh.13137

Review 2 Blood is taken from the intended patient, but labelled with another patient’s details (in other schemes ‘mislabelled’, but the term ‘mislabelled’ could include missing core identifiers or other errors which are not WBIT in SHOT). These definitions do not specify that these are only samples for transfusion; they are applied to other samples, particularly those for haemoglobin measurement where a wrong result can lead to an inappropriate transfusion (Bolton-Maggs et al, 2013). SHOT reports examine WBIT events that resulted in transfusion and also near miss events (i.e. the error was detected and there was no incorrect transfusion). The International Society for Blood Transfusion (ISBT) and International Haemovigilance Network (IHN) both use the term ‘wrong name on tube’ (WNOT), a definition restricted to samples for transfusion and includes ‘all cases where a blood sample submitted for blood group determination, irregular antibody screen and/or compatibility testing was labelled with the identification details (ID) of another patient’. This is a problem which is ubiquitous and serious. It includes all events: 1 Even if the error was detected by routine checks such as repeat blood group determination; 2 Even if the error did not lead to an incorrect transfusion (for whatever reason); 3 Even if the patient sampled was not (imminently) scheduled for transfusion.’ WNOT may include ABO-incompatible transfusion or other instances where the patient received an incorrect blood component, as well as near miss incidents. The Australian regional Serious Transfusion Incident Reporting (STIR) haemovigilance scheme defines WBIT in the context of near miss events (Department of Health, 2013): ‘this is a special category of a near miss incident where it is detected that the labelled blood sample has been collected: 1 From the wrong patient but labelled as per the intended patient. 2 From the intended patient but labelled as per another patient. 3 Or there is a mismatch between paperwork request and specimen’. Others use a definition restricted to those samples where the blood group result differed from a historical result (Dzik et al, 2003; Grimm et al, 2010). The IHN ISTARE (International Surveillance of Transfusion-Associated Reactions and Events) database defines sampling errors more widely, similarly to SHOT, as ‘all events where the name on the label of the tube was not the name of the patient whose blood was in the tube’ (http://www.ihn-org. com/haemovigilance-databases/istare-2/about-istare, accessed 3 August 2014). 4

What are the standards for sample labelling? British Committee for Standards in Haematology (BCSH) guidelines indicate that core identifiers required on a blood sample must include first name, family name, date of birth and a unique identification number (BCSH, 2009; BCSH et al, 2013). This may be a national number (for example the National Health Service [NHS] number) or a local hospital number. The local hospital number may be a problem if the patient is attending several hospitals, or has an emergency number later replaced by a hospital number. Other requirements in some hospitals or countries include the patient gender and first line of the address (Wales), and may also include date of sampling and signature of the person who took and labelled the sample. It can be very difficult to write all these details onto a paediatric 1 ml sample tube. In other countries hand-writing of labels is not regarded as essential or even recommended – for instance The Netherlands strongly recommends incorporation of a barcode or radiofrequency identification (RFID) into labels along with eye-readable identifiers (The Dutch Institute for Health Care Improvement [CBO], 2011). However labelling must be done next to the patient. Stringent criteria may be applied to samples for transfusion and not to other samples. This is not safe practice: the same standard should apply to all pathology samples for the reasons given above (Bolton-Maggs et al, 2013). A strict labelling policy is associated with a reduction in wrong samples (Lumadue et al, 1997). Where audit has been undertaken to review sample acceptance at the laboratory it is evident that, although some laboratories have apparent ‘zero tolerance’ (i.e. no changes permitted and inadequately labelled samples to be rejected), in practice some flexibility is permitted for unique or unrepeatable samples (e.g. very small babies) (Varey et al, 2013). A UK National Comparative Audit of blood sample collection and labelling reported mislabelled samples at a rate of 2
99% (133 sites) and 99 instances of miscollected samples (WBIT) (National Comparative Audit of Blood Transfusion, 2012). Although 70% of sites (154/221) had a policy of no labelling amendments or additions, a third appeared to deviate from this (National Comparative Audit of Blood Transfusion, 2012). There was description of deliberate violation of procedures – ‘it’s what we do here if not caught by the TP [transfusion practitioner]’. In common with SHOT findings, the majority of staff making errors had been competency-assessed [64% in the national audit, 67% in SHOT (Bolton-Maggs et al, 2014)]. Estimates for the rate of WBIT vary depending not only on definitions, populations and settings, but also on whether a correction factor is applied to allow for undetectable WBITs where, by chance, two samples have the same ABO and Rh blood groups [estimated at 30% in one study (Goodnough et al, 2009)]. Reported ranges are shown in Table I and vary from 1 in 1303 to 1 in 2717 with little change over time. ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

Review Table I. Rates of WBIT in selected studies.

Location

Rate of WBIT

Definition

UK, 27 hospitals

1 in 1303

International, 10 countries, 71 hospitals International, 122 institutions (95
1% USA)

1 in 1986

Blood group not matching previous record Blood group not matching previous record Blood group not matching previous record Blood group not matching previous record, clinical service notification and others Blood group not matching previous record notifications from clinical areas Self reported by 20 respondents

1 in 2500

USA Single centre over 5 years

1 in 2283

North East England, 15 hospitals over 12 months

1 in 2717

UK, national postal survey of 400 laboratories: 245 respondents France, 5-year study single blood bank for 35 hospitals Spain, single centre study over 6 months

Estimated 1 in 6000 red cell units issued 1 in 3448 1 in 2243

Blood group not matching previous record Detected by comparison with past samples

Correction factor

References

1
418

Murphy et al (2004)

1
6

Dzik et al (2003)

None

Grimm et al (2010)

None

Ansari and Szallasi (2011)

1
418

Varey et al (2013)

None

McClelland and Phillips (1994)

None

Chiaroni et al (2004)

1
4388

Gonzalez-Porras et al (2008)

Rates have a correction factor applied to allow for undetectable WBITs where, by chanc,e two samples have the same ABO and Rh groups. This varies in different populations dependent on the ABO and Rh blood group frequencies. WBIT, wrong blood in tube.

How does it occur? Several studies of WBIT events have identified common risk factors. Correct patient registration is essential (Callum et al, 2011). A significant percentage, 15
5%, of 122 hospitals (study in N America) noted incorrect registrations at least once a year (Grimm et al, 2010), and other studies noted 5% (Chiaroni et al, 2004) and 10% (Figueroa et al, 2006) of ABO mismatches were related to registration errors. Other risk factors include failure to use positive identification, labelling the samples away from the patients and patients wearing wristbands that were incorrect or changed/ removed during admission (Bolton-Maggs et al, 2013; Varey et al, 2013; Bolton-Maggs et al, 2014). Where the patient is unconscious or unable to identify him/herself a rigorous protocol for ‘unknown patient identification’ is required which should include sex and a unique number together with approximate age (BCSH, 2013) and a process to manage updating wristband, hospital and laboratory information when patient identity can be established.

most near miss WBIT events (Bolton-Maggs et al, 2013). In an audit of 15 hospitals, samples taken by doctors and labelled away from the bedside were identified as the most common risk factors for WBIT (occurring in 44%) (Varey et al, 2013). In a study from Northern Ireland, medical staff were implicated in 422/759 (55%) near miss events (Lundy et al, 2007). Sample collection was the first error in 468 events, mainly incorrectly or unlabelled samples. Doctors were responsible for 19/26 WBIT (Lundy et al, 2007) related to failure to correctly identify the patient and/or label away from the bedside. However, systems failures contributed to these events, including inability to provide electronically generated wristbands and case record numbers out of hours, and absent interfaces between laboratory and clinical computer systems. Another study in emergency departments noted ‘junior doctors appear to lack knowledge about the potential for error, a situation reinforced by a culture that openly accepts doctors not following protocols’ (Jeffcott, 2010).

Errors by all groups of staff Unsafe practice, particularly by medical staff National (National Comparative Audit of Blood Transfusion, 2012) and local (Varey et al, 2013) UK audits show that doctors were the staff group most likely to make errors (22%), and phlebotomists were much less likely, at 5%. SHOT data repeatedly show that phlebotomy by doctors (44
2%) and failure to label at the bedside (45
9%) are responsible for ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

Failure to properly identify the patient at the bedside when collecting blood samples is a recurring and major problem. Critical steps in the ID check are omitted, incorrectly performed or not performed at all (Soderberg et al, 2010; Nilsson et al, 2014). ‘Positive’ patient ID is often not done (where the conscious patient is asked to state his/her name and date of birth, rather than simply agreeing with a stated 5

Review name provided by staff). Medical staff may not have been taught this and the importance of patient ID was a notable omission in the UK Foundation Schools curriculum published in 2012 (http://www.foundationprogramme.nhs.uk/ download.asp?file=FP_Curriculum_2012_WEB_FINAL.PDF), now amended (http://www.foundationprogramme.nhs.uk/ download.asp?file=FINAL_Proposed_minor_modifications_ to_the_Foundation_Programme_Curriculum_2014_final.pdf, Accessed 4 September 2014). Hospitalized patients should be wearing ID wristbands in line with national and institutional policies (National Patient Safety Agency [NPSA], 2007), but a national audit in the UK (247 sites, 9250 transfusions) showed that 2
3% of patients being transfused were not wearing wristbands, more commonly in children (9
5%) and neonates (12
9%) than in adults (1
3%) (National Comparative Audit of Blood Transfusion, 2011). This trend towards misidentification in paediatrics was also shown by others; WBITs were more commonly found in paediatrics (4
7 per 10 000 samples) than in any other specialty (range 0
8 in trauma to 3
5 per 10 000 samples in medicine) (Varey et al, 2013). Neonates may not have a first name other than ‘baby’ and are likely to have the same date of birth as others in the same unit; samples from twins are mixed up and SHOT has also noted several instances of WBIT in children (44/77 near miss events in 2013 including confusion of maternal and baby samples in 37 instances) (Bolton-Maggs et al, 2014). An Australian regional audit of 1595 transfusions in 82 hospitals found that outpatients or day patients attending for transfusion were less likely than inpatients (90% vs. 99%) to be wearing wristbands (Department of Health, 2012). Hospital protocols require that samples be labelled by the collector after collection but before leaving the patient. However, breaches of protocol are common. Use of pre-labelled tubes is unacceptable; they are easily misplaced and mixed up with tubes for another patient. Similarly, failure to label the sample before leaving the patient contributes to WBIT events, including when patients are transferred out of a treatment area and unlabelled samples left behind are tagged with another patient’s details from pre-printed labels still available. The risk of these events is greater in areas with rapid patient turnover, such as emergency or radiology departments or delivery suites. Staff may try to assist each other by labelling samples they did not collect. In some circumstances (e.g. samples accessed from sterile central lines) this may be unavoidable but a process must be in place to ensure correct labelling. Human factors research identifies that contributing factors to WBIT cases include interruptions, distractions and fatigue (Health and Safety Executive [HSE], 1999), which are pervasive in hospitals. Interruptions to physicians in emergency departments occurred at a rate of 6
6 per h and were associated with failure to complete tasks (Westbrook et al, 2010). A human factors study of WBIT events in three Australian emergency departments confirmed these findings in relation 6

to patient ID and sample labelling, and further identified institutional safety culture, teamwork and feedback processes and physical environment (e.g. ready access to all necessary equipment and materials necessary for collecting pre-transfusion samples) as important contributors to errors (Jeffcott, 2010). Nevertheless, most samples are collected in a routine setting, such as a ward or outpatient clinic (69% in a UK national audit [National Comparative Audit of Blood Transfusion,2012]) and errors still occur frequently under these conditions.

How common is it? Trained phlebotomists (who perform these patient ID and sampling tasks constantly) appear to have fewer WBIT errors, but they do still occur, usually due to distraction or other factors during critical steps. A study of 147 laboratories (3
3 million specimens) demonstrated an error rate of 2
7/1000 samples where there was no dedicated phlebotomy service, but this was reduced to 1
1/1000 with a dedicated phlebotomy service (Wagar et al, 2008). In some countries, for instance The Netherlands, laboratory phlebotomy staff collect nearly all samples, even out of hours. SHOT data demonstrate that near miss events account for about a third of all reports each year (996/2595 in 2013) and most of these are WBIT samples (643/996 in 2013) (BoltonMaggs et al, 2014). Similar results are seen from Australia, where between 2009 and 2011, WBIT accounted for 28% of all cases reported to the STIR programme (Department of Health, 2013). Over the past 4 years SHOT data show that about 1 in 100 WBIT samples results in a wrong transfusion (Table II). The number of reported WBIT near miss incidents has increased year on year; this may in part be due to both an increased culture of reporting reflected in the overall increase in reports, and improved quality management systems in hospital laboratories. BCSH guidelines (BCSH, 2013) now recommend a group-check sample (i.e. a second, independent blood sample to confirm the ABO group unless secure electronic identification systems are in place) for patients about to receive their first transfusion, but it is too soon to determine if this has led to the apparent reduction in WBIT leading to wrong transfusion noted in 2013 (Bolton-Maggs et al, 2014). In The Netherlands, where the group-check sample has been in place since before the inception of the Transfusion Reactions in Patients (TRIP) (2007) Dutch haemovigilance scheme in 2002, there has been only Table II. Wrong blood in tube samples reported to SHOT detected prior to transfusion (near miss) or resulting in a wrong transfusion (Bolton-Maggs et al, 2014). Year

2010

2011

2012

2013

Near miss IBCT

388 3

469 5

505 6

643 0

IBCT, incorrect blood component transfused. ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

Review one incorrect transfusion resulting from WBIT (details in Table III).

How is it discovered? WBIT samples are typically discovered when laboratory testing determines that the current blood group is different to the previously recorded one. However, changes in results of typically stable RBC parameters, such as mean cell volume, can alert laboratory staff to a potential sample collection or labelling error. Other methods include realization in the clinical area that the wrong patient has been sampled, or RBC were crossmatched for a patient who had not been sampled nor required transfusion. Where patients attend several hospitals, sharing hospital laboratory data will increase safety. The Pittsburgh group have described the benefit of access to a centralized transfusion service (CTS) database, sharing previous blood group results, which has prevented some mistransfusions (MacIvor et al, 2009). The CTS covers 16 hospitals. Over two years, 16 miscollected samples were identified; in 6 the current and historical groups were from different hospitals. In 3 cases, an ABO-incompatible transfusion would have resulted (e.g. correct type O, current type A). Thus 38% more ABO typing errors were detected and six mistransfusions prevented (3 would have been ABO compatible). These could not have been prevented at a single institution. Another US study of a centralized database noted detection of 5/19 WBIT where the historical group at another hospital was different (Delaney et al, 2013) and 10
9% of patients had been tested or transfused at more than

one hospital. Sharing is also advocated in England with a national RBC immunology register (Specialist Services Electronic Reporting using Sunquest ICETM; Sp-ICE) between specialist red cell laboratories and hospitals who can sign up to participate (Bolton-Maggs et al, 2013). STIR recommended development of an Australian regional or national antibody register to help prevent delayed haemolytic transfusion reactions, and this would also probably help by providing historical blood group information for recurrently transfused patients (Department of Health, 2013). In The Netherlands, such a national antibody database was launched in 2007. By 2012 it was being used by the majority of hospital transfusion laboratories. All affiliated laboratories may consult (only) on behalf of patients currently under treatment; the database is being prospectively populated by the reference laboratories and hospitals (http://www.sanquin.nl/ producten-diensten/diagnostiek/trix/). In some instances, a WBIT results from a patient deliberately using another person’s ID, for example, an individual not entitled to healthcare using a family member’s identity to seek emergency or obstetric care. Discrepant results are found compared to an historical blood group on file. The historical blood group correctly belongs to one person, and the current result correctly belongs to the person from whom the blood was taken, but this is not the same person despite the sample being collected under the same name. SHOT noted two instances of wrong identity in 2013 (Bolton-Maggs et al, 2014). In another instance an unconscious woman was wrongly identified by the credit card she carried which belonged to her mother (Bolton-Maggs et al, 2013).

Table III. Some case examples of WBIT events. Types of error

Case descriptions

Two errors result in WBIT and an incompatible transfusion (TRIP, 2004)

A pre-registration house physician sent two samples from a single venepuncture as if they were independent, not understanding the rationale behind the group-check policy. This doctor had failed to correctly identify the patient; the patient had a reaction to the incompatible transfusion but nursing staff responded alertly when the patient’s temperature increased, stopping the transfusion in time to prevent major haemolysis. Two patients were sampled at the same time in a pre-operative clinic. The nurse was distracted while bleeding the first patient and so did not complete the process at his side and transposed the details onto samples for another patient. One patient had a previous historical group which was different so the WBIT was detected, but the other had not been tested previously and received 4 units of incompatible blood in the context of cardiac surgery resulting in haemolysis and an extended stay in the intensive care unit. A transcription error was made by a bed manager when admitting a patient. The incorrect identifiers were then used for records and identification band; the patient was confused and unable to identify himself. The details belonged to a different patient with the same year of birth. So although the correct patient was bled (who had a previous anti-Jka antibody), the identifiers used belonged to the other patient with a different transfusion history: Jka antigen negative blood was not selected and the patient developed evidence of a delayed haemolytic transfusion reaction. An urgent full blood count sample was labelled away from the patient with another patient’s barcode. The patient was transfused with two units of red cells and one pool of platelets. The error was discovered on further testing the next day when a normal platelet count was found.

One error results in two WBIT events, one a near miss and the other results in an ABO-incompatible transfusion (Bolton-Maggs et al, 2013)

Patient identification error on admission (Bolton-Maggs et al, 2013)

WBIT samples for full blood counts can result in inappropriate transfusion (Bolton-Maggs et al, 2013)

TRIP, (Transfusion and Transplantation Reactions in Patients) National hemovigilance and biovigilance office; WBIT, wrong blood in tube. ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

7

Review

What are the consequences?

How can WBIT be prevented?

Unfortunately, some WBIT events only become apparent when a transfusion reaction occurs. ABO-incompatible transfusions may cause death (6
7%) or serious harm (27%) - cumulative data analysed by SHOT (Bolton-Maggs et al, 2014). These numbers are remarkably consistent with data from France, 7
06% mortality and 28% major morbidity from their mandatory haemovigilance scheme between 1994 and 1998 (Andreu et al, 2002). However, 66
3% (187/282) of ABO-incompatible transfusions reported to SHOT resulted in no or few symptoms and therefore could be missed. Where the ABO group happens to be the same as or compatible with the patient, other specific requirements could be missed, particularly specific phenotypes for patients with sickle cell disease who are particularly likely to be admitted to multiple hospitals. Failure to provide appropriately phenotyped RBC units for such patients, or those known to have alloantibodies, is a potentially preventable cause of antibody development and haemolytic transfusion reactions which are a significant cause of morbidity and death in this population (BoltonMaggs et al, 2014). Where the WBIT sample is for a haemoglobin determination or coagulation screen, the wrong result may lead to an inappropriate transfusion of RBC or other components. Nine cases of WBIT full blood counts were reported by SHOT in 2012. Six patients received RBC that they did not need, two received platelets (one also with RBC: see Table IV) and in one case, transfusion was delayed because results were not available – the correct patient was bled but the sample labelled with another patient’s details (BoltonMaggs et al, 2013). Inappropriate RBC transfusions carry the additional risk of transfusion-associated circulatory overload, which is associated with significant morbidity and mortality (Bolton-Maggs et al, 2014). WBIT biochemistry samples may also have very serious consequences with wrong results leading to potentially dangerous interventions, for example inappropriate electrolyte or insulin administration. When a WBIT is recognized prior to testing the sample should be discarded and not tested. When a WBIT is detected as a result of a discrepant blood group result a further sample should be obtained to confirm which is the correct result. Ideally, results should not be released until the issue is resolved, or if already issued, results should be withdrawn and re-issued with clinical comment to document the event. The Dutch transfusion guideline (The Dutch Institute for Health Care Improvement (CBO), 2011) describes procedures for the double blood group check and states that detection of an ABO discrepancy should lead to investigation of the cause. In cases of misidentified samples, standard procedures should be available and adhered to in deletion of the incorrect ABO results and ensuring correctly established (concordant) results prior to issue of ABO-compatible RBC.

Potential solutions include wider use of trained phlebotomists, additional staff training (NPSA, 2006), audit with feedback and the development of new technology (Murphy et al, 2011a). Patient ID must be robust and, wherever possible, the patient should be asked to state his/her name and date of birth. ID bands should be electronically generated. Misidentification may occur when an emergency department issues an ID number which is replaced by a full hospital number later, or patients are identified by different numbers in different hospitals. Two countries in the international Biomedical Excellence for Safer Transfusion (BEST) collaborative study of sample collection have national patient ID numbers (Sweden, 21 hospitals participating; Finland, 5 hospitals participating); this was associated with very low miscollected sample rates (Dzik et al, 2003). There was an overall high rate of mislabelled samples (1 in 165) in this study. Others have demonstrated that mislabelled specimens rejected by a transfusion laboratory were also 40 times more likely to also be WBIT (>47 000 specimens in a 1-year period were reviewed) (Lumadue et al, 1997). There should be a policy of ‘zero tolerance’ for labelling of all blood samples, not just those for transfusion (BoltonMaggs et al, 2013), with at least the core identifiers, i.e. first name, family name, date of birth and unique identification number (national if possible). The addition of the sex of the patient, time sampled and some way to identify the sampletaker are also advisable. European Union Directives require institutions to have robust policies for sample acceptance and labelling and laboratories should monitor their sample rejection rates. These data should be provided to hospital management and transfusion committees to ensure that results are reviewed and action taken. The UK audit noted that ‘consistent application of national recommendations for sample labelling and acceptance across both hospitals and reference laboratories would be a major contribution to improving patient safety’ (National Comparative Audit of Blood Transfusion, 2012). A statistical process control is recommended which can operate at a regional or national level as a tool for developing standards (Dzik et al, 2008). If printed labels are used for blood samples, in line with institutional or national policies in some countries, these should be printed immediately prior to use and/or there should be some other mechanism for ensuring that the labels are for the intended patient. Blood sampling and labelling should be performed as a single continuous procedure, as recommended in national guidelines (BCSH, 2009, 2013). Patients should be encouraged to participate in ID and labelling processes for their samples with explanation about why this is so important for all parts of their hospital journey. In the UK the Patient Blood Management team of NHS Blood and Transplant has launched a campaign to raise awareness of this, designated ‘Do you know who I am?’ (Joint UK Blood Transfusion and Tissue Transplantation Services Professional Advisory Committee, 2012).

8

ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

Review Table IV. Main causes of WBIT and strategies for their mitigation. Causes of WBIT

Strategies to reduce WBIT incidence

Comments

Failure of correct identification of the patient at initial registration Failure to perform phlebotomy correctly, particularly medical staff

Careful attention to patient identification detail on admission Phlebotomists for all transfusion samples

Particular risks associated with newborn infants including twins Routine in The Netherlands. Doctors consistently show highest rate of WBIT Inconsistent cover in medical curricula at all levels: need to improve effectiveness of training Difficult to achieve but training in increased situational awareness is essential

Medical or other staff failure to label samples at the bedside

Failure to correctly identify patients

Improve transfusion training in medical education programmes at all levels Recognition of the role of human factors in medical practice; reduction in multitasking and distraction Rigorous compliance with use of core identifiers on all samples. Rejection of all mislabelled samples. Training with competency assessments for all staff recommended in the UK since 2005 Positive patient identification at all contacts by all staff: to be specifically covered in training Confirmation of ABO group on a second independent sample Confirmation of ABO group at the bedside by nursing staff End-to-end electronic identification

Reduction in deaths from ABO-incompatible transfusions associated with this and the introduction of European Union Directives in the UK

Frequently missed out; staff (especially doctors) commonly deviate from protocols Group-check sample adopted in many places and recommended in the UK since 2013 France and Germany; method itself prone to errors Reduced incidence of error but expensive to put in place and not widely adopted

WBIT, wrong blood in tube.

Transfusion training and assessment are now part of medical education and training in undergraduate, postgraduate and specialty curricula in the UK, but are not well standardized and are under review. However, all these measures still do not prevent errors occurring. SHOT and other data confirm that the majority of staff responsible for error have been competency-assessed (Varey et al, 2013; Bolton-Maggs et al, 2014). In other countries the basic transfusion training in the core medical (and paramedical) curriculum is also not yet felt to be sufficient – the results of haemovigilance reporting in The Netherlands have led to calls for increased time devoted to transfusion training (2007 and still standing in later reports). Novel approaches to training incorporating simulation and other techniques should continue to be explored. Two further steps have evidence of benefit and increased safety. These are the policy of obtaining a group-check sample for patients who have not been previously grouped or transfused, prior to transfusion, and the development of endto-end computer solutions.

A group-check sample policy Direct observations of staff performing phlebotomy repeatedly show failure in positive patient ID and labelling away from the patient (Jeffcott, 2010; Alimam et al, 2014; Thomas et al, 2014). As ABO grouping is the most important part of pretransfusion testing, BCSH guidelines recommend that ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

‘unless secure electronic patient identification systems are in place, a second sample should be requested for confirmation of the ABO group of a first time patient prior to transfusion, where this does not impede the delivery of urgent RBC or other components’ (BCSH, 2013). In other countries, e.g. Netherlands, France, the requirement for a second sample is extended to all situations. A two-sample policy can be introduced without significant impact on workload or increased use of O RhD-negative blood and without delays to transfusion (Thomas et al, 2014). This study showed that 86% of patients who required transfusion had a historical blood group. However, although introduction of such group-check policies can reduce the consequences they do not eradicate WBIT errors. Another study following its introduction found three such errors in the next 10 months, two of which would have been ‘silent’ (both groups were O RhD positive) (Ansari & Szallasi, 2011). Prior to introduction of a two-sample policy in California, 40 miscollected (WBIT) samples were identified by difference from the historical group, together with 86 mislabelled samples that were rejected and not tested (Goodnough et al, 2009). Some potential barriers to implementation were identified, mainly the resources required. However, the estimated risk reduction using two independent samples was from 1 in 630 (corrected) to 1 in 396,000. The impact on use of group O RhD negative RBC was minimal and there were no complaints. The authors noted that this policy was not designed to correct errors in patient ID/labelling (an acknowledgement that human factors 9

Review will always occur) but rather to neutralize them (Goodnough et al, 2009). Another centre identified a corrected WBIT rate of 1 in 3713 for the years 2000–2003. A two-sample policy had been in place since 1987 and was reviewed in 2003, during which time a total of 94 WBITs were identified, 61 by discrepant groups, 26 by the clinical area and 7 by other methods (Figueroa et al, 2006). Interestingly, in 14 cases the checkgroup sample was the wrong one, but this hospital uses prelabelled blood bank-generated tubes for the group-check and all were caused by failure of patient ID at the time of sampling. The use of prelabelled tubes is not recommended. An alternative is to use unlabelled tubes supplied from the laboratory placed in a bag with the patient details on it, requiring the sampler to write the patient identifiers on the sample using the locally recommended method to label the tubes at the time of phlebotomy and in immediate proximity to the patient. France and Germany have adopted an additional approach. In France, legislation requires an ABO compatibility test to be performed by the nurse at the bedside immediately before transfusion (Migeot et al, 2002; Daurat, 2008). However it is clear that errors are made in these tests [31
5% (Migeot et al, 2002)] so these authors stressed a continued need for additional robust mechanisms and the continued use of this test has been challenged (Levy, 2008). Bedside ABO testing has also had some success in India (Sindhulina & Joseph, 2014).

Electronic solutions Human factors can be reduced by removing human interventions as far as possible from a process, but even the assistance of technology does not guarantee an error-proof process. Barcode ID is used widely in the retail industry and has been routinely available in laboratories for sample ID as automation has increased. Electronic systems have been demonstrated to reduce transcription errors and thereby reduce the risk of WBIT (Turner et al, 2003) but are expensive to set up. In the UK, the Oxford Hospitals have led the field in developing end-to-end electronic ID for patients and their blood components. The aims were to improve patient safety by reduction in errors, reduce inappropriate use of blood with resultant cost savings, facilitate monitoring of transfusion practice and improve the efficiency of transfusion. This system uses 2-dimensional barcodes on the patients’ ID wristbands, on the blood samples and blood components. These barcodes contain the patient core ID details. Hand-held computers (which also identify users and timings) are used at the bedside with prompts to complete all the essential steps. Full implementation (in 2007) followed a series of pilot studies. This change required significant financing (including purchase of the hardware and employment of a system manager) but resulted in a reduction in blood usage, more rapid supply with electronic issue (Staves et al, 2008) and savings in nurse and laboratory time (Oxford University Hospitals, 2011). In 10

addition, pre- and post-implementation audits showed improved positive patient ID from 11
5% to 100%, improvement in the checking of ID bands, increased sample labelling at the bedside, from 42% in inpatients to 100% and increased correct labelling, from 88% to 100% (Davies et al, 2006). The WBIT rate reduced, from 1 in 12 322 samples prior to its introduction to 1 in 26 690 afterwards (Murphy et al, 2012). An additional advantage of information technology (IT) methods is that, providing linkage back to the transfusion laboratory system can be implemented, the actual administration of the transfusion is confirmed, dispensing with the need for further methods for the mandatory documentation of traceability. In hospitals where transfusion is currently not confirmed back to the laboratory, the adoption of bedside technology is an alternative to paper forms for traceability. Another centre using barcode technology noted a sample collection error avoided every 7
6 days, and estimate that a barcode system was 15–20 times safer than manual processes (Askeland et al, 2008, 2009). Despite these advantages, few hospitals have implemented this method, mainly because of cost (Murphy et al, 2011b). However electronic systems must be used correctly; a report from Japan (Miyata et al, 2011), reviewing 12 years use of an electronic system for bedside confirmation that the component was the correct one for the recipient, noted that although two transfusion errors were prevented (wrong components delivered), two near misses occurred. In one case a doctor ignored the system warning and in the other, the checked component was connected to a neighbouring patient. A fatal ABO mismatch was also reported where the electronic step of confirmation was omitted. RFID has been suggested as a simpler alternative. Barcode reading is not always easy at the patient’s side – the nurse has to hold the ID band with one hand and the scanner in the other. Blood bags have a confusing array of different barcodes (Dzik, 2007). RFID tags hold more information and passive tags are cheap and disposable. Comprehensive guidelines with full explanation of this technology and its applications have been published with a view to potential use in transfusion (Knels et al, 2010). It remains to be seen whether this technology is widely implemented. Clearly, the initial costs and complexities have been disincentives for many institutions, but there is potential for safety improvements across a broad range of clinical settings (medication safety, surgical and radiological procedural matching etc.) with these technologies, which may enhance their future adoption. Other risk-reducing methods have been reviewed (Callum et al, 2011), which may help reduce, but do not eliminate, error. Another suggestion is to have two people check the patient ID at the time of sampling but this is labour intensive and although the WBIT rate is reduced it is not eliminated (Quillen & Murphy, 2009). Other novel technology suggestions are the use of fingerprint ID in association with an IT system (Bennardello et al, 2009) or scanning of palm vein patterns (Lawrence, 2009). ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

Review

Do any of these interventions work? A systematic review concluded that although there is some evidence that all the interventions reduced WBIT, data collection has been insufficient to demonstrate sustainability (Cottrell et al, 2013). From more than 12,000 initial references, 128 were studied in more detail but only 9 were included. The range of time for data collection was 1
9–12 years but most were relatively short-term, up to 3 years. Among the limitations, the authors noted that none of the studies had determined the sample size needed to show a significant effect on WBIT rates. Five reports studied single interventions and four multiple (2 or 3) interventions. Single interventions included improved sample labelling and the introduction of a fully electronic system. Multiple interventions included focus on correct labelling, education and introduction of confirmatory blood grouping, but none of the 4 studies included the same features. A general conclusion was that multiple interventions and feedback are likely to be more effective than single interventions (Cottrell et al, 2013). Among all the national haemovigilance systems, to date (as far as we are aware) it is only SHOT in the United Kingdom and the French system which have reported a decline in the incidence of ABO-incompatible transfusions. In neither country has there been widespread uptake of IT methods to avoid sampling and transfusion errors, again suggesting that multiple interventions have, together, led to the desired improvement.

Recommendations for further research Human factors research applied to transfusion practice It is clear that most instances where wrong components are transfused result from human errors, or at least a human factors contribution. This term is preferred with the acknowledgement that it is not possible to eliminate all errors but rather to focus on means of catching and preventing adverse outcomes. SHOT reports have noted every year that most reported incidents are caused by mistakes in the transfusion process [77
6% of all reports in 2012 and 2013 (BoltonMaggs et al, 2013; Bolton-Maggs et al, 2014)]. A short checklist can reduce morbidity and mortality in surgery (Haynes et al, 2009) and is recommended for the bedside check in transfusion (Bolton-Maggs et al, 2014). Many incidents result from multiple errors [SHOT notes a range of 1 to 5, median 3 in 220 cases of wrong component transfusion in 2013 (Bolton-Maggs et al, 2014)]. Human factors training for healthcare staff is now recommended in the UK (House of Commons Health Committee, 2009; NHS England, 2013). It is evident that despite protocols and guidelines, staff involved in the transfusion process often do not follow correct procedures, sometimes because it is impossible for them to do so because of complex environmental and system factors (Jeffcott, 2010; Alimam et al, 2014). As recommended ª 2014 John Wiley & Sons Ltd British Journal of Haematology, 2015, 168, 3–13

in the Annual SHOT Report for 2013, the complex multidisciplinary transfusion process requires a fresh look and process redesign (Bolton-Maggs et al, 2014).

Implementation science approach to improving effectiveness of education/training and processes in hospital It is necessary to understand how feedback from audits may be better applied and a National Institute for Health Research-funded programme, the development of enhanced ‘Audit and Feedback Intervention to Increase the uptake of evidence-based Transfusion practice’ (AFFINITIE) is being developed (Grant-Casey, 2014). This research will review how the current UK National Comparative Transfusion Audit programme reports influence clinical practice and randomize hospitals to receive different interventions for audit and feedback.

Conclusion WBIT and similar events continue to be very common, and while serious or fatal outcomes are relatively uncommon, this is more by chance than good management and optimal systems, and patients continue to be harmed from transfusion-related errors. The key causes and strategies for their mitigation are shown in Table IV. Transfusion is a multistep process which needs to be re-examined and re-engineered in line with evidence that some steps are particularly vulnerable and difficult to complete as recommended. Humans are error-prone and cannot be made perfect. Healthcare professionals are trying to do the right thing, but errors still occur even after training and competency-assessment. Some technological solutions are already available but have not been widely adopted, largely because of costs. Safe transfusion still depends on strict adherence to standard operating procedures reinforced by appropriate checklists. Patient samples labelled with wrong patient details, whether blood or any other tissue, continue to be a hazard for patients and the same identification standards should apply to all, not just transfusion samples. The use of a group-check sample and IT end-to-end control offer the best opportunities to improve transfusion process safety, but need full audit before and after introduction to really demonstrate their benefits. Sharing the results of these interventions will continue to highlight problems, define standards and suggest novel solutions.

Acknowledgement All three authors contributed to the review, suggesting sources of data. Jo Wiersum performed a formal search of the literature, and all three contributed to the writing of the paper. None of the authors have any conflicts of interest.

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Review

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