Laboratory medicine contributions to patient blood management concepts

Reduction of blood volume withdrawn for laboratory diagnostic purposes

A critical review of the tubes used in the hospital was performed, followed by an assessment of the blood volumes currently needed for laboratory diagnostics following ongoing analytical and methodological developments. For this purpose, the complete analytical test profile of the laboratory was evaluated with respect to minimizing sample volumes. Tubes with lower nominal filling volumes [with the exception of ethylenediaminetetraacetic acid (EDTA) tubes for hematology and immune hematology analysis (Table 1)] were introduced as part of the process of changing from a Monovette to a Vacutainer system. For geriatric patients, hematology EDTA tube collection volumes were also reduced due to the likelihood of difficult venipunctures, whereas for all other patients there was an increase from 2.7 to 3.0 mL. The increase in EDTA immune hematology tube volumes is because for the Monovette system two tubes, each 4.9 mL, were used for blood group analysis and crossmatching of erythrocyte concentrates. This was reduced to one 6.0 mL tube in tandem with the introduction of an additional verification of the blood group in the crossmatch process in order to maintain a high level of patient safety by avoiding patient misidentification. In addition, non-gel clinical chemistry tubes were changed to gel separator tubes, leading to a higher sample yield and prolonged analyte stability. This higher yield and improved stability should reduce the need for repeated blood collection procedures, thereby affording a further saving of blood within diagnostic processes.

In order to quantify the final saving of blood in this process, two particularly vulnerable patient groups were chosen. A statistical analysis was performed by using the laboratory information system for checking all ICU laboratory assignments over a 1-month time period under initial conditions and again 1 year after the study. A stay in the ICU of at least 7 days was set as the filter criterion. For the initial 1-month query period, 32 patients met this requirement; for the 1-month query period 1 year after the study, 33 patients met the requirement. All individual laboratory assignments for these patients were checked during each patient’s complete ICU stay. The nominal volumes of the corresponding blood tubes, received in the laboratory and electronically confirmed, were recorded. The blood drawn for diagnostic purposes during each patient’s complete ICU stay was calculated on this basis, and the initial and final average diagnostic blood loss for this patient group was determined. The same approach was used for geriatric patients’ blood withdrawal profiles for a period of 1 week before the tube change (86 patients) and for 1 week 1 year after the change (84 patients).

Third, the initial and final number of tubes used hospitalwide and for ICU and geriatric patients per year was determined and the total volume of patients’ blood collected was calculated and compared.

Improvement of preanalytics

Preanalytical processes in different areas of interest were investigated in order to determine preanalytical errors, their potential to reduce blood sample quality and therefore to lead to unnecessary repeated blood collections which, in turn, leads to a delay in obtaining analytical results. In total, 54 blood collections in six representative hospital departments, including the emergency room (ER), were observed by trained specialists, using standardized questionnaires (BD Laboratory Consulting Services^®). A total of 563 blood samples were visually inspected in the central laboratory in order to evaluate if they met the criteria for sample acceptance (Table 2) (correct anticoagulant, additive tubes not underfilled, etc.).

The observed preanalytical errors were used as a base for developing hospitalwide training measures. Two kick-off events for a wide range of medical staff were performed in order to raise awareness of the impact of preanalytical errors on laboratory diagnostics and to gain acceptance for the forthcoming training. The staff received specific training on the processes associated with the preanalytical errors observed [4], [5]. After the change of blood collection equipment, an observation period of approximately 3 months was used to identify departments which needed additional training. After 1 year, a re-audit was performed, reviewing the same aspects as in the initial audit for 48 blood collections and 534 blood samples.

Quantification of the blood volume drawn

As the focus of this study was a reduction in diagnostic blood loss, a detailed evaluation was performed for two different clinical departments, both caring for patients especially prone to the development of iatrogenic anemia. For geriatric patients, particularly vulnerable due to their multimorbidity, diagnostic blood loss during 1 week was nearly halved (Table 3).

Intensive care patients are another patient group that is prone to the development of iatrogenic anemia [6], [7], [8]. In particular, patients with a longer stay in the ICU have to undergo blood tests several times a day for monitoring purposes. In this context, blood sampling for point-of-care testing (POCT) diagnostics, such as blood gas analysis (BGA), must also be considered when determining overall diagnostic blood loss.

The mean diagnostic blood loss for this group was reduced by 27.2% per week (Table 4). The fact that savings in the ICU were smaller than in geriatric patients may be partially due to the high usage of POCT BGA, which also gives information on additional parameters such as electrolytes and hemoglobin as part of the same analysis.

An estimation of diagnostic blood loss, for the entire hospital as well as for the ICU and geriatrics, was performed by comparing the total blood volume initially collected over 1 year, as measured by the number and volumes of tubes used, with that 1 year after the changes had been made. This approach is an approximation as not all of the tubes collected necessarily enter the diagnostic process. Tubes can be discarded for a number of reasons, such as the use of blood collection tubes in training courses, blood collection failures, etc. These discarded tubes cannot be excluded in this model, however they affect both calculation periods in the same manner. A correlation with hospital patient numbers per year revealed a significant saving in the number of blood collection tubes per patient used per year (Table 5). The total increase of 1% in tubes per year after the change of blood collection equipment was paralleled by a 4.9% increase in patient numbers and thereby constituted a reduction in the number of tubes per patient per day. In addition, nominal tube volumes were reduced. The total blood volume saved by means of the reduction of blood collection tube volumes was averaged at approximately 177 L per year. This corresponds to a decrease in the blood drawn for diagnostic purposes of 17.5% for all patients in the hospital. Also, the number of tubes per day and per patient were significantly reduced by 13% (Table 5). For ICU patients, tubes per patient and per day decreased slightly by 0.5%; for geriatric patients, the decrease was 4.5% (Table 5).

Reduction of the overall volume of blood collected can be converted into erythrocyte concentrate equivalents [9] for the 384-bed hospital. The average saving of 177 L blood corresponds to approximately 805 erythrocyte concentrate equivalents per year (−37%). The transfusion of erythrocyte concentrates during the 1-month time interval analyzed was reduced for ICU patients by 7.5%. For the comparison of the two geriatric patient groups, a slight increase from 0 to 3 erythrocyte concentrates was observed (Table 6).

Preanalytics on the ward

Correct identification of patients is an important aspect in avoiding unnecessary repeated blood collections. The omission of adequate patient identification carries a high risk of patient misidentification and therefore potential patient harm. In this study, it was determined whether three independent patient identification (ID) criteria were correctly checked in the identification process. Compared with the initial situation, training led to a significant improvement (3.7-fold) in patient identification using three independent ID criteria (Table 7).

Additionally, selection of the correct blood collection tube for the analysis to be performed and the correct labeling of the tubes with patient data, typically by applying barcode labels, are essential. The following non-compliances with respect to blood tube labeling, leading to a delay in laboratory analysis as these tubes require additional manual processing or cause tube rejection in the laboratory, were recorded: label was glued at an oblique angle or in a position which did not follow manufacturer’s recommendations, label stood out or label indicated a different additive to the actual tube type. After training and clarification of the importance of a correct labeling and tube choice for laboratory TAT, the initial rate of correct tube labeling almost doubled in the re-audit (Table 7).

Improvement of efficiency in the central laboratory

Initially, 563 blood collection tubes of different sample types were checked for sample quality and observed from their arrival in the laboratory until they were loaded into the appropriate analyzer. One year after the change in the blood collection equipment and training, 534 tubes were checked. Sample rejection rates have not been included in this study due to limited laboratory information system access.

As shown in Table 7, the initial rate of citrate tubes filled below 90% was already low. This had been achieved by continuous training and feedback using the hospital’s quality management system. Underfilling rates of citrate tubes 1 year after the changes had slightly increased. The rate of EDTA tubes filled below 75% also increased slightly. Further continuous training is a mandatory part of the quality management system. The rate of clinical chemistry analysis serum tubes filled below 75% was reduced slightly. In the case of lithium heparin tubes, the change was significant. The number of tubes filled more than 75% increased from 31% to 80% (Table 7).