BACKGROUND
In an environment of limited health care resources, it is crucial for health care systems which provide blood transfusion to have accurate and comprehensive information on the costs of ...transfusion, incorporating not only the costs of blood products, but also their administration. Unfortunately, in many countries accurate costs for administering blood are not available. Our study aimed to generate comprehensive estimates of the costs of administering transfusions for the UK National Health Service.
STUDY DESIGN AND METHODS
A detailed microcosting study was used to cost two key inputs into transfusion: transfusion laboratory and nursing inputs. For each input, data collection forms were developed to capture staff time, equipment, and consumables associated with each step in the transfusion process. Costing results were combined with costs of blood product wastage to calculate the cost per unit transfused, separately for different blood products. Data were collected in 2014/15 British pounds and converted to US dollars.
RESULTS
A total of 438 data collection forms were completed by 74 staff. The cost of administering blood was $71 (£49) per unit for red blood cells, $84 (£58) for platelets, $55 (£38) for fresh‐frozen plasma, and $72 (£49) for cryoprecipitate.
CONCLUSIONS
Blood administration costs add substantially to the costs of the blood products themselves. These are frequently incurred costs; applying estimates to the blood components supplied to UK hospitals in 2015, the annual cost of blood administration, excluding blood products, exceeds $175 (£120) million. These results provide more accurate estimates of the total costs of transfusion than those previously available.
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The COVID-19 pandemic caused >1 million infections during January-March 2020. There is an urgent need for reliable antibody detection approaches to support diagnosis, vaccine development, safe ...release of individuals from quarantine, and population lock-down exit strategies. We set out to evaluate the performance of ELISA and lateral flow immunoassay (LFIA) devices.
We tested plasma for COVID (severe acute respiratory syndrome coronavirus 2; SARS-CoV-2) IgM and IgG antibodies by ELISA and using nine different LFIA devices. We used a panel of plasma samples from individuals who have had confirmed COVID infection based on a PCR result (n=40), and pre-pandemic negative control samples banked in the UK prior to December-2019 (n=142).
ELISA detected IgM or IgG in 34/40 individuals with a confirmed history of COVID infection (sensitivity 85%, 95%CI 70-94%), vs. 0/50 pre-pandemic controls (specificity 100% 95%CI 93-100%). IgG levels were detected in 31/31 COVID-positive individuals tested ≥10 days after symptom onset (sensitivity 100%, 95%CI 89-100%). IgG titres rose during the 3 weeks post symptom onset and began to fall by 8 weeks, but remained above the detection threshold. Point estimates for the sensitivity of LFIA devices ranged from 55-70% versus RT-PCR and 65-85% versus ELISA, with specificity 95-100% and 93-100% respectively. Within the limits of the study size, the performance of most LFIA devices was similar.
Currently available commercial LFIA devices do not perform sufficiently well for individual patient applications. However, ELISA can be calibrated to be specific for detecting and quantifying SARS-CoV-2 IgM and IgG and is highly sensitive for IgG from 10 days following first symptoms.
BACKGROUND
Wrong blood in tube (WBIT) errors are a preventable cause of ABO‐mismatched RBC transfusions. Electronic patient identification systems (e.g., scanning a patient's wristband barcode before ...pretransfusion sample collection) are thought to reduce WBIT errors, but the effectiveness of these systems is unclear.
STUDY DESIGN AND METHODS
Part 1: Using retrospective data, we compared pretransfusion sample WBIT rates at hospitals using manual patient identification (n = 16 sites; >1.6 million samples) with WBIT rates at hospitals using electronic patient identification for some or all sample collections (n = 4 sites; >0.5 million samples). Also, we compared WBIT rates after implementation of electronic patient identification with preimplementation WBIT rates. Causes and frequencies of WBIT errors were evaluated at each site. Part 2: Transfusion service laboratories (n = 18) prospectively typed mislabeled (rejected) samples (n = 2844) to determine WBIT rates among samples with minor labeling errors.
RESULTS
Part 1: The overall unadjusted WBIT rate at sites using manual patient identification was 1:10,110 versus 1:35,806 for sites using electronic identification (p < 0.0001). Correcting for repeat samples and silent WBIT errors yielded overall adjusted WBIT rates of 1:3046 for sites using manual identification and 1:14,606 for sites using electronic identification (p < 0.0001), with wide variation among individual sites. Part 2: The unadjusted WBIT rate among mislabeled (rejected) samples was 1:71 (adjusted WBIT rate, 1:28).
CONCLUSION
In this study, using electronic patient identification at the time of pretransfusion sample collection was associated with approximately fivefold fewer WBIT errors compared with using manual patient identification. WBIT rates were high among mislabeled (rejected) samples, confirming that rejecting samples with even minor labeling errors helps mitigate the risk of ABO‐incompatible transfusions.
See article on page 899–902, in this issue
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Transfusion of an incorrect blood component is an important avoidable serious hazard of transfusion resulting from process errors. Our group and others have taken advantage of new technology and ...developed electronic transfusion systems for safe transfusion practice in a previous studies. They allow the clinical staff to correctly identify the patient and the blood product at the bedside, ensuring the right blood product is given to the right patient. This video is to demonstrate the process and not to promote any specific product. It is a follow up our previous video clip on electronic remote blood issue in a previous study. The process for correct patient identification originates from the wristband, which contains the patient identification details in a 2D barcode and is printed from the electronic patient record system. These details are associated with the blood sample through using a portable printer to produce a label for the sample tube. The patient details are scanned into the blood bank laboratory information system (LIS) and are then printed on a compatibility label by the LIS, which also contains a 2‐dimensional barcode, and is then attached to the blood product. Following an initial visual check of these details by the clinical staff, the electronic bedside system requires that both the patient wristband barcode and the blood product compatibility barcode are scanned. This will electronically verify at the patient's bedside that the right unit is to be given to the right patient. This is the final step in ensuring end‐to‐end electronic control and safe transfusion practice.
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This report describes the evolution of the electronic clinical decision support system (CDSS) and feedback methods at our center and the challenges and lessons learned. The electronic blood product ...order with integrated CDSS ensures collection of data regarding the patient's clinical condition and the justification for the blood product order. An alert is generated in real time if the order is placed outside agreed guidelines. We have provided feedback in several ways. We began with monthly review meetings with the junior hematology clinicians responsible for ordering blood. This was successful in reducing unjustified transfusions in this setting. We expanded the feedback to the rest of our hospitals in two ways. First, a dashboard was developed allowing visualization of ordering data by clinicians. Second, these data were summarized on a quarterly basis into a report circulated to the senior clinical staff by e‐mail. Finally, a daily report collates all orders placed for blood products that have triggered a CDSS alert from the previous day. A multidisciplinary team reviews these daily. If an order appears unjustified the specialist transfusion clinician contacts the prescribing clinician to ask for further information and, if necessary, provides education. The CDSS and feedback, allied with other patient blood management measures, have reduced total blood product costs for our hospitals by 26% over 6 years. The description of how we have developed and implemented CDSS and feedback to influence transfusion practice may be of particular value to others developing their own systems.
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BACKGROUND
Use of universally ABO‐compatible group AB plasma for trauma resuscitation can be challenging due to supply limitations. Many centers are now using group A plasma during the initial ...resuscitation of traumatically injured patients. This study was undertaken to evaluate the impact of this practice on mortality and hospital length of stay (LOS).
STUDY DESIGN AND METHODS
Seventeen trauma centers using group A plasma in trauma patients of unknown ABO group participated in this study. Eligible patients were group A, B, and AB trauma patients who received at least 1 unit of group A plasma. Data collected included patient sex, age, mechanism of injury, Trauma Injury Severity Score (TRISS) probability of survival, and number of blood products transfused. The main outcome of this study was in‐hospital mortality differences between group B and AB patients compared to group A patients. Data on early mortality (≤24 hr) and hospital LOS were also collected.
RESULTS
There were 354 B and AB patients and 809 A patients. The two study groups were comparable in terms of age, sex, TRISS probability of survival, and total number of blood products transfused. The use of group A plasma during the initial resuscitation of traumatically injured patients of unknown ABO group was not associated with increased in‐hospital mortality, early mortality, or hospital LOS for group B and AB patients compared to group A patients.
CONCLUSION
These results support the practice of issuing thawed group A plasma for the initial resuscitation of trauma patients of unknown ABO group.
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Background
Healthcare activities significantly contribute to greenhouse gas (GHG) emissions. Blood transfusions require complex, interlinked processes to collect, manufacture, and supply. Their ...contribution to healthcare emissions and avenues for mitigation is unknown.
Study Design and Methods
We performed a life cycle assessment (LCA) for red blood cell (RBC) transfusions across England where 1.36 million units are transfused annually. We defined the process flow with seven categories: donation, transportation, manufacturing, testing, stockholding, hospital transfusion, and disposal. We used direct measurements, manufacturer data, bioengineering databases, and surveys to assess electrical power usage, embodied carbon in disposable materials and reagents, and direct emissions through transportation, refrigerant leakage, and disposal.
Results
The central estimate of carbon footprint per unit of RBC transfused was 7.56 kg CO2 equivalent (CO2eq). The largest contribution was from transportation (2.8 kg CO2eq, 36% of total). The second largest was from hospital transfusion processes (1.9 kg CO2eq, 26%), driven mostly by refrigeration. The third largest was donation (1.3 kg CO2eq, 17%) due to the plastic blood packs. Total emissions from RBC transfusion are ~10.3 million kg CO2eq/year.
Discussion
This is the first study to estimate GHG emissions attributable to RBC transfusion, quantifying the contributions of each stage of the process. Primary areas for mitigation may include electric vehicles for the blood service fleet, improving the energy efficiency of refrigeration, using renewable sources of electricity, changing the plastic of blood packs, and using methods of disposal other than incineration.
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