Digitally enabled hemovigilance allows real time response to transfusion reactions.

BACKGROUND: Transfusion carries a risk of transfusion reaction that is often underdiagnosed due to reliance on passive reporting. The study investigated the utility of digital methods to identify potential transfusion reactions, thus allowing real-time intervention for affected patients. METHOD: The hemovigilance unit monitored 3856 patients receiving 43,515 transfusions under the hemovigilance program. Retrospective comparison data included 298,498 transfusions. Transfusion medicine physicians designed and validated algorithms in the electronic health record that analyze discrete data, such as vital sign changes, to assign a risk score during each transfusion. Dedicated hemovigilance nurses remotely monitor all patients and perform real-time chart reviews prioritized by risk score. When a reaction is suspected, a hemovigilance trained licensed clinician responds to manage the patient and ensure data collection. Board-certified transfusion medicine physicians reviewed data and classified transfusion reactions under various categories according to the Centers for Disease Control hemovigilance definitions. RESULTS: Transfusion medicine physicians diagnosed 564 transfusion reactions (1.3% of transfusions)-a 524% increase compared to the previous passive reporting. The rapid response provider reached the bedside on average at 12.4 min demonstrating logistic feasibility. While febrile reactions were most diagnosed, recognition of transfusion-associated circulatory overload demonstrated the greatest relative increase. Auditing and education programs further enhanced transfusion reaction awareness. DISCUSSION: The model of digitally-enabled expert real-time review of clinical data that prompts rapid response improved recognition of transfusion reactions. This approach could be applied to other patient deterioration events such as early identification of sepsis.

A Quality Approach to Reducing the Occurrence of Occluded Leukocyte Reduction Filters During Platelet Transfusion.

BACKGROUND: In 2019, an increase in clotted platelet filter occurrences was noted with the implementation of new leukocyte reduction filters through a volumetric pump. LOCAL PROBLEM: Occluded platelet filters contribute to delays in platelet transfusions, additional nursing workflows, and potential wastage of platelets, leading to staff and patient dissatisfaction. METHODS: Direct observation of nursing practice with priming platelet filters identified opportunities for improvement. Education was designed incorporating manufacturer recommendations with results of the observations. Nursing education was disseminated through small group sessions, one-to-one teaching, tip sheets, and an e-learning video. RESULTS: Nursing education interventions resulted in a 170% reduction in the reported monthly filter occlusion rate. CONCLUSION: Engagement of nurses in quality improvement processes and collaboration across departments led to a sustained decrease in the clotted platelet filters.

Oncology Patients Who Develop Transfusion-Associated Circulatory Overload: An Observational Study.

BACKGROUND: Transfusion-associated circulatory overload (TACO) is a largely preventable transfusion complication that results in significant morbidity and mortality. Cancers, related treatments, and comorbidities are among the factors that can predispose patients to TACO, but currently there are limited data on this topic in the literature. METHODS: We collected data retrospectively from the electronic health records of 93 adult patients with cancer who met Centers for Disease Control and Prevention (CDC) criteria for TACO from July 1, 2019, through October 31, 2020. The parameters we studied included demographics, comorbidities, treatment modalities, transfusion practices, and outcomes. We summarized data by means and ranges for continuous variables, and proportions for categorical variables. RESULTS: During the study period, the incidence of TACO among oncology patients was 0.84 per 1000 transfusions (95% CI, 0.68-1.02), representing 6.6% of all reactions. This percentage is high, compared with 1%-6% among other populations. Unique characteristics such as hematology malignancy (75.3%), receipt of cardiotoxic chemotherapy (87.1%), pneumonia (57.0%), preexisting oxygen use (59.1%), dyspnea (62.4%), hypertension (55.9%), renal insufficiency (46.2%), daily use of corticosteroids (43.0%), daily use of diuretics (40.9%), daily use of beta-blockers (36.6%), and elevated NT-proBNP (33.3%) were frequently observed in these group of oncology patients. CONCLUSIONS: Our study indicates that oncology patients have unique factors that may lead to diagnosis of TACO. Developing appropriate guidelines that apply to oncology patients, in addition to those set forth by the CDC, should be considered. Implementation by ordering healthcare providers of a tools that can predict TACO can help in early recognition and mitigation of TACO.