Measures to reduce red cell use in patients with sickle cell disease requiring red cell exchange during a blood shortage

The COVID-19 pandemic has created major disruptions in health care delivery, including a severe blood shortage. The inventory of Rh and K antigen–negative red cell units recommended for patients with hemoglobinopathies became alarmingly low and continues to be strained. Because patients with sickle cell disease requiring chronic red cell exchange (RCE) incur a large demand for red cell units, we hypothesized that implementation of 2 measures could reduce blood use. First, obtaining the pretransfusion hemoglobin S (HbS) results by procedure start time would facilitate calculation of exact red cell volume needed to achieve the desired post-RCE HbS. Second, as a short-term conservation method, we identified patients for whom increasing the targeted end procedure hematocrit up to 5 percentage points higher than the pretransfusion level (no higher than 36%) was not medically contraindicated. The goal was to enhance suppression of endogenous erythropoiesis and thereby reduce the red cell unit number needed to maintain the same target HbS%. These 2 measures resulted in an 18% reduction of red cell units transfused to 50 patients undergoing chronic RCE during the first 6 months of the COVID-19 pandemic. Despite reduction of blood use, pretransfusion HbS% target goals were maintained and net iron accumulation was low. Both strategies can help alleviate a shortage of Rh and K antigen–negative red cells, and, more generally, transfusing red cell units based on precise red cell volume required can optimize patient care and judicious use of blood resources.

Management of Blood Supply and Blood Demand to Ensure International Health Security

Maintaining international health security requires proactive and reactive activities and actions to minimise the negative impact of any health event that threatens public health. Blood transfusion services are a critical part of healthcare services, and blood and blood products can neither be synthesized nor stored for a long period. So, proper management of blood supply and blood demand is mandatory to preserve adequate safe blood. A failure to manage blood inventory and the resulting blood shortage are considered national and international health security threats because maintaining an adequate supply of safe blood is lifesaving for many patients. Blood shortages lead to the failure of blood transfusion services that ends with the collapse of the health system and health insecurity if health authorities do not take immediate corrective action. An imbalance between blood supply and blood demand is not only a threat to health security, but also poses some of the greatest threats to the national and international economy and security. The perception of health issues as an international health security threat is associated with benefits through attracting political and decision-makers’ attention and support. The global health policies and international health regulations concerning the management of blood supply and blood demand should be implemented and updated regularly. The information provided by this chapter addresses the management of blood supply and blood demand as an international health security issue and provides guidance in planning for proper management of blood inventory to avoid a sudden blood shortage and its catastrophic consequences.

Bloodbuddy: a Tracking System for Blood Donor Using GPS

Blood donation is one of the most significant contributions towards the society. Millions of people need blood transfusions each year. Some may need blood during surgery. Others depend on it after an accident or because they have a disease that requires blood components. This study is aim to develop and evaluate the impact of tracking system in the blood shortage situation which is the urgent requirement of the fresh blood and to improve the communication between the hospital and donor. This system will locate the nearest blood donor in cases of emergencies in fastest and easiest way using GPS.The findings on the views of user on the aspects of interface design, navigation and functionality of the web-based application that is developed are presented. Data analysis was done based on the questionnaire received from few users which are student from Universiti Pendidikan Sultan Idris (UPSI). The findings of this study were analysed according to the objectives and the research questions of the project.

Comparison of Time Series Methods and Machine Learning Algorithms for Forecasting Taiwan Blood Services Foundation’s Blood Supply

Purpose. The uncertainty in supply and the short shelf life of blood products have led to a substantial outdating of the collected donor blood. On the other hand, hospitals and blood centers experience severe blood shortage due to the very limited donor population. Therefore, the necessity to forecast the blood supply to minimize outdating as well as shortage is obvious. This study aims to efficiently forecast the supply of blood components at blood centers. Methods. Two different types of forecasting techniques, time series and machine learning algorithms, are developed and the best performing method for the given case study is determined. Under the time series, we consider the Autoregressive (AUTOREG), Autoregressive Moving Average (ARMA), Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA, Seasonal Exponential Smoothing Method (ESM), and Holt-Winters models. Artificial neural network (ANN) and multiple regression are considered under the machine learning algorithms. Results. We leverage five years worth of historical blood supply data from the Taiwan Blood Services Foundation (TBSF) to conduct our study. On comparing the different techniques, we found that time series forecasting methods yield better results than machine learning algorithms. More specifically, the least value of the error measures is observed in seasonal ESM and ARIMA models. Conclusions. The models developed can act as a decision support system to administrators and pathologists at blood banks, blood donation centers, and hospitals to determine their inventory policy based on the estimated future blood supply. The forecasting models developed in this study can help healthcare managers to manage blood inventory control more efficiently, thus reducing blood shortage and blood wastage.