Blood Bank Management Research Articles

A Comprehensive Blood Bank Management System:Optimizing Donor and Inventory Tracki

An essential part of today's healthcare infrastructure is the Blood Bank Management System (BBMS), which makes sure that blood donations, inventories, and distribution are managed effectively and efficiently. This study provides a thorough examination of BBMS, stressing its salient characteristics, range of applications, and effects on blood bank operations. The study looks into how BBMS implementation can boost patient care, increase overall blood bank efficiency, and lead to better healthcare outcomes. This paper offers important insights into the role of technology in blood bank management through a combination of literature review, system development, and evaluation. Because they offer a consistent supply of blood products for transfusions, surgeries, and medical treatments, blood banks are essential to healthcare systems. However, issues like inventory shortages, waste, and human error are common with traditional blood bank management procedures. This paper's introduction addresses the importance of effective blood bank management and poses the following research question: Howcan blood bank operations be made more effective and efficient with the use of a blood bank management system? The study intends to advance blood bank management techniques and the general standard of patient care by addressing this question.

Hem-cloud: Revolutionizing Blood Bank Operations Through Cloud Technology

The online blood bank management web application is a useful tool which can be used in different areas of the healthcare setting such as laboratories, clinics and even emergency situations where there is a need for blood units. Because of streamlining all the operational procedures that are needed for blood donation as well as for its purchase, this system is in fact a one stop center for the management of blood operations. Important facts about the blood groups and their site cannot be missed out by users of our web. This grips up reflection ensures that in case of emergency any one even who is ready to donate or any representative of the authorized centers can quickly search and get the required blood groups. One of the main objectives of our system is also to minimize the concerns which people usually have when they are in need of blood due to its lack. Through focusing on blood systems that prevent breakdowns in ordering and using the blood, we will construct efficient systems that, together, eliminate the problems encountered in blood purchasing and usage.

BLOOD BANK MANAGEMENT STSTEM

The Blood Bank Management System (BBMS) is a comprehensive software solution designed to streamline and automate the operations of blood banks and transfusion centers. This system provides a centralized platform for managing blood inventory, donor information, blood testing, and distribution processes, thereby enhancing operational efficiency and ensuring timely access to safe blood products for patients.

The Integrated Online Application for Blood Bank and Donor Management System

Blood shortages pose a significant global health challenge, hindering medical interventions and causing preventable deaths. Traditional blood collection methods struggle to keep pace with demand, highlighting the need for a centralized and digital solution. We propose a online Blood Bank and Donor Management System (BBDMS) – a mobile application utilizing HTML, CSS, JavaScript, PHP, and SQL – to streamline blood donation and transfusion processes.

Online Blood Bank Management System

Blood donation plays a significant role in saving the lives of many people worldwide. The blood bank management system is a crucial tool for maintaining the inventory of blood donations and blood Management The System will help in the efficient management of blood donations and Blood Samples. The system allows blood banks to store and manage their data in a secure environment, providing better accessibility and scalability The web application is also designed to improve the communication between the blood bank and donors. In this System, we propose the design and implementation of a blood bank management system using a visual Studio Code. The system will also allow for tracking of donor information, blood types, and inventory records

Blood Bank Management System and Inventory Optimization

The research paper proposes an innovative approach to revolutionize blood bank management through a meticulously organized database system and a user-friendly application, aimed at addressing India's alarming shortage of blood supply. By streamlining information storage and retrieval, the system enhances efficiency and encourages consistent blood donations through timely reminders and real- time event updates for donors. For recipients, it simplifies the blood request process, particularly crucial during emergencies. This holistic approach not only tackles the immediate issue but also fosters a sustainable blood donation ecosystem, showcasing the potential of technology in addressing critical healthcare challenges and promoting community engagement in life-saving endeavours.

Distribution of ABO-Rh Blood Group System Among the Students at Shah Abdul Latif University Khairpur, Pakistan

Background: The distribution of ABO and Rh blood groups significantly varies across different populations and is crucial for effective blood bank management and transfusion services. Previous studies have shown diverse patterns in blood group distribution globally, influenced by regional, ethnic, and demographic factors. Objective: This study aimed to analyze the distribution of ABO and Rh blood groups among the student population at Shah Abdul Latif University (SALU), Sindh, Pakistan, and to understand its implications for local healthcare services. Methods: A cross-sectional study was conducted involving 253 students (133 males and 120 females) aged 18 to 24 years. Informed consent was obtained from all participants. The study employed a sterile lancet for blood sample collection via a finger prick. Blood group phenotyping was done using the slide method with monoclonal antiserum A, B, and D. Agglutination results were recorded to determine the ABO blood group and Rh factor. Data analysis was conducted using the Statistical Package for the Social Sciences (SPSS) version 25. Results: The study found that 21.7% of students belonged to blood group A (49.1% Rh positive and 5.5% Rh negative in males, 40% Rh positive and 5.5% Rh negative in females), 35.2% to blood group B (38.2% Rh positive and 6.7% Rh negative in males, 52.8% Rh positive and 2.3% Rh negative in females), 11.1% to blood group AB (57.1% Rh positive in males, 39.3% Rh positive in females), and 32.0% to blood group O (54.3% Rh positive and 2.5% Rh negative in males, 38.3% Rh positive and 4.9% Rh negative in females). Conclusion: The distribution of ABO and Rh blood groups in the student population at SALU exhibits a distinct pattern, emphasizing the importance of regional studies in blood group distribution. These findings have significant implications for blood bank management, transfusion services, and healthcare planning in the region.

E-Blood Banking System Using Cloud Computing

Abstract: Across the globe, there is an ever-increasing shortage of blood, which has led to many deaths. These losses are mainly due to the lack of a centralized blood donation system. Technologies have enhanced the efficiency and effectiveness of every aspect of the health industry, and information systems manage the distribution of blood through cloud computing. An automated system is needed to superintend the centers and provide information to interested parties. Research methodology involves a exploratory literature review and using aforesaid studies related to the ongoing situation to collect data. Our goal is to eliminate these problems through this website that satisfies all these requirements. The integrated framework includes a database for storing blood donation data in a centralized location for analysis. A database is used in this system to manage and store the data using HTML,PHP, and MySQL. In addition to educating the local community on the importance of blood donation, the website provides easy access to blood donation information, allowing hospitalsin India to store and distribute blood. As a conduit between health care systems and the public, the Arogini blood bank management system acts as a liaison. In a short period,the system will enable users to locate donors who havespecific blood groups, permit new donors to register, and help patients to request blood

Genetic prediction of 33 blood group phenotypes using an existing genotype dataset.

Accurate blood type data are essential for blood bank management, but due to costs, few of 43 blood group systems are routinely determined in Danish blood banks. However, a more comprehensive dataset of blood types is useful in scenarios such as rare blood type allocation. We aimed to investigate the viability and accuracy of predicting blood types by leveraging an existing dataset of imputed genotypes for two cohorts of approximately 90,000 each (Danish Blood Donor Study and Copenhagen Biobank) and present a more comprehensive overview of blood types for our Danish donor cohort. Blood types were predicted from genome array data using known variant determinants. Prediction accuracy was confirmed by comparing with preexisting serological blood types. The Vel blood group was used to test the viability of using genetic prediction to narrow down the list of candidate donors with rare blood types. Predicted phenotypes showed a high balanced accuracy >99.5% in most cases: A, B, C/c, Coa /Cob , Doa /Dob , E/e, Jka /Jkb , Kna /Knb , Kpa /Kpb , M/N, S/s, Sda , Se, and Yta /Ytb , while some performed slightly worse: Fya /Fyb , K/k, Lua /Lub , and Vel ~99%-98% and CW and P1 ~96%. Genetic prediction identified 70 potential Vel negatives in our cohort, 64 of whom were confirmed correct using polymerase chain reaction (negative predictive value: 91.5%). High genetic prediction accuracy in most blood groups demonstrated the viability of generating blood types using preexisting genotype data at no cost and successfully narrowed the pool of potential individuals with the rare Vel-negative phenotype from 180,000 to 70.

Blood Demand Forecasting and Supply Management: An Analytical Assessment of Key Studies Utilizing Novel Computational Techniques

Use of data-driven methodologies in enhancing blood transfusion practices is rising, leveraging big data, machine learning, and optimization techniques to improve demand forecasting and supply chain management. This review used a narrative approach to identify, evaluate, and synthesize key studies that considered novel computational techniques for blood demand forecasting and inventory management through a search of PubMed and Web of Sciences databases for studies published from January 01, 2016, to March 30, 2023. The studies were analyzed for their utilization of various techniques, and their strengths, limitations, and areas for improvement. Seven key studies were identified. The studies focused on different blood components using various computational methods, such as regression, machine learning, hybrid models, and time series models, across different locations and time periods. Key variables used for demand forecasting were largely derived from electronic health record data, including clinical related predictors such as laboratory test results and hospital census by location. Each study offered unique strengths and valuable insights into the use of data-driven methods in blood bank management. Common limitations were unknown generalizability to other healthcare settings or blood components, need for field-specific performance measures, lack of ABO compatibility consideration, and ethical challenges in resource allocation. While data-driven research in blood demand forecasting and management has progressed, limitations persist and further exploration is needed. Understanding these innovative, interdisciplinary methods and their complexities can help refine inventory strategies and address healthcare challenges more effectively, leading to more robust, accurate models to enhance blood management across diverse healthcare scenarios.

Instant Plasma Donor Management System

Abstract: Instant Plasma Donor Management System offers a first-class system to solve all the problems of blood donors and non-blood donors. Blood bank management app is a way to synchronize customers (partners) and non-customers. The world is going through the COVID 19 crisis and we haven't found a vaccine yet. However, there is another way we can help reduce the death rate or help those affected by COVID 19, and that is by donating blood from healthy patients. There is no agreement to treat the virus against the dangerous COVID-19 disease, plasma therapy is an experimental method to treat COVID-positive patients and help them recover. Treatment is seen as preventive and promising. If a person has fully recovered from COVID 19, they can donate plasma. This app will help users find blood donors or donate plasma to help others. Customers can register, log in and submit plasma gift requests with comprehensive information on their COVID 19 recovery. Customers can also voluntarily request plasma in an emergency.

Blood Bank Management System with Emergency Blood Locator

Abstract: The intention of this study is to create a blood management system for Both Android and iOS to help with the administration of blood records, and ease or control the distribution of blood in different parts of the nation based on the hospitals or recipient’s demands. Without quick and timely access to donors, this can lead to the death of the patient. If someone needs the blood, then either the person has to go to the blood bank nearby or else he has to buy the blood from the hospital, but if both places don’t have the blood of the required group, then finding the required blood group might be a tough task in those critical times. This application will help users find and select nearby source online instantly by tracing their location using GPS, and it will also reduce the time spent to a greater extent searching for blood remotely. A digital donor card will be provided to donors, as well as insurance services. Ambulance services will be arranged in case of an emergency

An evaluation of blood collection efficiency at the regional level: the case of Turkey

PurposeThe aim of this study is to analyze Turkey's blood collection efficiency at the regional level between 2018 and 2021 and discuss managerial implications.Design/methodology/approachThe authors utilize data envelopment analysis (DEA) to evaluate the efficiency scores of the 18 regions for which the Turkish Red Crescent is responsible. The data set is obtained from the General Directorate of Blood Services in the Turkish Red Crescent.FindingsThe results reveal that the efficient regions over the years did not substantially change, and regions that were consistently efficient for a four-year period are identified. Another finding is that COVID-19 did not affect the blood collection efficiency of the regions. Moreover, the findings illustrate that concentrating on the operations would contribute more to the blood collection efficiency than changing the scale size. Furthermore, the authors observe that the service population is by far the most important variable in determining the efficiency of the regions.Originality/valueIn this study, the authors present a multi-dimensional perspective on the performance evaluation of blood collection operations. In addition, the authors present blood bank managers' feedback on the performance evaluation model, outlining managerial implications. Furthermore, the authors explore the effects of the pandemic on blood collection in Turkey and illustrate the changes in efficiency throughout a distinct period that incorporates the pandemic. The study would provide a guide for blood bank managers to improve the performance of their organizations.

Development and Implementation of a Web-Based Blood Bank Management System for Efficient Blood Donation and Distribution

Abstract: Blood donation plays a significant role in saving the lives of many people worldwide. However, the traditional methods of blood bank management are time-consuming and prone to errors. To address this issue, we have developed a web application for blood bank management that can help blood banks efficiently manage their blood inventory, donor registration, and blood distribution. The web application allows the blood bank to manage the entire blood donation process electronically, from donor registration to blood collection and distribution. The web application is also designed to improve the communication between the blood bank and donors.

BLOOD BANK MANAGEMENT SYSTEM

Blood Bank Management System is a project designed to automate the differenceoperation in blood bank. This project manages and maintains the records of the donor, recipient, stock and the transaction. The modules available in this project are donor details, recipient details,stock details, transaction and other details like equipment, employee, supplier details. Donormodule have the details of new and existing donor. In recipient module, it contains the details of recipient and they request for the certain blood group through hospital. In Stock details it contains the availability of blood and equipment. In equipment module it provides the details of ordered and purchased equipment. Employee modules gives the information about the employee and their designation along with the basic pay. In supplier module, we provide supplier details. Reports can be generated for donor, recipient, stock and transaction in month wise or date-to-date. In this blood bank management system it is easy to store and retrieve the details of existing donor. This project completes the needs of the patients at the right time.

Smart monitoring, management and control of Blood bank Management System using IoT

An emergency system that directs the quick accessibility and availability of blood and delivery is entitled in a blood donation center. There exists a high demand for blood as a life saver in case of emergencies and the primary purpose of these blood donation centers meant to supply blood to the needy people. The unavailability of donor at the correct time is the foremost issue met by several people in case of emergencies. In our work, a group of people with data about their blood group and other details are made as a software for easy access. An application software has been developed where the Blood donation centers can inform about the Blood Stock and supply to people at urgent times. Since there are several steps involved in donating blood manually, the reliability and precision will be less. The proposed automatic blood bank system has been planned and developed into sector which involves sensors like temperature sensor, IR sensor, GSM module interfaced with Arduino Mega. Subsequent sector comprises of Wi-Fi module for files transference to administrator and third sector has been designed to monitor the position of existing blood stock. Entirely the web page designed narrates the obtainable blood stock in the blood bank which will be displayed on web page, so that the needy person can acquire required blood group from neighboring blood donation center.

Smart Platform for Data Blood Bank Management: Forecasting Demand in Blood Supply Chain Using Machine Learning

Despite the efforts of the World Health Organization, blood transfusions and delivery are still the crucial challenges in blood supply chain management, especially when there is a high demand and not enough blood inventory. Consequently, reducing uncertainty in blood demand, waste, and shortages has become a primary goal. In this paper, we propose a smart platform-oriented approach that will create a robust blood demand and supply chain able to achieve the goals of reducing uncertainty in blood demand by forecasting blood collection/demand, and reducing blood wastage and shortage by balancing blood collection and distribution based on an effective blood inventory management. We use machine learning and time series forecasting models to develop an AI/ML decision support system. It is an effective tool with three main modules that directly and indirectly impact all phases of the blood supply chain: (i) the blood demand forecasting module is designed to forecast blood demand; (ii) blood donor classification helps predict daily unbooked donors thereby enhancing the ability to control the volume of blood collected based on the results of blood demand forecasting; and (iii) scheduling blood donation appointments according to the expected number and type of blood donations, thus improving the quantity of blood by reducing the number of canceled appointments, and indirectly improving the quality and quantity of blood supply by decreasing the number of unqualified donors, thereby reducing the amount of invalid blood after and before preparation. As a result of the system’s improvements, blood shortages and waste can be reduced. The proposed solution provides robust and accurate predictions and identifies important clinical predictors for blood demand forecasting. Compared with the past year’s historical data, our integrated proposed system increased collected blood volume by 11%, decreased inventory wastage by 20%, and had a low incidence of shortages.

Enhancing donor acquisition and retention in blood banks via AI-powered decision support framework

Blood banks play a critical role in ensuring a steady supply of safe blood for medical procedures. However, donor recruitment and retention pose significant challenges to the sustainability of blood banks. This study proposes an AIenabled decision-support system to optimize donor recruitment and retention strategies in blood banks. The system leverages machine learning algorithms to analyze historical donor data, demographic information, and external factors to predict donor behavior and identify potential strategies for improving recruitment and retention. By incorporating AI into decision-making processes, blood banks can make data-driven decisions, enhance the efficiency of donor management, and allocate resources effectively. This paper presents the methodology used to develop the AIenabled system and discusses its potential benefits and implications for blood bank operations. Experimental results demonstrate the effectiveness of the system in identifying successful recruitment and retention strategies. Overall, the research offers valuable insights into the application of AI in blood bank management, ultimately leading to more sustainable and efficient donor recruitment and retention practices.

Red cell requisition and utilization pattern in a tertiary care hospital of South India.

The equilibrium between supply and demand for red blood cells is increasing unpredictably in many countries. An understanding of trends in blood usage profile and current usage can help predict future trends in demand and to put efforts to reduce use in particular areas. This study helps in analyzing the pattern of red blood cell utilization in a tertiary care hospital. This retrospective study was conducted in a blood bank, tertiary care hospital over a period of 6 months. All the requests coming to blood bank with information regarding patient's demographic details, diagnosis and indication for transfusion, type of request, blood transfused or returned were collected and reviewed. Crossmatch transfusion (CT) ratio, transfusion index (TI), and transfusion probability were also calculated. A total of 10,364 patients (20,399 requests) utilized total 32,608 units of blood and its components, out of those 14,195 units of packed red cells units were utilized. March month had maximum number of requests and utilization. Most of the requests for blood were from the inpatients (wards) and were requested and utilized in the age group of 21-30 years with male predominance. Patients in the division of medicine utilized most blood. Although the division of surgery requested most of the blood, on an average, they utilized only one-third of the requested product. Overall, anemia was the most common indication for red cell utilization. In surgical group, spine surgery had a maximum CT ratio. Neurosurgery and hand surgery had the lowest TI in all specialties. Hand surgery and spine surgery had a lowest transfusion probability. Overall, utilization rate in our study was 59.8%. A regular review of blood unit's usage is very important to estimate the blood utilization pattern in any hospital. Profile of blood utilization will act as indicator for quality management of blood bank.

Phenotypic and Allelic Distribution of the ABO and Rhesus Blood Groups among students at Hawassa University, Ethiopia

A prior information on the distribution of ABO and Rh groups is important for management of blood bank and transfusion, genetic counseling, anthropological studies, to study the association of blood groups and diet; to investigate the association between blood and diseases. This study aimed to determine the frequency of ABO and Rh bloods and investigate gene diversity at both loci among students in Ethiopia. A descriptive cross-sectional survey was employed involving randomly selected two thousand thirty nine (2039) university students (1054 males and 985 females) with an age range of 18–29 years. Blood groups were determined based on agglutination reaction. The most common blood group was found to be O (42.47%), followed by A (27.86%), B (21.87%), and AB (7.80 %). The frequency of Rh+ and Rh- were 90.88% and 9.12 %, respectively. The combined blood types showed O+, A+, B+ and AB+ were: 38.60 %, 25.20%, 20.10% and 7.00%, respectively. A slightly different distribution pattern of ABO blood group was observed among females from Amhara region (O> B> A>AB). The distribution of ABO phenotypes from Addis Ababa and Amhara did not differ significantly from those expected under the Hardy Weinberg Equilibrium. A high level of gene diversity was observed for both loci. In general, the O blood type is most frequent and followed by A, B and AB. A similar pattern of distribution of the ABO and Rh blood groups was found in male and female study subjects. The present study will generate baseline data that could be used in blood bank management and transfusion, genetic counseling, population genetic and anthropological studies, and for disease management.