Healthcare Management Problems Research Articles

Disease Prevalence among Cattle and Knowledge of Farmers Regarding Health Management and Livestock Technology in Developing Countries: Evidence from Bangladesh

This study aims to investigate the prevalence of cattle disease and the knowledge of farmers regarding health management and livestock technology in Bangladesh as a paradigm of developing countries. Data were collected via face-to-face interviews between December 2020 and June 2021 from 301 randomly selected farmers from three districts in Bangladesh. Foot and Mouth (FMD) was the predominant disease in the study cattle. About 45% of cattle in Dhaka and 40% of cattle in Rajshahi were infected with FMD while Diarrhea (33%) and bloat (33%) were most prevalent in cattle from Sirajganj. Although the majority of respondents practiced regular vaccination and deworming for cattle, they had significantly less knowledge of vaccination and deworming. Moreover, there is a significant difference in regular practice and knowledge of farmers about vaccination among our study areas (p<0.007). FMD vaccine use was significantly higher among farmers of Dhaka (p<0.016) while the use of Black quarter (p<0.003) and Hemorrhagic septicemia (p<0.001) vaccines were significantly higher among farmers of Rajshahi. Most of the respondents provided prophylactic care by themselves or with the help of quacks while dependent on quacks or registered veterinarians for treatment. Half of the farmers faced various problems in health care management including the high prevalence of diseases (60%). Fifty-two percent of subjects from Dhaka had received different training such as cattle rearing and animal health and 84% of them implemented received training. The results of this study demonstrated that more awareness and training are needed regarding healthcare management and technology adoption in developing countries like Bangladesh for obtaining sustainable livestock production.

Russian-language publication activity of medical researchers in during the COVID-19 pandemic: “post-COVID-19 syndrome”

Aim. To study the dynamics and pattern of publications in Russian on post-COVID-19 syndrome (PCS) in order to assess the completeness of information and identify medical specialties with its most active investigation in Russia.Material and methods. The search for publications was carried out in the database of the largest digital scientific library in Russia Elibrary.ru from February 1, 2021 to February 1, 2022. The study included publicly available medical publications on the consequences of coronavirus disease 2019 (COVID-19) in Russian. Publications were classified according to subject matter, study design, and evidence hierarchy. The data obtained is reflected using integers, percentages and graphs.Results. The study included 478 publications, of which 196 (41%) presented data from original studies, while 269 (56,3%) reflected the results of existing sources. Expert community documents accounted for 2,7%. In terms of study design, most of original studies described case series (37,2%) and individual case reports (22,4%). Casecontrol studies accounted for 20,4%, cross-sectional studies — 8,7%, prospective cohort studies — 3,6%, randomized clinical trials — 1,5%, and systematic reviews — 1%. In addition, 5,1% of publications were devoted to preclinical studies, mathematical models and various methodological aspects. By topic, the largest number of publications noted cardiovascular (12,2%) and neurological manifestations of PCS (12,2%). Furthermore, 23,5% of publications described the course of PCS in specific groups of patients, particular issues of COVID-19 consequences, and healthcare management problems. We also revealed that 11,7% of publications were devoted to general rehabilitation, 71% — to imaging diagnostics, 5,6% — to herd immunity to the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARSCoV-2), and 5,6% — to PCS features in children. The smallest number of publications considered mental (5,1%), gastroenterological (4,6%), pharmacological (4,6%), rheumatological (4%) and pulmonological aspects of PCS.Conclusion. The dynamics and pattern of publications on COVID-19 in Russian are generally consistent with global trends and reflect the natural consequences of the pandemic. This analysis of publications on PCS showed that the most in-demand specializations in this filed are cardiology, neurology, and rehabilitation.

AN AHP BASED OPTIMAL DISTRIBUTION MODEL AND ITS APPLICATION IN COVID-19 VACCINATION

COVID-19 is causing a large number of causalities and producing tedious healthcare management problems at a global level. During a pandemic, resource availability and optimal distribution of the resources may save lives. Due to this issue, the authors have proposed an Analytical Hierarchy Process (AHP) based optimal distribution model. The proposed distribution model advances the AHP and enhances real-time model applicability by eliminating judgmental scale errors. The model development is systematically discussed. Also, the proposed model is utilized as a state-level optimal COVID-19 vaccine distribution model with limited vaccine availability. The COVID-19 vaccine distribution model used 28 Indian states and 7 union territories as the decision elements for the vaccination problem. The state-wise preference weights were calculated using the geometric mean AHP analysis method. The optimal state-level distribution of the COVID-19 vaccine was obtained using preference weights, vaccine availability and the fact that a patient requires exactly vaccine doses to complete a vaccination schedule. The optimal COVID-19 vaccine distribution along with state and union territory rank, and preference weights were compiled. The obtained results found Kerala, Maharashtra, Uttarakhand, Karnataka, and West Bengal to be the most COVID-19 affected states. In the future, the authors suggest using the proposed model to design an optimal vaccine distribution strategy at the district or country level, and to design a vaccine storage/inventory model to ensure optimal use of a vaccine storage center covering nearby territories.

Designing a closed-loop blood supply chain network considering transportation flow and quality aspects

Managing blood and its sub-products is one of the challenging problems in healthcare management, where the managers attempt to solve them by designing appropriate supply chain networks. Although previous authors tried to enhance the performance of the blood supply chain, some critical concepts such as reusable blood transportation boxes were rarely considered. These boxes are the crucial apparatus in the transmission of products along the supply chain. As such, it is vital to discuss the related flow and quality features in the network using a mathematical formulation. Moreover, a closed-loop network design to achieve more economical and environmental benefits than a traditional design is a more efficient approach. Regarding these concerns, a closed-loop supply chain of blood products that considers blood transportation equipment and the relevant quality features is formulated in this paper first. Then, a differential evolution algorithm (DE), boosted by extending two new versions of DE, is used for solving the problem. Finally, some sensitivity analyses on the parameters of the model are performed to report some managerial insights.

Genetic algorithm for obstacle location-allocation problems with customer priorities

In this paper we propose a metaheuristic approach to solve a customer priority based location-allocation problem in presence of obstacles and location-dependent supplier capacities. In many network optimization problems presence of obstacles prohibits feasibility of a regular network design. This includes a wide range of applications including disaster relief and pandemic disease containment problems in healthcare management. We focus on this application since fast and efficient allocation of suppliers to demand nodes is a critical process that impacts the results of the containment strategy. In this study, we propose an integrated mixed-integer program with location-based capacity decisions that considers customer priorities in the network design. We propose an efficient multi-stage genetic algorithm that solves the problem in continuous space. The computational findings show the best allocation strategies derived from proposed algorithms.

ADOPTING AN OPEN SOURCE HOSPITAL INFORMATION SYSTEM TO MANAGE HEALTHCARE INSTITUTIONS

Our paper is a comparative study of different Open Source Hospital Information Systems (OSHISs). We chose open source because of problems in healthcare management like budget, resources and computerization. A literature review did not allow us to find a similar comparison, which explains the great interest of our study. Firstly, we retrieved nine OSHISs: MediBoard, OpenEMR, OpenMRS, OpenHospital, HospitalOS, PatientOS, Care2x, MedinTux and HOSxP. Then, we used the DeLone & McLean model to evaluate information systems qualities and the SQALE method for the technical evaluation. Finally, we get OSHISs activities using open source community statistics. In application, we used SonarQub as a SQALE implementation. As results, we get six characteristics for MediBoard (respectively OpenEMR, OpenMRS, OpenHospital, HospitalOS, PatientOS, Care2x, MedinTux and HOSxP), with a technical debt of 42.16% (respectively 53.23%, 54.5%, 65%, 66.1%, 65.2%, 56.96%, 52.13% and 75.5%). Activities statistics prove the MediBoard potential with 2381 commits and 12 contributions in 2016. Based on these results, we chose MediBoard as a solution to adapt in healthcare organizations. It is also a challenge to prove open source power in health management. As a future work, we will implement and test MediBoard modules in a real case. Article DOI: https://dx.doi.org/10.20319/lijhls.2017.33.3857 This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

Evolutionary radial basis function network for gestational diabetes data analytics

The development of smart decision support systems (DSSs) that seek to simulate human behavioral aspects is a major challenge for computational intelligence (CI). Artificial neural network (ANN) approaches have the ability to solve complex decision-making problems that involve uncertainty and a large amount of information in a fast and reliable way. The application of this evolutionary CI technique to analyze a large amount of data is an important strategy to solve several problems in healthcare management. This paper proposes the modeling, performance evaluation, and comparison analysis of an ANN technique known as the radial basis function network (RBFNetwork) to identify possible cases of gestational diabetes that can lead to multiple risks for both the pregnant women and the fetus. This method achieved promising results with a precision of 0.785, F-measure of 0.786, ROC area of 0.839, and Kappa statistic of 0.5092. These indicators show that this ANN-based approach is an excellent predictor for gestational diabetes mellitus. This research provides a comprehensive decision-making model capable of improving the care provided to women who are at a risk of developing gestational diabetes, which is the most common metabolic problem in gestation with a prevalence of 3–18%. Thus, this work can contribute to the reduction of maternal and fetal mortality and morbidity rates.

Handling uncertainty in health care management using the cardinality-constrained approach: Advantages and remarks

Different approaches have been proposed in the literature to handle uncertain parameters in health care optimisation problems. Among them, the cardinality-constrained approach to robust optimisation seems suitable for handling several of these problems because it allows a trade-off between the level of robustness and the cost of the solution, and an easy implementation that can be understood by clinicians and planners without any background in operations research. Thus far, however, cardinality-constrained approach has rarely been applied to health care. We recently applied the cardinality-constrained approach to two relevant health care management problems, namely, the operating room planning problem and the nurse-to-patient assignment problem in home care services. In this communication, we briefly describe our experience and focus on general considerations, advantages, and remarks that can help operations researchers in evaluating the approach for other applications in health care management.

Factors influencing use of an e-health website in a community sample of older adults

The use of the internet as a source of health information and link to healthcare services has raised concerns about the ability of consumers, especially vulnerable populations such as older adults, to access these applications. This study examined the influence of training on the ability of adults (aged 45+ years) to use the Medicare.gov website to solve problems related to health management. The influence of computer experience and cognitive abilities on performance was also examined. Seventy-one participants, aged 47-92, were randomized into a Multimedia training, Unimodal training, or Cold Start condition and completed three healthcare management problems. MEASUREMENT AND ANALYSES: Computer/internet experience was measured via questionnaire, and cognitive abilities were assessed using standard neuropsychological tests. Performance metrics included measures of navigation, accuracy and efficiency. Data were analyzed using analysis of variance, χ(2) and regression techniques. The data indicate that there was no difference among the three conditions on measures of accuracy, efficiency, or navigation. However, results of the regression analyses showed that, overall, people who received training performed better on the tasks, as evidenced by greater accuracy and efficiency. Performance was also significantly influenced by prior computer experience and cognitive abilities. Participants with more computer experience and higher cognitive abilities performed better. The findings indicate that training, experience, and abilities are important when using complex health websites. However, training alone is not sufficient. The complexity of web content needs to be considered to ensure successful use of these websites by those with lower abilities.

The nurse executive role in Hong Kong's transforming healthcare environment.

The goal of International Perspectives is to share the views of nurse leaders, from countries other than the United States, on global healthcare issues. The focus is on identifying healthcare management problems and their implications, research priorities, policy development, and ethical-moral dilemmas faced by nurse administrators. You are encouraged to send the names and addresses of international nurse leaders who might be interested in participating, as well as your ideas, for format and content of the department.

Health and Nursing Leadership in Taiwan, Republic of China

The goal of International Perspectives is to share the views of nurse leaders, from countries other than the United States, on global healthcare issues. The focus is on identifying healthcare management problems and their implications, research priorities, policy development, and ethical-moral dilemmas faced by nurse administrators. You are encouraged to send the names and addresses of international nurse leaders who might be interested in participating, as well as your ideas for format and content of the department.

Nursing in Brazil.

The goal of International Perspectives is to share the views of nurse leaders, from countries other than the United States, on global healthcare issues. The focus is on identifying healthcare management problems and their implications, research priorities, policy development, and ethical-moral dilemmas faced by nurse administrators. You are encouraged to send the names and addresses of international nurse leaders who might be interested in participating, as well as your ideas, for format and content of the department.

Nurse Managers and Their Future in New South Wales

The goal of International Perspectives is to share the views of nurse leaders, from countries other than the United States, on global healthcare issues. The focus is on identifying healthcare management problems and their implications, research priorities, policy development, and ethicalmoral dilemmas faced by nurse administrators. You are encouraged to send the names and addresses of international nurse leaders who might be interested in participating, as well as your ideas, for format and content of the department.

Cocaine and Pregnancy: A Challenge for Health Care Providers

There is an alarming increase in the number of individuals using cocaine in this country. As many as 10 percent of all pregnant women have used cocaine one or more times during their pregnancy. The rising number of pregnant cocaine abusers who present themselves for medical services is creating a challenge for health care practitioners. This article addresses the biopsychosocial issues of cocaine abuse during pregnancy, including the medical impact of cocaine abuse on pregnant women and their newborn infants, behavioral manifestations of cocaine abusers that create health care management problems, and social work's contribution to the health care management of these women.