No abstract available

High content live cell imaging experiments are able to track the cellular localisation of labelled proteins in multiple live cells over a time course. Experiments using high content live cell imaging will generate multiple large datasets that are often stored in an ad-hoc manner. This hinders identification of previously gathered data that may be relevant to current analyses. Whilst solutions exist for managing image data, they are primarily concerned with storage and retrieval of the images themselves and not the data derived from the images. There is therefore a requirement for an information management solution that facilitates the indexing of experimental metadata and results of high content live cell imaging experiments.

This study examined the level of acceptance of Health Information Technology (HIT) as tools for diabetes care and management, in six selected tertiary hospitals in southwestern zone of Nigeria. Using both quantitative and qualitative methods, this study was conducted amongst selected healthcare stakeholders namely Nurses, Doctors, Laboratory Scientists, Pharmacists, ICT unit Professionals, Medical Record Officers, and Type-2 diabetes out-patients available in the designated hospitals. Adapting Technology Acceptance and Chronic Care Models, the level of HIT acceptance by the respondents in the study area was measured in terms of Perceived Ease-of-Use, Perceived Usefulness, and the Perceived Unintended Consequences relating to HIT, while also considering the roles of the government, community and healthcare organizations. One hundred and fifty (150) respondents were examined, each for both Staff and Patients, and the factor variables studied on a 5-point Likert rating scale of measurement from 1 (Strongly Disagree) to 5 (Strongly Agree). The results revealed strong perception of Staff and Patients about HIT implementation and acceptance and showed that in some cases, the perception of Staff and patients about HIT acceptance are the same, while different in some. The study concluded that for acceptability of HIT, hospitals have to embark on 'continuous' training for the HIT users, so that users would familiarize themselves with the system, and it will be fully incorporated into their workflow. Based on the findings, a conceptual Health Information Technology Acceptance Framework for Chronic diseases' management, especially for diabetes mellitus was developed.

Multiple sclerosis (MS) is a chronic disease of central nervous system. The multiple sclerosis information system (MSIS), such as other information system (IS), depends on identification, collection and processing of data for producing useful information. Lack of the integrated IS for collecting standard data causes undesirable effects on exchanging, comparing, and managing. The aim of this study was to recognize the role of the IS in the MS management and determine the advantages and barriers in implementing of the MSIS. The present study was a nonsystematized review that was done in order to recognize the role of the IS in the MS management. In this study, electronic scientific resources such as scientific magazines and books and published topics at conferences were used. We used key words (IS, chronic disease management, and multiple sclerosis), their combination or their synonyms in title, key words, abstracts, and text of English articles and published reports from 1980 until 2013, and by using search engines such as Google, Google Scholar and scientific databases and electronic issues such as iPubMed, sufficiently important difference, Scopus, Medlib, and Magiran for gathering information. More than 200 articles and reports were collected and assessed and 139 of them. Findings showed that the MSIS can reduce of disease expenses through continuously collecting correct, accurate, sufficient, and timely patients and disease nature information; recoding; editing; processing; exchanging, and distributing among different health care centers. Although the MSIS has many advantages; but, we cannot ignore cultural, economic, technical, organizational, and managerial barriers. Therefore, it is necessary to do studies for preventing, reducing, and controlling them. One of the ways is to recognize the advantages of the MSIS and usage information technology in optimizing disease management.

Emergency management of the emerging infectious disease outbreak is critical for public health threats. Currently, control of the COVID-19 outbreak is an international concern and has become a crucial challenge in many countries. This article reviews significant information technologyIT) applications in emergency management of COVID-19 by considering the prevention/mitigation, preparedness, response, and recovery phases of the crisis. This review was conducted using MEDLINE PubMed), Embase, IEEE, and Google Scholar. Expert opinions were collected to show existence gaps, useful technologies for each phase of emergency management, and future direction. Results indicated that various IT-based systems such as surveillance systems, artificial intelligence, computational methods, Internet of things, remote sensing sensor, online service, and GIS geographic information system) could have different outbreak management applications, especially in response phases. Information technology was applied in several aspects, such as increasing the accuracy of diagnosis, early detection, ensuring healthcare providers' safety, decreasing workload, saving time and cost, and drug discovery. We categorized these applications into four core topics, including diagnosis and prediction, treatment, protection, and management goals, which were confirmed by five experts. Without applying IT, the control and management of the crisis could be difficult on a large scale. For reducing and improving the hazard effect of disaster situations, the role of IT is inevitable. In addition to the response phase, communities should be considered to use IT capabilities in prevention, preparedness, and recovery phases. It is expected that IT will have an influential role in the recovery phase of COVID-19. Providing IT infrastructure and financial support by the governments should be more considered in facilitating IT capabilities.

This paper presents the Bioinformatics Computational Journal (BCJ), a framework for conducting and managing computational experiments in bioinformatics and computational biology. These experiments often involve series of computations, data searches, filters, and annotations which can benefit from a structured environment. Systems to manage computational experiments exist, ranging from libraries with standard data models to elaborate schemes to chain together input and output between applications. Yet, although such frameworks are available, their use is not widespread-ad hoc scripts are often required to bind applications together. The BCJ explores another solution to this problem through a computer based environment suitable for on-site use, which builds on the traditional laboratory notebook paradigm. It provides an intuitive, extensible paradigm designed for expressive composition of applications. Extensive features facilitate sharing data, computational methods, and entire experiments. By focusing on the bioinformatics and computational biology domain, the scope of the computational framework was narrowed, permitting us to implement a capable set of features for this domain. This report discusses the features determined critical by our system and other projects, along with design issues. We illustrate the use of our implementation of the BCJ on two domain-specific examples.

The purpose of this study was to review evaluation studies of nursing management information systems (NMISs) and their outcome measures to examine system effectiveness.

To summarize the recent literature and research and present a selection of the best papers published in 2020 in the field of Health Information Management (HIM) and Health Informatics.

The science of information systems, management, and interpretation plays an important part in the continuity of care of patients. This is becoming more evident in the treatment of human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS), the leading cause of death in sub-Saharan Africa. The high replication rates, selective pressure, and initial infection by resistant strains of HIV infer that drug resistance will inevitably become an important health care concern. This paper describes proposed research with the aim of developing a physician-administered, artificial intelligence-based decision support system tool to facilitate the management of patients on antiretroviral therapy.

Older adults face growing health care needs and could potentially benefit from personal health information management (PHIM) and PHIM technology. To ensure effective PHIM and to provide supportive tools, it is crucial to investigate the needs, challenges, processes, and tools used by this subpopulation. The literature on PHIM by older adults, however, remains scattered and has not provided a clear picture of what we know about the elements that play a role in older adults' PHIM.

Federal and state governments in developing countries have tasked local governments with managing COVID-19 on the ground. The bottom-up approach is critical to ensuring household food security, especially in rural areas. We have utilized data from a panel of Indian households that participated in two rounds of a livelihoods survey. While the first round was fielded before COVID-19, the second round was conducted telephonically after the COVID-19-lockdown. We developed an Information Management Response Index (IMRI) to measure the strength of local governments' information management initiatives. The difference-in-difference estimates show that local governments could partially mitigate the pandemic's adverse effects on (a) level and distribution (adult-equivalent per-capita) of food and nutrition expenditure and (b) household vulnerability to food and nutrition poverty. For landless households, IMRI led to statistically significant and additional welfare effects. Three channels explain our empirical findings: (a) maintenance of essential commodities through fair-price shops, (b) access to paid employment and cash (income effect), and (c) disease management (substitution effect). The estimates have been adjusted for sample attrition and multiple-hypothesis correction. We conducted robustness checks with respect to index construction, instrumental variable estimation, and sub-group analysis.

Value of information (VOI) analysis provides information on opportunity cost of a decision in healthcare by estimating the cost of reducing parametric uncertainty and quantifying the value of generating additional evidence. This study is an application of the VOI methodology to the problem of choosing between home telemonitoring and nurse telephone support over usual care in chronic heart failure management in the Netherlands.

A well-functioning routine health information system (RHIS) can provide the information needed for health system management, for governance, accountability, planning, policy making, surveillance and quality improvement, but poor information support has been identified as a major obstacle for improving health system management.

Falls had been identified as one of the nursing-sensitive indicators for nursing care in hospitals. With technological progress, health information systems make it possible for health care professionals to manage patient care better. However, there is a dearth of research on health information systems used to manage inpatient falls.

This article aims to perform a Systematic Literature Review (SLR) to better understand the structures of different methods, techniques, models, methodologies, and technologies related to provenance data management in health information systems (HISs). The SLR developed here seeks to answer the questions that contribute to describing the results.

Not considering the usability in designing clinical information systems causes problems in human-computer interaction and patient dissatisfaction. Therefore, in this study, the usability of the bed information management system (BIMS) was examined by think-aloud method. This cross-sectional study was conducted on the BIMS in 50 noneducational hospitals. Participants consisted of three groups including users, facilitators, and technical support. To carry out the study, a scenario consisting of four tasks was designed. Three researchers analyzed the recorded files to identify the usability problems and their severity. The mean time of the evaluation process was 20:33 ± 4:47 s. The total number of the problems identifies by users was 80 cases. Data entry and layout problems with 38 (48%) and 33 (41%) cases were the most frequently found problems, respectively. About 61% and 55% of the data entry and layout problems had a minor severity (Severity 2), respectively. Furthermore, 43 (54%) cases of the problems were resolved by the users and 32 (40%) cases by the facilitator assistance. This study showed that a large number of the problems were due to the system poor design. Furthermore, by increasing the users' level of knowledge about the system, it is possible to enhance user-system interaction. It is recommended that before designing and implementing a system, the system should be evaluated for usability, and the users should be educated in clinical information systems.

High-quality plant phenotyping and climate data lay the foundation for phenotypic analysis and genotype-environment interaction, providing important evidence not only for plant scientists to understand the dynamics between crop performance, genotypes, and environmental factors but also for agronomists and farmers to closely monitor crops in fluctuating agricultural conditions. With the rise of Internet of Things technologies (IoT) in recent years, many IoT-based remote sensing devices have been applied to plant phenotyping and crop monitoring, which are generating terabytes of biological datasets every day. However, it is still technically challenging to calibrate, annotate, and aggregate the big data effectively, especially when they were produced in multiple locations and at different scales.

Facilities that provide a service for DNA sequencing typically support large numbers of users and experiment types. The cost of services is often reduced by the use of liquid handling robots but the efficiency of such facilities is hampered because the software for such robots does not usually integrate well with the systems that run the sequencing machines. Accordingly, there is a need for software systems capable of integrating different robotic systems and managing sample information for DNA sequencing services. In this paper, we describe an extension to the Protein Information Management System (PIMS) that is designed for DNA sequencing facilities. The new version of PIMS has a user-friendly web interface and integrates all aspects of the sequencing process, including sample submission, handling and tracking, together with capture and management of the data.

The launch of the eagle-i Consortium, a collaborative network for sharing information about research resources, such as protocols and reagents, provides a vivid demonstration of the challenges that researchers, libraries and institutions face in making their data available to others.

This study aims to explore the information chain management model of large instrument and equipment inter-working in the operating room (OR) led by information nurses.