This heavily revised open access edition provides a thorough overview of the technologies available to assemble, manage and assess the quality of health information systems. It details a variety of ...scenarios in the context of both health and heath care, including where prevention and wellness are related, such as the treatment of both acute and chronic diseases. Stakeholder requirements are also described to provide perspectives for describing the architectures and management techniques associated with health information systems, enabling the reader to develop a detailed holistic overview of the subject. Health Information Systems: Technological and Management Perspectives features a detailed overview of how information systems in health care can be managed and is a vital resource for medical informatics students seeking an up-to-date text on the topic.
Today, our reality and lives are increasingly game-like, not only because games have become a pervasive part of our lives, but also because activities, systems and services are increasingly gamified. ...Gamification refers to designing information systems to afford similar experiences and motivations as games do, and consequently, attempting to affect user behavior. In recent years, popularity of gamification has skyrocketed and manifested in growing numbers of gamified applications, as well as a rapidly increasing amount of research. However, this vein of research has mainly advanced without an agenda, theoretical guidance or a clear picture of the field.
To make the picture more coherent, we provide a comprehensive review of the gamification research (N = 819 studies) and analyze the research models and results in empirical studies on gamification. While the results in general lean towards positive findings about the effectiveness of gamification, the amount of mixed results is remarkable. Furthermore, education, health and crowdsourcing as well as points, badges and leaderboards persist as the most common contexts and ways of implementing gamification. Concurrently, gamification research still lacks coherence in research models, and a consistency in the variables and theoretical foundations. As a final contribution of the review, we provide a comprehensive discussion, consisting of 15 future research trajectories, on future agenda for the growing vein of literature on gamification and gameful systems within the information system science field.
GPlates: Building a Virtual Earth Through Deep Time Müller, R. Dietmar; Cannon, John; Qin, Xiaodong ...
Geochemistry, geophysics, geosystems : G3,
July 2018, 2018-07-00, 20180701, Letnik:
19, Številka:
7
Journal Article
Recenzirano
Odprti dostop
GPlates is an open‐source, cross‐platform plate tectonic geographic information system, enabling the interactive manipulation of plate‐tectonic reconstructions and the visualization of geodata ...through geological time. GPlates allows the building of topological plate models representing the mosaic of evolving plate boundary networks through time, useful for computing plate velocity fields as surface boundary conditions for mantle convection models and for investigating physical and chemical exchanges of material between the surface and the deep Earth along tectonic plate boundaries. The ability of GPlates to visualize subsurface 3‐D scalar fields together with traditional geological surface data enables researchers to analyze their relationships through geological time in a common plate tectonic reference frame. To achieve this, a hierarchical cube map framework is used for rendering reconstructed surface raster data to support the rendering of subsurface 3‐D scalar fields using graphics‐hardware‐accelerated ray‐tracing techniques. GPlates enables the construction of plate deformation zones—regions combining extension, compression, and shearing that accommodate the relative motion between rigid blocks. Users can explore how strain rates, stretching/shortening factors, and crustal thickness evolve through space and time and interactively update the kinematics associated with deformation. Where data sets described by geometries (points, lines, or polygons) fall within deformation regions, the deformation can be applied to these geometries. Together, these tools allow users to build virtual Earth models that quantitatively describe continental assembly, fragmentation and dispersal and are interoperable with many other mapping and modeling tools, enabling applications in tectonics, geodynamics, basin evolution, orogenesis, deep Earth resource exploration, paleobiology, paleoceanography, and paleoclimate.
Plain Language Summary
The GPlates virtual globe software provides the capability to reconstruct geodata attached to tectonic plates to develop and modify models that describe how the plates and their boundaries have evolved through time. It allows users to deform plates and to visualize surface tectonics in the context of convecting mantle structure and evolution by importing seismic tomography models or outputs from geodynamic models. GPlates applications include tectonics, geodynamics, basin evolution, orogenesis, deep Earth resource exploration, paleobiology, paleoceanography, and paleoclimate. The software is enabling end‐users in universities, government organizations, industry, and schools to explore the evolution of planet Earth on their desktop.
Key Points
GPlates is an open‐source plate tectonic geographic information system, enabling the interactive manipulation of tectonic reconstructions
GPlates enables the building of topological plate models, including plate deformation, and allows the visualization of subsurface volumes
GPlates applications include tectonics, geodynamics, basin evolution, orogenesis, resource exploration, paleobiology, and paleoclimate
Perguruan Tinggi Swasta XYZ menghadapi tekanan yang semakin meningkat untuk menjalankan operasinya secara efektif dan efisien dalam era digital yang cepat berubah. Pengelolaan strategi Teknologi ...Informasi (TI) adalah salah satu kunci untuk mencapai tujuan tersebut. Penelitian ini bertujuan untuk memberikan rekomendasi yang konkret dan terukur untuk meningkatkan kapabilitas strategi TI di Perguruan Tinggi Swasta XYZ, dengan menggunakan analisis berdasarkan COBIT 2019 Domain APO02 (Manage Strategy). Penelitian ini menggunakan metode campuran yang melibatkan survei, wawancara dengan pemangku kepentingan kunci, dan analisis dokumen strategis yang ada. Hasil penelitian berdasarkan tingkat kapabilitas dalam pengelolaan strategi TI di perguruan tinggi swastaXYZ, dengan beberapa aspek yang telah berkembang dengan baik sementara aspek lainnya memerlukan perbaikan. Perlu diketahui bahwa Perguruan Tinggi Swasta XYZ tersebut belum pernah melakukan proses tata kelola TI dan audit internal menggunakan COBIT 2019
Identification of hospital sites and their ranking is important for the planning and development of any country's health infrastructure. The site selection problem is a typical multi-criteria ...decision making problem involving multiple stakeholders and their interests. Multi-Criteria Decision Analysis (MCDA) is a promising approach to solve a location-based problem due to the constitution of various criteria involved in decision making. In this research, eleven criterion are chosen which are classified under three main criteria; socio-economic, geographical and environmental. This research aims to identify the appropriate MCDA method for the selection of a new hospital sites. Here, two MCDA methods named Analytical Hierarchy Process (AHP) and Fuzzy AHP (FAHP) are used. Further, Geographical Information System (GIS) based MCDA methodology is proposed in this paper. The results obtained with both AHP and FAHP methods are compared. This comparison is based on criterion rankings, proposed hospital locations and sensitivity analysis. The main difference in results is shown in the result of sensitivity analysis in which constant variation in site ranking is obtained when weight change analysis is performed using AHP. The FAHP result shows only one variation in site ranking after a change in weight from +10 to +20%. The result suggests that FAHP may be a better approach to the hospital site selection problem.
Contrastive learning has recently emerged as an effective strategy for improving the performance of sequential recommendation. However, traditional models commonly construct the contrastive loss by ...directly optimizing human-designed positive and negative samples, resulting in a model that is overly sensitive to heuristic rules. To address this limitation, we propose a novel soft contrastive framework for sequential recommendation in this paper. Our main idea is to extend the point-wise contrast to a region-level comparison, where we aim to identify instances near the initially selected positive/negative samples that exhibit similar contrastive properties. This extension improves the model’s robustness to human heuristics. To achieve this objective, we introduce an adversarial contrastive loss that allows us to explore the sample regions more effectively. Specifically, we begin by considering the user behavior sequence as a holistic entity. We construct adversarial samples by introducing a continuous perturbation vector to the sequence representation. This perturbation vector adds variability to the sequence, enabling more flexible exploration of the sample regions. Moreover, we extend the aforementioned strategy by applying perturbations directly to the items within the sequence. This accounts for the sequential nature of the items. To capture these sequential relationships, we utilize a recurrent neural network to associate the perturbations, which introduces an inductive bias for more efficient exploration of adversarial samples. To demonstrate the effectiveness of our model, we conduct extensive experiments on five real-world datasets.
Background: Health information systems offer many potential benefits for healthcare, including financial benefits and for improving the quality of patient care. The purpose of District Health ...Information Systems (DHIS) is to document data that are routinely collected in all public health facilities in a country using the system.
Objective: The aim of this study was to examine the strengths and operational challenges of DHIS2, with a goal to enable decision makers in different counties to more accurately evaluate the outcomes of introducing DHIS2 into their particular country.
Method: A review of the literature combined with the method of meta-synthesis was used to source information and interpret results relating to the strengths and operational challenges of DHIS2. Databases (Embase, PubMed, Scopus and Google Scholar) were searched for documents related to strengths and operational challenges of DHIS2, with no time limit up to 8 April 2017. The review and evaluation of selected studies was conducted in three stages: title, abstract and full text. Each of the selected studies was reviewed carefully and key concepts extracted. These key concepts were divided into two categories of strengths and operational challenges of DHIS2. Then, each category was grouped based on conceptual similarity to achieve the main themes and sub-themes. Content analysis was used to analyse extracted data.
Results: Of 766 identified citations, 20 studies from 11 countries were included and analysed in this study. Identified strengths in the DHIS were represented in seven themes (with 21 categories): technical features of software, proper management of data, application flexibility, networking and increasing the satisfaction of stakeholders, development of data management, increasing access to information and economic benefits. Operational challenges were identified and captured in 11 themes (with 18 categories): funds; appropriate communication infrastructure; the need for the existence of appropriate data; political, cultural, social and structural infrastructure; manpower; senior managers; training; using academic potentials; definition and standardising the deployment processes; neglect to application of criteria and clinical guidelines in the use of system; data security; stakeholder communications challenges and the necessity to establish a pilot system.
Conclusion: This study highlighted specific strengths in the technical and functional aspects of DHIS2 and also drew attention to particular challenges and concerns. These results provide a sound evidence base for decision makers and policymakers to enable them to make more accurate decisions about whether or not to use the DHIS2 in the health system of their country.
Health Information System is the key to making evidence-based decisions. Ethiopia has been implementing the Health Management Information System (HMIS) since 2008 to collect routine health data and ...revised it in 2017. However, the evidence is meager on the use of routine health information for decision making among department heads in the health facilities. The study aimed to assess the proportion of routine health information systems utilization for evidence-based decisions and factors associated with it.
A cross-sectional study was carried out among 386 department heads from 83 health facilities in ten selected districts in the Amhara region Northwest of Ethiopia from April to May 2019. The single population proportion formula was applied to estimate the sample size taking into account the proportion of data use 0.69, margin of error 0.05, and the critical value 1.96 at the 95% CI. The final sample size was estimated at 394 by considering 1.5 as a design effect and 5% non-response. The study participants were selected using a simple random sampling technique. Descriptive statistics mean and percentage were calculated. The study employed a generalized linear mixed-effect model. Adjusted Odds Ratio (AOR) and the 95% CI were calculated. Variables with p value < 0.05 were considered as predictors of routine health information system use.
Proportion of information use among department heads for decision making was estimated at 46%. Displaying demographic (AOR = 12.42, 95% CI 5.52, 27.98) and performance (AOR = 1.68; 95% CI 1.33, 2.11) data for monitoring, and providing feedback to HMIS unit (AOR = 2.29; 95% CI 1.05, 5.00) were individual (level-1) predictors. Maintaining performance monitoring team minute (AOR = 3.53; 95% CI 1.61, 7.75), receiving senior management directives (AOR = 3.56; 95% CI 1.76, 7.19), supervision (AOR = 2.84; 95% CI 1.33, 6.07), using HMIS data for target setting (AOR = 3.43; 95% CI 1.66, 7.09), and work location (AOR = 0.16; 95% CI 0.07, 0.39) were organizational (level-2) explanatory variables.
The proportion of routine health information utilization for decision making was low. Displaying demographic and performance data, providing feedback to HMIS unit, maintaining performance monitoring team minute, conducting supervision, using HMIS data for target setting, and work location were factors associated with the use of routine health information for decision making. Therefore, strengthening the capacity of department heads on data displaying, supervision, feedback mechanisms, and engagement of senior management are highly recommended.
Accurate and high-quality data are important for improving program effectiveness and informing policy. In 2009 Bangladesh's health management information system (HMIS) adopted the District Health ...Information Software, Version 2 (DHIS2) to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality and reporting. We aimed to understand the facilitators and barriers to implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal, newborn, child, and adolescent health (RMNCAH) services.
This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n = 11), in-depth interviews (n = 23), and focus group discussions (n = 2). The study participants were involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically.
DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward technology among staff. Quality checks and feedback loops at multiple levels of data gathering points are helpful for minimizing data errors. Introducing a dashboard makes DHIS2 compatible to use as a monitoring tool. Barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to DHIS2 versions, and maintaining both manual and electronic system side-by-side. The data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel HMIS reporting the same RMNCAH indicators threatens data quality and increases the reporting workload.
The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building a responsive HMIS. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.
A new method consisting of enrichment factor (EF) determination, nonmetric multidimensional scaling (NMS), and the geographic information system (GIS) technique was firstly developed to identify ...anthropogenic heavy metal sources in marine sediments of Hong Kong. Firstly, the EF was determined to differentiate between heavy metals originating from human and natural sources. Subsequently, NMS was applied to identify various source patterns of heavy metals, and the NMS score was calculated and spatially interpolated using GIS technology to evaluate the spatial influences of anthropogenic impacts in different areas. The concentrations of heavy metals in sediments of Hong Kong substantially exceeded their background values, demonstrating anthropogenic pollution. Two different types of human sources could be identified via NMS, one representing the industrial pollution discharges in the period from the 1960s to the 1980s before pollution control was introduced and one representing sewage discharge before the Tolo Harbour Action Plan in the mid-1980s.
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