scholarly journals The meaningfulness of open data in Public Health and Healthcare

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J Pita Costa ◽  
F Fuart ◽  
B Cleland ◽  
J Wallace ◽  
A Staines ◽  
...  
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Open Data ◽  
Knowledge Bases ◽  
Data Sources ◽  
Local Context ◽  
Easy Access ◽  
New Information ◽  
Challenges And Opportunities ◽  
Complex Ecosystem

Abstract Background The growing challenges and opportunities of Big Data for Public Health have revealed the potential to improve the efficiency and cost-effectiveness of public policy, for example through better targeting of resources with regard to General Practice (GP) prescribing. Open data has an important role due to its easy access and potential to complement proprietary data sources from, e.g., regional hospitals, and also itself be complemented with social data acquired by specialized approaches. Methods MIDAS pipeline of open source tools aiming integrating, analysing and visualising Open Data enabling health professionals and decision-makers to: (i) improve the usability of open data in combination with proprietary data through combining multiple visualisation tools in an integrated dashboard (ii) to explore the meaning of data in a global/local context based on new information using tone analysis and natural language techniques; and (iii) to have better informed decision-making based on evidence from trusted knowledge-bases. Specific data sources used have included information extracted from the biomedical database MEDLINE, worldwide news and government open data. Social media sources have also been used to gather information from the general public. Results Results include a strong correlation between antidepressant prescribing and economic deprivation, and a wide variation in how individual GP practices respond to demographic conditions. Automated anomaly detection based on the Local Outlier Probability has also been shown to be an easily understood and controllable approach to identifying prescribing outliers. Conclusions MIDAS demonstrates the significant value of open data from heterogeneous sources as basis decision-making in public health and healthcare, particularly when it is combined with proprietary or closed datasets. A key challenge in this regard is the ability to integrate and utilize data from diverse sources in a variety of formats and standards. Key messages MIDAS is exemplar on tackling the need for improved standards of open data, and new software architectures, tools and platforms addressing a complex ecosystem of heterogenous data sources and formats. MIDAS demonstrates the significant value of open data from heterogeneous sources as basis decision-making in public health and healthcare, particularly when combined with proprietary datasets.

scholarly journals Data Sources Analysis for Sustainable Trip Planner Development for Riga City

2021 ◽  
Vol 22 (3) ◽  
pp. 321-331
Author(s):  
Alise Dinko ◽  
Irina Yatskiv Jackiva ◽  
Evelina Budilovich Budiloviča
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Open Data ◽  
Life Quality ◽  
Data Sources ◽  
Added Value ◽  
Transportation Services ◽  
Data Usage ◽  
Trip Planner ◽  
To Receive

Abstract In today’s daily traveller world, not only the time and money became important, but climate change and pandemic raised the importance of safety and sustainability of future trip plans. In order to provide such a wide coverage for a variety of important information, a sustainable trip planner needs to receive a lot of data from a variety of differentiated data sources. Provided review of related works shows that a lot of started activities in this aspects gives all of us promises and hope that available Big Data sources will be wisely used in order to bring added value not only to individual travellers, but also society, the transportation services will become better structured and information will be easily available for smart and safe decision making, that gradually will increase life quality. The study’s main goal is analysis of open data sources for the trip planner development. Authors analysed availability of data for Riga transport system and data usage for sustainable trip planner.

Opportunities and Challenges of Visualization and Open Data in Food Security Analysis

2019 ◽  
pp. 748-772
Author(s):  
Thida Chaw Hlaing ◽  
Julian Prior
Keyword(s):  
Decision Making ◽  
Food Security ◽  
Security Analysis ◽  
Open Data ◽  
Global Level ◽  
Statistical Literacy ◽  
The World ◽  
The Future ◽  
Challenges And Opportunities ◽  
Decision Making Processes

Statistical literacy presents many aspects about food security in the world. It highlights weaknesses, it creates awareness of threats in current situations, helps overcome challenges and creates opportunities for the future. Statistical data analysis enables existing food security interventions and programs to be reviewed and revised, and this better understanding of current situations enables more authoritative and relevant decision-making processes for the future. Statistical literacy involves skills and expertise in data description and interpretation (in words as well as in numbers) to name, explore and amend beliefs, opinions and suggestions. It helps decision-making processes about food security in a sub-nation, nation and region, as well as the world. This chapter will demonstrate the importance of open data and visualization, including its challenges and opportunities, in the food security context at national and global level to make decision-makers aware of the need to enhance their capacity for and investment in statistical literacy.

Patient-Centered Clinical Trials Decision Support Using Linked Open Data

2018 ◽  
pp. 1765-1782
Author(s):  
Bonnie MacKellar ◽  
Christina Schweikert ◽  
Soon Ae Chun
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Clinical Trials ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Linked Data ◽  
Open Data ◽  
Data Sources ◽  
Patient Centered

Patients often want to participate in relevant clinical trials for new or more effective alternative treatments. The clinical search system made available by the NIH is a step forward to support the patient's decision making, but, it is difficult to use and requires the patient to sift through lengthy text descriptions for relevant information. In addition, patients deciding whether to pursue a given trial often want more information, such as drug information. The authors' overall aim is to develop an intelligent patient-centered clinical trial decision support system. Their approach is to integrate Open Data sources related to clinical trials using the Semantic Web's Linked Data framework. The linked data representation, in terms of RDF triples, allows the development of a clinical trial knowledge base that includes entities from different open data sources and relationships among entities. The authors consider Open Data sources such as clinical trials provided by NIH as well as the drug side effects dataset SIDER. The authors use UMLS (Unified Medical Language System) to provide consistent semantics and ontological knowledge for clinical trial related entities and terms. The authors' semantic approach is a step toward a cognitive system that provides not only patient-centered integrated data search but also allows automated reasoning in search, analysis and decision making using the semantic relationships embedded in the Linked data. The authors present their integrated clinical trial knowledge base development and a prototype, patient-centered Clinical Trial Decision Support System that include capabilities of semantic search and query with reasoning ability, and semantic-link browsing where an exploration of one concept leads to other concepts easily via links which can provide visual search for the end users.

Decision Making Support Systems

2011 ◽  
pp. 392-403 ◽  
Author(s):  
Guisseppi A. Forgionne ◽  
Jatinder N.D. Gupta ◽  
Manuel Mora
Keyword(s):  
Decision Making ◽  
Support Systems ◽  
State Of The Art ◽  
Organizational Structures ◽  
Decision Makers ◽  
Organizational Benefits ◽  
New Information ◽  
Challenges And Opportunities ◽  
Future Challenges ◽  
Decision Making Support

Previous chapters have described the state of the art in decision making support systems (DMSS). This chapter synthesizes the views of leading scientists concerning the achievements of DMSS and the future challenges and opportunities. According to the experts, DMSS will be technologically more integrated, offer broader and deeper support for decision making, and provide a much wider array of applications. In the process, new information and computer technologies will be necessitated, the decision makers’ jobs will change, and new organizational structures will emerge to meet the changes. The changes will not occur without displacements of old technologies and old work paradigms. In particular, there will be an evolution toward team-based decision making paradigms. Although the evolution can require significant investments, the organizational benefits from successful DMSS deployments can be significant and substantial. Researchers and practitioners are encouraged to collaborate in their effort to further enhance the theoretical and pragmatic developments of DMSS.

scholarly journals Some mathematical tools for modelling malaria: a subjective survey

BIOMATH ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 2110029
Author(s):  
Jacek Banasiak ◽  
Rachid Ouifki ◽  
Woldegebriel Assefa Woldegerima
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Confidence Interval ◽  
Mathematical Modelling ◽  
South African ◽  
Health Interventions ◽  
Design Strategies ◽  
Public Health Interventions ◽  
The Past ◽  
Challenges And Opportunities

In this paper, we provide a brief survey of mathematical modelling of malaria and how it is used to understand the transmission and progression of the disease and design strategies for its control to support public health interventions and decision-making. We discuss some of the past and present contributions of mathematical modelling of malaria, including the recent development of modelling the transmission-blocking drugs. We also comment on the complexity of the malaria dynamics and, in particular, on its multiscale character with its challenges and opportunities. We illustrate the discussion by presenting a curve fitting using a 95% confidence interval for the South African data for malaria from the years 2001-2018$ and provide projections for the number of malaria cases and deaths up to the year 2025.

Opportunities and Challenges of Visualization and Open Data in Food Security Analysis

2017 ◽  
pp. 69-101
Author(s):  
Thida Chaw Hlaing ◽  
Julian Prior
Keyword(s):  
Decision Making ◽  
Food Security ◽  
Security Analysis ◽  
Open Data ◽  
Global Level ◽  
Statistical Literacy ◽  
The World ◽  
The Future ◽  
Challenges And Opportunities ◽  
Decision Making Processes

Statistical literacy presents many aspects about food security in the world. It highlights weaknesses, it creates awareness of threats in current situations, helps overcome challenges and creates opportunities for the future. Statistical data analysis enables existing food security interventions and programs to be reviewed and revised, and this better understanding of current situations enables more authoritative and relevant decision-making processes for the future. Statistical literacy involves skills and expertise in data description and interpretation (in words as well as in numbers) to name, explore and amend beliefs, opinions and suggestions. It helps decision-making processes about food security in a sub-nation, nation and region, as well as the world. This chapter will demonstrate the importance of open data and visualization, including its challenges and opportunities, in the food security context at national and global level to make decision-makers aware of the need to enhance their capacity for and investment in statistical literacy.

Evidence-Based Practice and Public Health

2018 ◽  
Author(s):  
Patrick Bryant ◽  
Peter D Hurd ◽  
Ardis Hanson
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Public Health Practice ◽  
Standards Of Care ◽  
Evidence Based ◽  
Clinical Knowledge ◽  
Health Practice ◽  
Challenges And Opportunities ◽  
Based Medicine ◽  
Evidence Based Decision Making

The most difficult step of evidence-based medicine (EBM) and evidence-based public health (EBPH) is to link the evidence with current clinical knowledge and experience, especially with the continued focus on using evidence in decision-making. Standards of care and clinical practice guidelines are now established and reported using nationally and globally recognized protocols to ensure standard nomenclature and clinical crosswalks. This chapter examines relevant background issues, including concepts underlying EBM, EBPH, and definitions of evidence; describes key analytic tools to enhance the adoption of evidence-based decision-making; and finishes with challenges and opportunities for implementation in public health practice.

Invited Commentary: The Prevalent New User Design in Pharmacoepidemiology: Challenges and Opportunities

2020 ◽  
Author(s):  
Kristian B Filion ◽  
Ya-Hui Yu
Keyword(s):  
Public Health ◽  
Decision Making ◽  
Real World ◽  
Simulation Studies ◽  
Public Health Importance ◽  
Treatment History ◽  
Real World Evidence ◽  
User Design ◽  
Challenges And Opportunities ◽  
Study Population

Abstract The prevalent new user design includes a broader study population than the traditional new user approach that is frequently used in pharmacoepidemiologic research. In an article appearing in this issue (Am J Epidemiol. XXXX;XXX(XX):XXXX–XXXX), Webster-Clark and colleagues describe the treatment initiator types included in the prevalent new user design and contrast the causal questions assessed using a prevalent new user design versus a new user design. They further applied a series of simulation studies showing the importance of accounting for treatment history in addition to time since initiation of the comparator in the prevalent new user design. In this commentary, we put their findings in the broader context with a discussion of the strengths and limitations of the prevalent new user design and settings where it may be most useful. The prevalent new user design and new user design both address unique questions of clinical and public health importance. Real-world evidence generated by pharmacoepidemiologic research is increasingly being used by regulators and other knowledge users to inform their decision making. Understanding the causal questions addressed by different designs is crucial in this process; the study by Webster-Clark and colleagues represents an important step in addressing this issue.

scholarly journals La cobertura de los índices de citas abiertos se acerca a la de Web of Science y Scopus

2021 ◽  
Author(s):  
Alberto Martín-Martín
Keyword(s):  
Information Sources ◽  
Web Of Science ◽  
Open Data ◽  
Digital Transformation ◽  
Data Sources ◽  
Google Scholar ◽  
Easy Access ◽  
Citation Data ◽  
Microsoft Academic ◽  
New Infrastructure

The information sources that are often used to monitor and to obtain a better understanding of the system of scholarly communication (such as Web of Science, Scopus, and Google Scholar) have historically been distributed under restrictive use licenses. However, in a scenario where science and scientific communication are undergoing a process of digital transformation, these models do not facilitate the development of new infrastructure that is better adapted to current and future needs. At the same time, these models hamper reproducibility. In recent years, a variety of open data sources, such as Microsoft Academic, Crossref, and others, have become available, providing easy access to large collections of metadata that were previously only available from closed sources. Citation data are one type of metadata provided by these open data sources. This study documents the significant growth in coverage of open citation data that has taken place between 2019 and 2021, and the events that have led to this point. These collections of open scholarly metadata have kick-started the development of a new ecosystem of scholarly information services. However, their fragility still poses a risk for downstream applications. Academic libraries could become important allies of open scholarly metadata initiatives. Resumen Históricamente, las fuentes de información utilizadas para observar y comprender el funcionamiento del sistema de comunicación científica han sido distribuidas bajo licencias de uso restrictivas (Web of Science, Scopus, Google Scholar). En el contexto actual, caracterizado por un proceso de transformación digital de la ciencia y de la comunicación científica, estos modelos no facilitan el desarrollo de infraestructuras y herramientas de información científica adaptadas a nuevas necesidades, e impiden la realización de análisis reproducibles. Afortunadamente, en los últimos años han aparecido diversas colecciones de metadatos de investigación distribuidas bajo licencias abiertas, como las ofrecidas por Microsoft Academic, Crossref y otros. Un tipo de metadato ofrecido por estas fuentes abiertas que anteriormente solo estaba disponible desde fuentes cerradas son las relaciones de citación entre documentos académicos. Este trabajo muestra el significativo crecimiento que se ha producido entre 2019 y 2021 en la cobertura de citas disponible en fuentes abiertas, así como los pasos que han sido necesarios para llegar hasta este punto. Estas colecciones de metadatos abiertas han estimulado el desarrollo de un nuevo ecosistema de herramientas de información científica, pero su fragilidad representa un riesgo de cara al futuro. Las bibliotecas académicas podrían convertirse en importantes aliadas de estas iniciativas.

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