Development of a statewide highway safety data warehouse: Massachusetts data warehouse and web-based access

2005 ◽  
Vol 36 (5) ◽  
pp. 465-467
Author(s):  
Heather A. Rothenberg ◽  
Robin Riessman ◽  
Davin Flatten
Author(s):  
Zhenyu Huang ◽  
Lei-da Chen ◽  
Mark Frolick
Keyword(s):  

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Claire J Peet ◽  
Charalampia Papadopoulou ◽  
Bella Ruth M Sombrito ◽  
Michael R Wood ◽  
Helen J Lachmann

Abstract Objectives The systemic autoinflammatory diseases are rare conditions; to date, data on coronavirus disease 2019 (COVID-19) infection and vaccination safety are scarce. Agents targeting innate immune pathways have transformed the management of affected patients, and their outcomes are of wider interest given the role of inflammation in both viral clearance and severe COVID-19 disease. We surveyed patients with systemic autoinflammatory disease on biologic therapy to determine the prevalence and outcomes of COVID-19 infection and to gather early safety data on vaccination. Methods Electronic medical records of 248 patients with systemic autoinflammatory disease on biologic therapy at a national centre were reviewed. Patients were then surveyed in clinic or using a Web-based survey. Results In the cohort of 248 patients, no deaths were recorded. One hundred and seventy-five survey responses were received. Among the respondents, 27 reported suspected COVID-19 infection, of which 14 were confirmed by testing (8.0%). Two patients required hospital admission owing to dehydration. No patient required respiratory support or intensive care. One hundred and thirty-eight doses of COVID-19 vaccine had been administered to 130 patients. Side effects were reported after 71 of 138 (51.4%) administrations and were consistent with a flare of the underlying disease in 26 of 138 (18.8%) instances. No serious adverse events or hospital admissions were reported after vaccination. Conclusion These data, including the largest published series of patients on anti-IL-1/6 biologics to receive any adenoviral vector or messenger RNA vaccine, show no serious early concerns regarding vaccination and will provide an urgently needed resource to inform decision-making of these patients and their clinicians.


2016 ◽  
Vol 2 (2) ◽  
Author(s):  
ADJAT SUDRADJAT

ABSTRACT - As an educational institution, Bina Sarana Informatika of course requires summary of information which is comprehensive and sustainable as a support to management in doing evaluation, planning and decision-making in the field of academic services. But the information system from operational data processing today can’t meet the needs, because it’s only able to produce detailed reports periodically. The research studies the development of a data warehouse for Call Center on The Division of Public Information of Bina Sarana Informatika in order to explore the strategic information contained in the operational database and present them in the form of summary information which is useful as input in improving the quality of academic services. By using a nine steps kimball approach, the research produce a data warehouse which is equipped with a web-based presentation application that can be easily accessed by all stakeholders of Bina Sarana Informatika. The development of data warehouse has been able to extract operational data into strategic information summaries that are useful to Bina Sarana Informatika management as supporting in doing evaluation, planning and decision-making in the field of academic services. Keywords : Nine Steps Kimball, Call Center, Data Warehouse, Decision Support. ABSTRAKSI - Sebagai sebuah institusi pendidikan, Bina Sarana Informatika tentu membutuhkan ringkasan informasi yang komprehensif dan berkesinambungan sebagai penunjang bagi manajemen dalam melakukan evaluasi, perencanaan dan pengambilan keputusan di bidang pelayanan akademik. Namun sistem informasi yang berasal dari pengolahan data operasional saat ini tidak dapat memenuhi kebutuhan tersebut, karena hanya mampu menghasilkan laporan–laporan yang bersifat detail dan periodik. Penelitian ini mengkaji pengembangan data warehouse Call Center pada Divisi Informasi Publik Bina Sarana Informatika untuk menggali informasi strategis yang terdapat pada database operasional dan menyajikannya dalam bentuk ringkasan informasi yang berguna sebagai masukan dalam usaha peningkatan kualitas pelayanan akademik. Dengan menggunakan metodologi kimball nine-step, penelitian menghasilkan sebuah data warehouse dilengkapi dengan aplikasi presentasi berbasis web yang dapat diakses dengan mudah oleh seluruh stakeholder Bina Sarana Informatika. Pengembangan data warehouse telah mampu mengekstrak data operasional menjadi ringkasan informasi strategis yang berguna bagi manajemen Bina Sarana Informatika sebagai penunjang dalam melakukan evaluasi, perencanaan dan pengambilan keputusan di bidang pelayanan akademik. Kata Kunci : Nine Steps Kimball, Call Center, Data Warehouse, Decision Support.


Author(s):  
Sandro Bimonte

Data warehouse and OLAP systems are tools to support decision-making. Geographic information systems (GISs) allow memorizing, analyzing and visualizing geographic data. In order to exploit the complex nature of geographic data, a new kind of decision support system has been developed: spatial OLAP (SOLAP). Spatial OLAP redefines main OLAP concepts: dimension, measure and multidimensional operators. SOLAP systems integrate OLAP and GIS functionalities into a unique interactive and flexible framework. Several research tools have been proposed to explore and the analyze spatio-multidimensional databases. This chapter presents a panorama of SOLAP models and an analytical review of research SOLAP tools. Moreover, the authors describe their Web-based system: GeWOlap. GeWOlap is an OLAP-GIS integrated solution implementing drill and cut spatio-multidimensional operators, and it supports some new spatio-multidimensional operators which change dynamically the structure of the spatial hypercube thanks to spatial analysis operators.


Author(s):  
D. Xuan Le ◽  
J. Wenny Rahayu ◽  
David Taniar

This paper proposes a data warehouse integration technique that combines data and documents from different underlying documents and database design approaches. The well-defined and structured data such as Relational, Object- oriented and Object Relational data, semi-structured data such as XML, and unstructured data such as HTML documents are integrated into a Web data warehouse system. The user specified requirement and data sources are combined to assist with the definitions of the hierarchical structures, which serve specific requirements and represent a certain type of data semantics using object-oriented features including inheritance, aggregation, association and collection. A conceptual integrated data warehouse model is then specified based on a combination of user requirements and data source structure, which creates the need for a logical integrated data warehouse model. A case study is then developed into a prototype in a Web-based environment that enables the evaluation. The evaluation of the proposed integration Web data warehouse methodology includes the verification of correctness of the integrated data, and the overall benefits of utilizing this proposed integration technique.


2016 ◽  
Author(s):  
Terri Parker and James B. McDaniel ◽  
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Author(s):  
Setyo Purnomo ◽  
Aris Puji Widodo ◽  
Yuliani Setyaningsih

Abstract. To provide security to their patients, healthcare providers use a system for patient safety which includes risk reporting and analysis of incidents, identification and management of risks, and the ability to learn about events that have occurred. According to the 2017 patient safety data at Prof. Dr. Soerojo Psychiatric Hospital, 7% of patient safety incidents at the hospital required a Root Cause Analysis. To aid the process, an online information system is necessary. This research was qualitative research that used the waterfall method for the information syntax. This involved planning, analysis, design, implementation, and system. From there, the data was then evaluated based on its accessibility, completeness, accuracy, and speed. The qualitative data was gathered through questionnaires, in-depth interviews, and unstructured interviews with selected informants. 26 informants were involved in this research, this included the reporters, the Patient Safety (KPRS) Team, and the hospital management board. Results of the would then produce recommendations on how to handle the problems found. Based on the data gathered, we discovered that after the application of the information system, the hospital experienced a 53.8% increase in patient safety.


Author(s):  
H. McGrath ◽  
E. Stefanakis ◽  
M. Nastev

In New Brunswick flooding occurs typically during the spring freshet, though, in recent years, midwinter thaws have led to flooding in January or February. Municipalities are therefore facing a pressing need to perform risk assessments in order to identify communities at risk of flooding. In addition to the identification of communities at risk, quantitative measures of potential structural damage and societal losses are necessary for these identified communities. Furthermore, tools which allow for analysis and processing of possible mitigation plans are needed. Natural Resources Canada is in the process of adapting Hazus-MH to respond to the need for risk management. This requires extensive data from a variety of municipal, provincial, and national agencies in order to provide valid estimates. The aim is to establish a data warehouse to store relevant flood prediction data which may be accessed thru Hazus. Additionally, this data warehouse will contain tools for On-Line Analytical Processing (OLAP) and knowledge discovery to quantitatively determine areas at risk and discover unexpected dependencies between datasets. The third application of the data warehouse is to provide data for online visualization capabilities: web-based thematic maps of Hazus results, historical flood visualizations, and mitigation tools; thus making flood hazard information and tools more accessible to emergency responders, planners, and residents. This paper represents the first step of the process: locating and collecting the appropriate datasets.


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