Difference between revisions of "Template:Article of the week"

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'''"[[Journal:National and transnational security implications of asymmetric access to and use of biological data|National and transnational security implications of asymmetric access to and use of biological data]]"'''
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Ebnehoseini OAccessMacJofMedSci2019 7-9.png|240px]]</div>
'''"[[Journal:Determining the hospital information system (HIS) success rate: Development of a new instrument and case study|Determining the hospital information system (HIS) success rate: Development of a new instrument and case study]]"'''


Biology and [[biotechnology]] have changed dramatically during the past 20 years, in part because of increases in computational capabilities and use of engineering principles to study biology. The advances in supercomputing, data storage capacity, and [[Cloud computing|cloud platforms]] enable scientists throughout the world to generate, analyze, share, and store vast amounts of data, some of which are biological and much of which may be used to understand the human condition, agricultural systems, evolution, and environmental ecosystems. These advances and applications have enabled: (1) the emergence of data science, which involves the development of new algorithms to analyze and [[Data visualization|visualize data]]; and (2) the use of engineering approaches to manipulate or create new biological organisms that have specific functions, such as production of industrial chemical precursors and development of environmental bio-based sensors. Several biological sciences fields harness the capabilities of computer, data, and engineering sciences, including synthetic biology, precision medicine, precision agriculture, and systems biology. These advances and applications are not limited to one country. This capability has economic and physical consequences but is vulnerable to unauthorized intervention. ('''[[Journal:National and transnational security implications of asymmetric access to and use of biological data|Full article...]]''')<br />
A [[hospital information system]] (HIS) is a type of health information system which is widely used in clinical settings. Determining the success rate of a HIS is an ongoing area of research since its implications are of interest for researchers, physicians, and managers. In the present study, we develop a novel instrument to measure HIS success rate based on users’ viewpoints in a teaching [[hospital]]. The study was conducted in Ibn-e Sina and Dr. Hejazi Psychiatry Hospital and education center in Mashhad, Iran. The instrument for data collection was a self-administered structured questionnaire based on the information systems success model (ISSM), covering seven dimensions, which includes system quality, [[information]] quality, service quality, system use, usefulness, satisfaction, and net benefits. The verification of content validity was carried out by an expert panel. The internal consistency of dimensions was measured by Cronbach’s alpha. Pearson’s correlation coefficient was calculated to evaluate the significance of associations between dimensions. The HIS success rate on users’ viewpoints was determined. ('''[[Journal:Determining the hospital information system (HIS) success rate: Development of a new instrument and case study|Full article...]]''')<br />
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Revision as of 16:04, 15 July 2019

Fig4 Ebnehoseini OAccessMacJofMedSci2019 7-9.png

"Determining the hospital information system (HIS) success rate: Development of a new instrument and case study"

A hospital information system (HIS) is a type of health information system which is widely used in clinical settings. Determining the success rate of a HIS is an ongoing area of research since its implications are of interest for researchers, physicians, and managers. In the present study, we develop a novel instrument to measure HIS success rate based on users’ viewpoints in a teaching hospital. The study was conducted in Ibn-e Sina and Dr. Hejazi Psychiatry Hospital and education center in Mashhad, Iran. The instrument for data collection was a self-administered structured questionnaire based on the information systems success model (ISSM), covering seven dimensions, which includes system quality, information quality, service quality, system use, usefulness, satisfaction, and net benefits. The verification of content validity was carried out by an expert panel. The internal consistency of dimensions was measured by Cronbach’s alpha. Pearson’s correlation coefficient was calculated to evaluate the significance of associations between dimensions. The HIS success rate on users’ viewpoints was determined. (Full article...)

Recently featured:

▪ Smart information systems in cybersecurity: An ethical analysis
▪ Chemometric analysis of cannabinoids: Chemotaxonomy and domestication syndrome
▪ National and transnational security implications of asymmetric access to and use of biological data
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