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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Duncan FrontBioengBiotech2019 7.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Ebnehoseini OAccessMacJofMedSci2019 7-9.png|240px]]</div>
'''"[[Journal:Cyberbiosecurity: A new perspective on protecting U.S. food and agricultural system|Cyberbiosecurity: A new perspective on protecting U.S. food and agricultural system]]"'''
'''"[[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]]"'''


Our national data and infrastructure security issues affecting the “bioeconomy” are evolving rapidly. Simultaneously, the conversation about cybersecurity of the U.S. [[Agriculture industry|food and agricultural system]] (cyber biosecurity) is incomplete and disjointed. The food and agricultural production sectors influence over 20% of the nation's economy ($6.7T) and 15% of U.S. employment (43.3M jobs). The food and agricultural sectors are immensely diverse, and they require advanced technologies and efficiencies that rely on computer technologies, big data, [[Cloud computing|cloud-based]] data storage, and internet accessibility. There is a critical need to safeguard the cyber biosecurity of our bioeconomy, but currently protections are minimal and do not broadly exist across the food and agricultural system. Using the food safety management Hazard Analysis Critical Control Point (HACCP) system concept as an introductory point of reference, we identify important features in broad food and agricultural production and food systems: dairy, food animals, row crops, fruits and vegetables, and environmental resources (water). ('''[[Journal:Cyberbiosecurity: A new perspective on protecting U.S. food and agricultural system|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