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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Perez-Castillo Sensors2018 18-9.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Ebnehoseini OAccessMacJofMedSci2019 7-9.png|240px]]</div>
'''"[[Journal:DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data|DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data]]"'''
'''"[[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]]"'''


The [[internet of things]] (IoT) introduces several technical and managerial challenges when it comes to the use of data generated and exchanged by and between various smart, connected products (SCPs) that are part of an IoT system (i.e., physical, intelligent devices with sensors and actuators). Added to the volume and the heterogeneous exchange and consumption of data, it is paramount to [[Quality assurance|assure]] that data quality levels are maintained in every step of the data chain/lifecycle. Otherwise, the system may fail to meet its expected function. While data quality (DQ) is a mature field, existing solutions are highly heterogeneous. Therefore, we propose that companies, developers, and vendors should align their data quality management mechanisms and artifacts with well-known best practices and [[Specification (technical standard)|standards]], as for example, those provided by ISO 8000-61. This standard enables a process-approach to data quality management, overcoming the difficulties of isolated data quality activities. This paper introduces DAQUA-MASS, a methodology based on ISO 8000-61 for data quality management in sensor networks. ('''[[Journal:DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor 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...)

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