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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1397576 | PMC |
| http://dx.doi.org/10.1097/00000658-197109000-00009 | DOI Listing |
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Assessing the factors militating against the effective implementation of electronic health records (EHR) in Nigeria.
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Fidson Health Care PLC, Ibadan, Oyo State, Nigeria.
This study assessed the factors militating against the effective implementation of electronic health records (EHR) in Nigeria, the computerization of patients' health records with a lot of benefits including improved patients' satisfaction, improved care processes, reduction of patients' waiting time, and medication errors. Despite these benefits, healthcare organizations are slow to adopt the EHR system. Therefore, the study assessed the factors militating against the effective implementation of the EHR system, the level of awareness of EHR, and the utilization of electronic health records; it also investigated the factors militating against the effective implementation of EHR.
View Article and Find Full Text PDFInfluence of rock bolt reinforcement on shear behaviour of a nonpersistent joint plane.
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School of Civil Engineering and Architectures, Shandong University of Science and Technology, Qingdao, 266590, People's Republic of China.
The impact of rock bolts on the mechanical behavior of nonpersistent joints, including the intricate interactions between the joints, rock bridges, and rock bolts, has received limited investigation despite their effectiveness in reinforcing rock mass discontinuities. In order to tackle this issue, a variety of normal stresses were applied during direct shear tests conducted on artificial rock-like specimens with nonpersistent joints, both bolted and unbolted. Meanwhile, to measure the deformation in the rock bridge and joint plane region, a set of strain gauges were implemented.
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Faculty of Natural Science, Walter Sisulu University, Mthatha, South Africa.
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View Article and Find Full Text PDFReduced bacteria concentrations in wastewater is a key indicator of the efficacy of water resource recovery facilities (WRRFs). However, monitoring the presence of bacterial concentrations in real time at each stage of the WRRF is challenging as it requires taking and processing water samples offline. Although few studies have been proposed to predict bacterial concentrations using data-driven models, generalizing these models to unseen data from different WRRFs remains challenging.
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