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Management of Severe Pulmonary Infection Based on Computed Tomography Examination Procedures

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Objective: In order to shorten the time of diagnosis and reduce the risk of examination for patients with severe pulmonary infection, the inspection process of patients with severe pulmonary infection is managed in a cluster. Methods: We design and make "assistance bed," optimize the inspection process, and compare the total time of inspection and the number of escorts for patients with severe pulmonary infection in the "assistance bed" and traditional inspection groups. We statistically compiled the number of complications, and patient satisfaction, and compare the CT examination of the two groups of patients. Patients surveyed included those contacted with lobar pneumonia, lobular pneumonia, and viral pneumonia. Results: The "assistance bed" group was significantly shorter than the traditional examination group in the total time to go out (16.5 ± 1.4 min vs. 28.1 ± 2.6 min, P < 0.05), and the number of complications was significantly less than the traditional group (4 times 0 times). (P <0.05), which significantly improved the satisfaction of patients' families (78.4% vs. 97.3%, P <0.05), and the CT examination of the patients was also better than the traditional group. The differences were statistically significant, and the number of escorts going out could be reduced by 1 compared with the traditional group. Conclusions: The use of "assistance bed" for transportation of patients with severe pulmonary infection and the centralized management of the inspection process are beneficial to reducing the time of going out for inspection, reducing complications, reducing the number of transport escorts and improving patient satisfaction.

Keywords: ASSISTANCE BED; COMPUTED TOMOGRAPHY; OUT-OF-THE-BOX EXAMINATION; PROCESS CLUSTERING; SEVERE LUNG INFECTION

Document Type: Research Article

Publication date: 01 December 2020

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  • Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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