J Med Syst
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Electronic medical records are generally used by nurses in hospitals. However, studies investigating views on and evaluations of electronic medical records by nurses are limited in Turkey and in other countries around the world. Thus, in this study, nurses' views on electronic medical record systems will be investigated in terms of use, quality and user satisfaction. ⋯ This study revealed that there are significant differences among the mean quality scores for the EMR systems in the Ministry of health hospital, the university hospital and the private hospital. Interestingly, 59.0% of all participants in this study felt that EMR systems were not well integrated into their workflow. In addition, half of all respondents had not been trained in using EMR systems.
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Nurses are the foundation of any healthcare system. It is essential to alert nurses on time so that they can offer care and comfort without any delay. Pager messages (short messages) represent an important part of the overall hospital communication network. ⋯ With this overall design, pager messages can be sent from any computer that has an Internet connection on the hospital network. A logging scheme is also introduced to assess the performance of the TAP. NET.
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Electronic anamnesis is to transform ordinary paper trails to digitally formatted health records, which include the patient's general information, health status, and follow-ups on chronic diseases. Its main purpose is to let the records could be stored for a longer period of time and could be shared easily across departments and hospitals. Which means hospital management could use less resource on maintaining ever-growing database and reduce redundancy, so less money would be spent for managing the health records. ⋯ In order to verify the reliability of the proposed system framework, we have also conducted a security analysis to list all the possible security threats that may harm the system and to prove the system is reliable and safe. If the system is adopted, the doctors would be able to quickly access the information while performing medical examinations. Hence, the efficiency and quality of healthcare service would be greatly improved.
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This article aims at building clinical data groups for Electronic Medical Records (EMR) in China. These data groups can be reused as basic information units in building the medical sheets of Electronic Medical Record Systems (EMRS) and serve as part of its implementation guideline. The results were based on medical sheets, the forms that are used in hospitals, which were collected from hospitals. ⋯ As a pilot study of health information standards in China, the development of EMR data groups combined international standards with Chinese national regulations and standards, and this was the most critical part of the research. The original medical sheets from hospitals contain first hand medical information, and some of their items reveal the data types characteristic of the Chinese socialist national health system. It is possible and critical to localize and stabilize the adopted international health standards through abstracting and categorizing those items for future sharing and for the implementation of EMRS in China.
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In this study, power spectrum of the EEG data and the heartbeat data obtained from 250 patients has been applied to the designed Neural network system. A backpropagation artificial neural network has been developed which contains 53 nodes in the input layer, 27 nodes in the hidden and 1 node in the output layer. In the artificial neural network inputs, the power spectral density values corresponding 1-50 Hz frequency interval of the EEG slices which has 10 seconds of time interval, the ratio of the total of the PSD values of current EEG slice to the total PSD values of EEG slice of pre-anesthesia, the ratio of the total PSD values of the EEG data to the total PSD values of the previous EEG data, and the previous anaesthetic gas ratio values have been applied and the network has been educated. ⋯ In the anesthetic gas prediction according to the anesthesia level, successful results have been obtained with the designed system. The system has been able to correctly purposeful responses in average accuracy of 94% of the cases. This method is also computationally fast and acceptable real-time clinical performance has been obtained.