Volume 3, Issue 4 (3-2017)                   jhbmi 2017, 3(4): 259-271 | Back to browse issues page

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Ghazisaeedi M, Tansaz M, Shahmoradi L, Nasiri A, Tahmasebi F, Sahraei Z. Electronic Record for Infertile Patients Based on Traditional Medicine Approach. jhbmi 2017; 3 (4) :259-271
URL: http://jhbmi.ir/article-1-157-en.html
Msc of Health Information Technology, School of Paramedical, Health Information Management Dept., Tehran University of Medical Science, Tehran, Iran.
Abstract:   (6495 Views)
Introduction: Electronic records can be used as one of the key technologies in health care field. Electronic record, with its several capabilities, is an efficient tool for documentation, information exchange and cooperation of health care organizations. The aim of this study was to design an electronic record based on the traditional medicine approach for infertile patients.
Methods: The present study was an applied- development research. First, information requirements questionnaire was filled out by 20 traditional medicine specialists and the obtained data were analyzed through SPSS22 software. Then, a system based on data was designed and given to 10 traditional medicine specialists for evaluation of its practical use and patients’ satisfaction rate.
Results: A majority of data elements in the questionnaire were found necessary by the respondents and in relation to practical use, it gained mean score of 8.6 (out of 9). The designed system, in addition to providing data storage, retrieval and reporting is capable of changing the used data, creating new forms and displaying items with different sizes and types according to the user’s comments and without any need for programming.
Conclusion: According to the obtained results, the electronic medical record designed based on traditional medicine approach was an effective step in managing health data of infertile patients. Designing electronic record based on traditional medicine approach for infertile patient’s increases efficient performance, function, storage and retrieval of health data.
 
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Type of Study: Original Article | Subject: Special
Received: 2017/01/15 | Accepted: 2017/03/15

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