نشریه مدیریت اطلاعات سلامت
سال پانزدهم شماره 2 (پیاپی 60، خرداد و تیر 1397)

One of the new effective technologies for healthcare is the use of wearable sensor technology in the environment of internet of things (IOT). In this article, we examined the activities of patients with stress and fatigue complaints as well as the effects of such devices on improving their general health.
In this survey study, General Health Questionnaire (GHQ) was used to assess the status of general health among the individuals in the selected sample in two stages of before and after the intervention; while the rate of changes in some of the measurable indicators was measured through wearable sensor devices during the study period. Given the existing limitations, 26 individuals were randomly selected, and finally 20 of them agreed to cooperate in this research. The obtained results were analyzed using descriptive statistics.
After a thirty-day trial, the overall general health which was initially at an average of 52%, improved after the intervention, reaching an average of 74% for the whole group. The results also showed the effect of increase in mobility rate on improving sleeping conditions, and depth of sleep among the participants.
A proper use of wearable sensor technology, to monitor the activities of individuals, and sending appropriate alert messages via the monitoring center, can improve their general health, reduce stress and fatigue, and modify health behaviors.

Decision making about the location of emergency medical centers, to facilitate quick respond to requests for emergency medical services, is a complex issue for managers of emergency medical services. This research aimed to reduce the response time to emergency medical services requests, using a combination of optimization and simulation methods for placement of emergency bases.
This was a descriptive research. A number of locations in the districts one, three, five, and six of Isfahan City, Iran, were defined as the locations of emergency medical bases, according to criteria such as population density, and the rate of request calls for emergency medical services. Then, the final locations of bases were determined among these possible locations. After determining factors such as the impact of traffic conditions on response time, demand rate, and operating costs, different scenarios were analyzed using Arena software, and the best scenario was selected.
The mean time of response to emergency requests reached nine minutes, with the implementation of the selected scenario, which was close to the international standard of eight minutes.
The results of this research show that without spending a lot of money to create and equip additional bases, different requests can be answered in the shortest possible time. The method presented in this study can be used to solve placement problems of other emergency services such as firefighting stations.

Access to quality information plays an important role in disasters. Due to lack of minimum dataset necessary for health management in disasters, this study aimed to design a minimum dataset for health management in disasters in Iran.
This descriptive study was conducted in 2016 using Delphi technique. 18 individuals were selected and enrolled the study, using heterogeneous sampling method. The Delphi technique was performed in three steps, and mean calculation was used to analyze the data.
The minimum health management dataset of before, during, and after the disaster included 9 data classes and 84 data elements, 9 data classes and 45 data elements, and 6 data classes and 54 data elements, respectively.
Disaster managers and policymakers can use the results of this study to collect and process the correct health information, which facilitates health management during the disasters.

Healthcare centers can achieve social sustainability through adoption of sustainable information systems (SIS). This study aimed to identify and model the factors played a role in affecting the adoption of health care centers with information systems.
The current study was a descriptive survey in the category of applied research. The statistical population of this study included two groups. The first group consisted of experts. The factors were identified and modeled by library studies, and through interviews with experts. The second group consisted of the staff, nurses, head nurses, and supervisors in Alzahra training and treatment center of Isfahan, Iran. The research questionnaire was distributed among the second statistical population. The identified factors were leveled through the interpretive structural modeling. The research hypotheses were then defined based on the model’s levels. The research hypotheses were tested using the analysis techniques of the study route.
The interpretive interpretive-structural model included three levels. The factor of staff along with society and shareholders was placed at the first level. The factor of business ethics was placed at the second level. The third level included factors of social responsibility and organizational responsibility. The research hypotheses were determined based on the model’s levels. The results obtained from model fitness indicated the confirmation of all research hypotheses.
Social responsibility and organizational responsibility are two fundamental and effective factors in adoption of health care centers with sustainable information system. The adoption of sustainable requires senior management support, strategy development, proper policies, and expansion of organizational knowledge storage.

Despite the vast benefits of Iran in the field of medical tourism, the number of tourists entering the country for medical reasons is still negligible. The aim of this study was to identify and prioritize the factors affecting the choice of medical tourism destination.
This was a descriptive study using survey method. The study population consisted of experts familiar with the subject of medical tourism, among which a sample of 12 individuals was selected. A questionnaire was used to measure the importance and priority of the extracted factors influencing the selection of medical tourism destination. Data analysis was performed by utilizing analytical hierarchy process (AHP).
Twenty-four indicators in four dimensions were identified, affecting the choice of medical tourism destination. Among the identified dimensions, the medical technology was more important than the other dimensions.
According to the importance level, the affecting factors on the choice of medical tourism destination are medical technology, staff and treatment process, economic dimensions, and tourism dimensions. Paying attention to these factors and indicators for each of them will increase the attractively of medical tourism to Iran.

The present study aimed to investigate the presence and attentions received by Iranian highly-cited articles in the field of medical science, in various social media platforms.
This descriptive and analytical survey was conducted using scientometrics and altmetrics indicators. The study population comprised of 1288 highly-cited papers from Iran in Essential Science Indicators (ESI) database during 2007-2016. In addition to Essential Science Indicators, Web of Science and Altmetric Explorer database were utilized for data gathering, too.
0.27% of the total publications from Iran in the field of medical sciences were among highly-cited papers (top 1% with the highest number of citations). Moreover, Iranian researchers contributed in 0.28% of world highly-cited papers in the field of medical sciences. 85.5% of Iranian highly-cited papers were mentioned at least once in social media platforms. Mendeley and Twitter were the most promising altmetrics sources for Iranian highly-cited papers in the field of medical sciences. Investigating the characteristics of highly-mentioned articles showed that they had similar publishing patterns. All five highly-alted papers in social media, were produced through international research collaboration, had more than 10 authors, and were published in the Lancet journal.
Comparing to other subject categories, the altmetrics coverage of highly-cited papers in the field of medical sciences was in an acceptable level. Considering the positive and statistical significant association between the number of citations received by papers and their altmetrics scores, we can conclude that highly-cited papers from Iran in the field of medical sciences attract high attentions in social media as well.