Background One common model utilized to understand clinical staff and patients' technology adoption is the technology acceptance model (TAM). Objective This article reviews published research on TAM use in health information systems development and implementation with regard to application areas and model extensions after its initial introduction. Method An electronic literature search supplemented by citation searching was conducted on February 2017 of the Web of Science, PubMed, and Scopus databases, yielding a total of 492 references. Upon eliminating duplicates and applying inclusion and exclusion criteria, 134 articles were retained. These articles were appraised and divided into three categories according to research topic: studies using the original TAM, studies using an extended TAM, and acceptance model comparisons including the TAM. Results The review identified three main information and communication technology (ICT) application areas for the TAM in health services: telemedicine, electronic health records, and mobile applications. The original TAM was found to have been extended to fit dynamic health service environments by integration of components from theoretical frameworks such as the theory of planned behavior and unified theory of acceptance and use of technology, as well as by adding variables in specific contextual settings. These variables frequently reflected the concepts subjective norm and self-efficacy, but also compatibility, experience, training, anxiety, habit, and facilitators were considered. Conclusion Telemedicine applications were between 1999 and 2017, the ICT application area most frequently studied using the TAM, implying that acceptance of this technology was a major challenge when exploiting ICT to develop health service organizations during this period. A majority of the reviewed articles reported extensions of the original TAM, suggesting that no optimal TAM version for use in health services has been established. Although the review results indicate a continuous progress, there are still areas that can be expanded and improved to increase the predictive performance of the TAM.

Objective Regardless of the acceptance of users, information and communication systems can be considered as a health intervention designed to improve the care delivered to patients. This study aimed to determine the adoption and use of the extended Technology Acceptance Model (TAM2) by the users of hospital information system (HIS) in paraclinical departments including laboratory, radiology, and nutrition and to investigate the key factors of adoption and use of these systems. Materials and Methods A standard questionnaire was used to collect the data from nearly 253 users of these systems in paraclinical departments of eight university hospitals in two different cities of Iran. A total of 202 questionnaires including valid responses were used in this study (105 in Urmia and 97 in Khorramabad). The data were processed using LISREL and SPSS software and statistical analysis technique was based on the structural equation modeling (SEM). Results It was found that the original TAM constructs had a significant impact on the staffs' behavioral intention to adopt HIS in paraclinical departments. The results of this study indicated that cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use), except for result demonstrability, were significant predictors of intention to use, whereas the result revealed no significant relationship between social influence processes (subjective norm, voluntariness, and image) and the users' behavioral intention to use the system. Conclusion The results confirmed that several factors in the TAM2 that were important in previous studies were not significant in paraclinical departments and in government-owned hospitals. The users' behavior factors are essential for successful usage of the system and should be considered. It provides valuable information for hospital system providers and policy makers in understanding the adoption challenges as well as practical guidance for the successful implementation of information systems in paraclinical departments.

The mothers’ nutritional literacy is an important determinant of child malnourishment. We assessed the effect of a smartphone-based maternal nutritional education programme for the complementary feeding of undernourished children under 3 years of age in a food-secure middle-income community. The study used a randomised controlled trial design with one intervention arm and one control arm (n = 110; 1:1 ratio) and was performed at one well-child clinic in Urmia, Iran. An educational smartphone application was delivered to the intervention group for a 6-month period while the control group received treatment-as-usual (TAU) with regular check-ups of the child’s development at the well-child centre and the provision of standard nutritional information. The primary outcome measure was change in the indicator of acute undernourishment (i.e., wasting) which is the weight-for-height z-score (WHZ). Children in the smartphone group showed greater wasting status improvement (WHZ +0.65 (95% Confidence Interval (CI) ± 0.16)) than children in the TAU group (WHZ +0.31 (95% CI ± 0.21); p = 0.011) and greater reduction (89.6% vs. 51.5%; p = 0.016) of wasting caseness (i.e., WHZ < −2; yes/no). We conclude that smartphone-based maternal nutritional education in complementary feeding is more effective than TAU for reducing undernourishment among children under 3 years of age in food-secure communities.

Malnutrition is one of the most important reasons for child mortality in developing countries, especially during the first 5 years of life. We set out to systematically review evaluations of interventions that use mobile phone applications to overcome malnutrition among preschoolers. The review was conducted and reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses: the PRISMA statement. To be eligible, the study had to have evaluated mobile phone interventions to increase nutrition knowledge or enhance behavior related to nutrition in order to cope with malnutrition (under nutrition or overweight) in preschoolers. Articles addressing other research topics, older children or adults, review papers, theoretical and conceptual articles, editorials, and letters were excluded. The PubMed, Web of Science and Scopus databases covering both medical and technical literature were searched for studies addressing preschoolers’ malnutrition using mobile technology. Seven articles were identified that fulfilled the review criteria. The studies reported in the main positive signals concerning the acceptance of mobile phone based nutritional interventions addressing preschoolers. Important infrastructural and technical limitations to implement mHealth in low and middle income countries (LMICs) were also communicated, ranging from low network capacity and low access to mobile phones to specific technical barriers. Only one study was identified evaluating primary anthropometric outcomes. The review findings indicated a need for more controlled evaluations using anthropometric primary endpoints and put relevance to the suggestion that cooperation between government organizations, academia, and industry is necessary to provide sufficient infrastructure support for mHealth use against malnutrition in LMICs.

The collection of large volumes of medical data has offered an opportunity to develop prediction models for survival by the medical research community. Medical researchers who seek to discover and extract hidden patterns and relationships among large number of variables use knowledge discovery in databases (KDD) to predict the outcome of a disease. The study was conducted to develop predictive models and discover relationships between certain predictor variables and survival in the context of breast cancer. This study is Cross sectional. After data preparation, data of 22,763 female patients, mean age 59.4 years, stored in the Surveillance Epidemiology and End Results (SEER) breast cancer dataset were analyzed anonymously. IBM SPSS Statistics 16, Access 2003 and Excel 2003 were used in the data preparation and IBM SPSS Modeler 14.2 was used in the model design. Support Vector Machine (SVM) model outperformed other models in the prediction of breast cancer survival. Analysis showed SVM model detected ten important predictor variables contributing mostly to prediction of breast cancer survival. Among important variables, behavior of tumor as the most important variable and stage of malignancy as the least important variable were identified. In current study, applying of the knowledge discovery method in the breast cancer dataset predicted the survival condition of breast cancer patients with high confidence and identified the most important variables participating in breast cancer survival.

Background: Assessment of hospital information system (HIS) service quality helps to meet the needs of users and a strategy to expand the interaction between HIS developers and the users. SERVQUAL is an extensively used technique to measure the service quality of information systems. Objectives: The purpose of this study was to assess HIS service quality by the SERVQUAL model in the teaching hospitals affiliated to Urmia University of Medical Sciences (UMSU). Methods: This study is a descriptive analysis carried out in UMSU teaching hospitals in 2017. The sample was comprised of 270 users selected randomly via multi-stage cluster sampling. The modified SERVQUAL questionnaire, which included five dimensions, was used to collect data. The gap between the perceptions and the expectations of the users was calculated and the significance of scores was tested. Results: The highest quality gaps in the five dimensions were related to responsiveness (-1.52) and reliability (-1.34) and also the lowest quality gap was related to tangibles (-0.95). There were significant differences between perceptions and expectations of the users in all SERVQUAL dimensions (P < 0.001). This implied that the quality of the delivered services was lower than what the users expected. Conclusions: Given the greatest gap in responsiveness and reliability, it is essential that HIS vendors focus on providing HIS support and updating services and allocate IT staff with the right knowledge and skills to provide the trust needed to use HIS services in the users.