Telemedicine has been shown to be a feasible and effective vehicle for health care delivery in many research studies, but its uptake has been slow and fragmented. The tele-endocrinology service in Princess Alexandra hospital in Brisbane, is one of instances of successful implementation of telemedicine clinic that has well-integrated into the routine care. The aim of this study was to identify the success factors and challenges for implementation and sustain of this service. Semi-structured interviews were conducted with the consultants, nurses, coordinator, and director of Diabetes and Endocrinology department at the Princess Alexandra hospital where the service is operating. Qualitative data were analyzed using thematic analysis technique. Five major themes emerged: organizational-managerial factors, cultural and social factors, economic and financial factors and factors related to ethical considerations. The main challenges to the implementation of telemedicine clinic included resistance to change, distrust to the provider organization and uncertainty towards continuity of the service, and most important success factors were existing reliable infrastructure, executives support, and economic justification of the service as well as adopting a scalable service model, central coordination and proactive follow-up of patients. Implementation of a telemedicine clinic and provision of remote treatment services are associated with numerous challenges, and various factors are involved in successful implementation and sustainability of such projects. The findings discussed in this paper can inform and inspire health care managers towards successful implementation of similar projects in Iran.

The implementation of automation is considered as a process in organizational development, and change the procedure of affairs. The aim of this paper was to determine the impact of automation on performance and work processes in Shahroud University of Medical Sciences in 2012. This descriptive analytical study was conducted on 239 automation users in presidential field, deputy departments, emergency centers and hospitals of Shahroud University of Medical Sciences. The data were collected by a questionnaire contained 30 questions with five point Likert scale which its reliability and validity had been confirmed. Data analysis performed by Chisquare and Pearson Correlation. To analyze the data SPSS version 20 was used. The average of work time with automation network was 30.05±2.70 hours per day. Only 28% of staffs were satisfied of automation and the rest has relative satisfaction (61.9%) or were unsatisfied (10.1%). The average scores of attitudes toward automation was 64.83±6.9 and 88.3% of staffs had positive attitude, and 11.7% had a negative attitude. Also, there was significant relationship between attitude and satisfaction, as people who had more positive attitudes were more satisfied (P=0.001). The results indicated a positive impact of automation on the performance of employees. Due to problems in implementation and use of this technology, resolving operational problems can increase the efficiency and effectiveness of the organization.

Bacterial meningitis requires timely diagnosis and treatment; otherwise it will have relatively high complications and mortality and morbidity. In the early stages of the disease distinguishing between bacterial meningitis that it is most dangerous type and other type is so complicated and inaccurate. Hence in this study a fuzzy expert system for distinguish bacterial meningitis from other kind of meningitis in children is presented. In the proposed fuzzy system, two fuzzy inference engines (The diagnosis of bacterial meningitis and the proposed new LP) were used. Mamdani model was used in both fuzzy inference engines using Max-Min as AND-OR operators and Centroid method was used as defuzzification technique. The first fuzzy inference engine was evaluated using data obtained from 106 patients’ records admitted with meningitis. Accuracy, sensitivity, and precision of the system in terms of bacterial meningitis diagnosis were 91%, 100% and 89% respectively. The ROC curve was used to show system performance graphically and the area under the ROC curve was 0.947. To measure agreement of system results with the physician diagnosis, Kappa statistics was employed and showed a high relation (K=0.79, P<0.001). Extracted data from 75 cases with non-bacterial meningitis were used to evaluate the second inference engine and accuracy, sensitivity, and precision of this system were 96%, 100%, and 95% respectively, and the area under the ROC curve was 0.96 and Kappa statistic showed a very high agreement between the system output with physician diagnosis (K=0.87,P<0/001). According to the complexity and importance of early diagnosis of bacterial meningitis, and favorable results of the implementation and evaluation of the suggested expert system, therefore this system can be useful for detecting and differentiating acute bacterial meningitis of other meningitis, but more studies must be performed for better assessment and verification of system.

Breast cancer is one of the most common cancers, and also it is the most common type of malignancy in Iranian women that has been growing in recent years. The risk of recurrence is usual in patient. Many factors may increase or decrease the recurrence rate. Data mining methods have been used to diagnose or predict cancer and one of the most application of data mining approaches is prediction of breast cancer recurrence This is a retrospective study. Collected data on 809 patients with breast cancer with 18 fields for each patient were used. Due to excessive missing data only about 665 cases have been used. Since the number of fields in the remaining records with null values have been observed, as a preprocessing and data preparation phases, these values have been estimated by the EM algorithm and using SPSS.v20 software. In this study, a model for prognosis of breast cancer recurrence among patients using J48 tree has been developed. The specificity and sensitivity of the developed model are 53% and 85%, respectively. Moreover, only 14% of patients who have relapsed are known as false negative with developed model. Creating a predictive model with appropriate specificity and sensitivity can warn patients about recurrence and timely preventive measures to prevent progression of the cancer. The False Negative rate is very important in medical prediction models that can make serious results/consequences. In present study this rate is about 14% that seems reasonable amount in term of modeling.

Growing application of medical information systems and various digital communication channels to transfer and share vital and medical information demonstrate the significance of medical data security and privacy policy. Nowadays several block cipher encryption algorithms secure information have done by encrypting them. Most of these algorithms are based on a block cipher that use a predetermined fixed/constant key with at least 128 bits length. In this study encryption performed by Rijndael encryption algorithm using conventional constant and variable cipher key. Mackey Glass, known as chaotic system, attached in key expansion block of Rijndael and play role in place of its conventional key expansion procedure. Mackey Glass generates series of chaotic cipher key, monitored and modified by controlling block. Both methods were evaluated by 6 individual criteria. Results have shown that variable chaotic keys are significantly successful to hide medical image pattern and histogram distribution with 2.47 percent increase in computational time where conventional Rijndael failed. Moreover this modification does not lead to considerable changes in sensitivity. Employing chaotic system in Rijndael key expansion block for medical images improves security of medical information and privacy policy.

The cancellation of a surgery operation not only imposed too much expenditure on the healthcare system, but also waste lots of energy and time of patient and health care provider. The aim of this study was to assess reasons of surgery cancellation, and to provide a comprehensive list of cancellation reasons to implement in hospital information system for improving documentation. This study is an applied-descriptive study which was conducted in two parts. In first part, all medical records of hospitalized patients in Shafa educational hospital during 6 months period which had been assigned a cancellation code based on ICD-10, were assessed. The data were collected through a researcher-made checklist and have been analyzed using SPSS.V18 software. The second part was literature review which provided a list of surgery cancellation reasons. To retrieve the relevant papers PubMed and Google Scholar databases were searched. Finally the results of two parts of the study were combined and a comprehensive list of surgery cancellation reasons was developed. Of 7529 surgical operation, 1229 operations (16.4%) were cancelled. Most of the cancelled surgical operations were related to inappropriate patient’s clinical condition before surgery. Extracted cancellation reasons were categorized into 8 groups. Totally a list of 54 reasons for cancellation was developed. Precise documentation of surgery cancellation reasons in each health care institution in order to determine the reasons and plan to prevent them is essential. Designing an information system with proper information content can support the above mentioned issues.

New diagnostic methods like immunohistochemistry staining in skin cancer can help the physicians to have more accurate diagnosis. The purpose of this study was to compare a method based on decision tree for differential diagnosis of two kind of skin cancer (Basal cell cancer and Squamous cell cancer) based on the results of staining methods. Sixty skin cancer patients’ data from Malaysia were assessed by two methods of decision tree, CART and CHAID, in data mining and using Clementine 12 and SPSS 19. The results of three staining methods including B-cell lymphoma-2 antibody (BCL2), Galectin-3 (Cytoplasm), and Galectin-3 (Nucleus) were analyzed. The best predictive model for decision tree induction was compared with another researcher-made model based on critical values resulted from Receiver Operating Characteristic (ROC) curve analysis. In final synthetic model, the sensitivity and specificity for Basal Cell Carcinoma (BCC) were 82.1% and 100%, and for Squamous Cell Carcinoma (SCC) were 100% and 82.8%, respectively. The overall accuracy of the model was 90.38% and the positive predictive values (PPV) for SCC and BCC were 82.1% and 100%, and the positive likelihood ratios (PLR) were 5. and 5.5 respectively. The decision tree model based on two methods of immunohistochemistry staining in skin cancer, can help in the diagnosis of these malignant disease and provide further studies.

Tele-dermatology is considered by telemedicine service providers about more than a decade. Many reasons, including safety, high diagnostic accuracy compared with physical examination, image-based diagnosis and relatively low cost for installing required systems are making Tele-dermatology successful remarkable. This study introduced Tele-dermatology and its kind and the results of different studies were conducted in clinical area in compare with physical examination is investigated. This review article was done using available library resources and searching online database and articles which published between 2000–2014 in Tele-dermatology field were assessed. Findings showed that, in average the conformity of the proposed diagnosis in skin disease for Tele-dermatology compared with visiting were (79.4 %), for treatment plans were (76.7 %) and reduction of attended visiting was(% 55.6). Also about the servicing fees skin a significant reduction of direct and indirect costs of skin care services show cost- effectiveness of Tele-dermatology. Although most of the researchers and experts agree with the effectiveness of Teledermatology for providing professional health care services and increasing the accessibility of these services, this method is not the final solution to overcome all difficulties related to the shortage of human and financial resources in healthcare system. It should be considered as a complementary to resolve some problems in providing high quality healthcare.