Newfangled Procedures Using X-ray to Determine the Cobb Angle in Patients with Scoliosis: An Updated Systematic Review.

BACKGROUND: Scoliosis is a three-dimensional deformity of the spine. It is usually assessed by measuring Cobb angle. Nowadays, due to increasing effectiveness of image processing and machine vision, willingness to apply these methods has improved considerably in determining scoliosis of Cobb angle. METHODS: In accordance with the PRISMA guideline, a broad electronic search of all English language literature was conducted on the topic through four databases, including MEDLINE, Web of Science, Scopus, and the Cochrane Library from 2012 (last search date from earlier review) to 30 March 2017. RESULTS: Twelve studies were included. 90% labeled high-quality were selected for analysis. Eighty percent of the selected studies were published in the period between 2012 and 2017. Three new procedures were used to measure the Cobb angle. One study used automated procedure (7%), two studies used smartphone procedure (14%), and nine studies used the semiautomatic procedure of Cobb measurement (79%). Seven studies reported reproducibility and repeatability. Reproducibility range was 0.72 to 1 in reporting of ICC. Repeatability has a high range in three separated methods. CONCLUSION: Computerized assessment method (Automatic and Semi-automatic) is most commonly performed in Cobb measurement. Semi-automatic is an effective measurement option for computerized assessment Cobb angle. There is no significant difference between manual, computer- based, and smartphone-based methods in described measures.

Recommendations for Using Barcode in Hospital Process.

BACKGROUND: Lack of attention to the proper barcode using leads to lack of use or misuse in the hospitals. The present research aimed to investigate the requirements and barrier for using barcode technology and presenting suggestions to use it. METHODS: The research is observational-descriptive. The data was collected using the designed checklist which its validity was assessed. This check list consists of two parts: "Requirements" and "barrier" of using the barcodes. Research community included 10 teaching hospitals and a class of 65 participants included people in the hospitals. The collected data was analyzed using descriptive statistics. RESULTS: Required changes of workflow processes in the hospital and compliance them with the hospital policy are such requirements that had been infringed in the 90 % of hospitals. Prioritization of some hospital processes for barcoding, system integration with Hospital Information system (HIS), training of staff and budgeting are requirements for the successful implementation which had been infringed in the 80% of hospitals. Dissatisfaction with the quality of barcode labels and lacks of adequate scanners both whit the rate of 100 %, and the lack of understanding of the necessary requirements for implementation of barcodes as 80% were the most important barrier. CONCLUSION: Integrate bar code system with clinical workflow should be considered. Lack of knowledge and understanding toward the infrastructure, inadequate staff training and technologic problems are considered as the greatest barriers.

Evidence-based medicine: going beyond improving care provider viewpoints, using and challenges upcoming.

OBJECTIVES: Evidence Based Medicine (EBM) is proper and an efficient incorporation of the researches and experiences. This is study surveyed the attitudes, awareness, and practice of EBM with specific focus on the barriers to EBM, among clinical residents. METHODS: We conducted a cross sectional survey during September 2012 to February 2013 at the teaching hospitals of Mazandaran University of Medical Sciences among 81 clinical providers from different medical specialties. A valid and reliable questionnaire consisted of five sections and 22 statements were used in this research. Most respondents (83%) completed the questionnaires voluntarily and anonymously. We input the data into Micro- soft Excel 2007. Data were analysed using SPSS 16.0 software. RESULTS: Findings of the study showed that the knowledge of respondents about EBM is low. Their attitude towards EBM was positive but their knowledge and skills in regard to the evidence based medical information resources were mostly limited to PubMed and Google scholar. The main barrier was the lack of enough time to practicing EBM. There was no significant correlation between residency grade and familiarity and use of electronic EBM resources (Spearman, P = 0.116). CONCLUSIONS: The attitude of the respondents towards EBM is fairly positive. But there is a deficit in knowledge and skills of EBM among respondents. Integration and implementation of training approaches like journal clubs or workshops in clinical practices is suggested.

Awareness and using of medical students about mobile health technology in clinical areas.

CONFLICT OF INTEREST: NONE DECLARED. INTRODUCTION: Necessity of data transmission and getting contact with specialists is so evident in impassable regions. In order to solve such problems, there are different solutions one of which is mobile health technology. Being small and user-friendly, easy to enter data and having low expense are some of its advantages. This study aims to define the association between awareness of medical students in clinical stage about mobile health technology application and the rate of their using this technology in educational hospital of Isfahan in 2011. METHOD: The study is a cross-sectional analytical application research. Sixty medical students were selected as samples from a society of 240 medical students. A researcher-made questionnaire was used. The questionnaire included 21 multiple choice and 15 yes no questions, which were corrected to reach a score. A researcher-made checklist with 5-fold Likert scale was used to define the rate of applying such technology. The reliability of questionnaire was confirmed through a test-retest. The collected data were analyzed with the help of SPSS software in descriptive and deductive statistics level. FINDINGS: The highest percentage of awareness about mobile health technology among medical students in the clinical stage of Azzahra educational hospital is 45.6 in nature areas, and their lowest percentage of awareness is 17.8 in the infrastructure area. In addition, their mean awareness of all areas is 54.4. The highest percentage of using mobile health technology by medical students is 14.6 in the education area, and their lowest percentage of usage is 6.8 in the treatment area. Their mean usage of all areas is 9.4 as well. CONCLUSION: The rate of awareness and application of mobile health technology is not favorable. Except for treatment, there is no significant association between the rate of awareness and application of mobile health technology.

Use of data mining techniques to determine and predict length of stay of cardiac patients.

OBJECTIVES: Predicting the length of stay (LOS) of patients in a hospital is important in providing them with better services and higher satisfaction, as well as helping the hospital management plan and managing hospital resources as meticulously as possible. We propose applying data mining techniques to extract useful knowledge and draw an accurate model to predict the LOS of heart patients. METHODS: Data were collected from patients with coronary artery disease (CAD). The patient records of 4,948 patients who had suffered CAD were included in the analysis. The techniques used are classification with three algorithms, namely, decision tree, support vector machines (SVM), and artificial neural network (ANN). LOS is the target variable, and 36 input variables are used for prediction. A confusion matrix was obtained to calculate sensitivity, specificity, and accuracy. RESULTS: The overall accuracy of SVM was 96.4% in the training set. Most single patients (64.3%) had an LOS ≤5 days, whereas 41.2% of married patients had an LOS >10 days. Moreover, the study showed that comorbidity states, such as lung disorders and hemorrhage with drug consumption have an impact on long LOS. The presence of comorbidities, an ejection fraction <2, being a current smoker, and having social security type insurance in coronary artery patients led to longer LOS than other subjects. CONCLUSIONS: All three algorithms are able to predict LOS with various degrees of accuracy. The findings demonstrated that the SVM was the best fit. There was a significant tendency for LOS to be longer in patients with lung or respiratory disorders and high blood pressure.

Clinical care improvement with use of health information technology focusing on evidence based medicine.

OBJECTIVES: Healthcare institutions need timely patient information from various sources at the point-of-care. Evidence-based medicine (EBM) is a tool for proper and efficient incorporation of the results of research in decision-making. Characteristics of medical treatment processes and practical experience concerning the effect of EBM in the clinical process are surveyed. METHODS: A cross sectional survey conducted in Tehran hospitals in February-March 2012 among 51 clinical residents. The respondents were asked to apply EBM in clinical decision-making to answer questions about the effect of EBM in the clinical process. A valid and reliable questionnaire was used in this study. RESULTS: EBM provides a framework for problem solving and improvement of processes. Most residents (76%) agreed that EBM could improve clinical decision making. Eighty one percent of the respondents believed that EBM resulted in quick updating of knowledge. They believed that EBM was more useful for diagnosis than for treatment. There was a significant association between out-patients and in-patients in using electronic EBM resources. CONCLUSIONS: Research findings were useful in clinical practice and decision making. The computerized guidelines are important tools for improving clinical process quality. When learning how to use IT, methods of search and evaluation of evidence for diagnosis, treatment and medical education are necessary. Purposeful use of IT in clinical processes reduces workload and improves decision-making.