Management of the essential data element in the differential diagnosis of oral medicine: An effective step in promoting oral health.

BACKGROUND: Oral soft tissue diseases include a broad spectrum, and the wide array of patient data elements need to be processed in their diagnosis. One of the biggest and most basic challenges is the analysis of this huge amount of complex patient data in an increasing number of complicated clinical decisions. This study seeks to identify the necessary steps for collecting and management of these data elements through establishing a consensus-based framework. METHODS: This research was conducted as a descriptive, cross-sectional study from April 2016 to January 2017, which has been performed in several steps: literature review, developing the initial draft (v. 0), submitting the draft to experts, validating by an expert panel, applying expert opinions and creating version v.i, performing Delphi rounds, and creating the final framework. RESULTS: The administrative data category with 17 and the historical data category with 23 data elements were utilized in recording data elements in the diagnosis of all of the different oral diseases. In the paraclinical indicator and clinical indicator categories, the necessary data elements were considered with respect to the 6 main axes of oral soft tissue diseases, according to Burket's Oral Medicine: ulcerative, vesicular, and bullous lesions; red and white lesions of the oral mucosa; pigmented lesions of the oral mucosa; benign lesions of the oral cavity and the jaws; oral and oropharyngeal cancer; and salivary gland diseases. CONCLUSIONS: The study achieved a consensus-based framework for the essential data element in the differential diagnosis of oral medicine using a comprehensive search with rich keywords in databases and reference texts, providing an environment for discussion and exchange of ideas among experts and the careful use of the Delphi decision technique.

Developing a new intelligent system for the diagnosis of oral medicine with case-based reasoning approach.

OBJECTIVE: Since the clinical manifestations of many oral diseases can be quite similar despite the wide variety in etiology and pathology, the differential diagnosis of oral diseases is a complex and challenging process. Intelligent system for differential diagnosis of oral medicine using the artificial intelligence (AI) capabilities helps specialists in achieving differential diagnosis in a wide range of oral diseases. MATERIALS AND METHODS: First, the essential data elements to design and develop an intelligent system were identified in a cross-sectional descriptive study. The case-based reasoning method was selected to design and implement the system, which consists of three stages: collect the clinical data, construct the cases database, and case-based reasoning cycle. The problem is solved by CBR method in a cycle consisting of four main stages of retrieval, reuse, review, and retention. The evaluation process was conducted in a pilot-based way through the evaluation of the system's performance in the clinical setting and also using the usability assessment questionnaire. RESULTS: The output of the present project is a web-based intelligent information system, which is developed using the Visual Studio 2015 software. The database of this system is the Microsoft SQL Server version 2012, which has been programmed based on Net framework (version 4.5 or higher) using Visual Basic language. The results of the system evaluation by specialists in clinical settings showed that the system's diagnosis power in different aspects of the disease is influenced by their prevalence and incidence. CONCLUSIONS: System development using the artificial intelligence capabilities and through the clinical data analysis has potential to help specialists to determine the best diagnostic strategy to achieve a differential diagnosis of a wide range of oral diseases. The results of evaluation present the potential of the system to improve the quality and efficiency of patient care.

Highlighting a valuable dimension in health care librarianship: A systematic review.

Background: Educational role is one of the most important roles of librarians, which has taken on wider dimensions. A review of the literature on the training programs provided by librarians revealed an evolution of the ideas and trends in this area. This systematic review aimed at providing a clear image of the available educational programs, their target groups, and the way they are performed. Methods: This systematic review was done to identify different aspects of the educational role of medical librarians. It was conducted on the studies published in PubMed database during 2005 and 2015. All the studies that described the educational activities of medical librarians were considered for inclusion. All the studies were evaluated by 2 researchers using a checklist, which was developed as an assessment tool. Variables that were considered were as follow: skills taught by librarians, target group, providing training on information resource, teaching method, and session location. After data extraction process and appraisal, the mentioned variables were classified into main categories. Results: A total of 24 studies met the inclusion criteria. The training skills taught by librarians were classified into 3 main groups: information literacy, evidence-based practice, and health literacy. The target groups were library users, patients, and health professionals. Group training was provided, and if necessary, personal training was also offered. Recently, synchronous online training has also been added to the training methods. Most of the training programs are held in classrooms. Conclusion: By categorizing different aspects of training programs, this study aimed at providing a basis for designing a framework to identify the tasks of educational librarians in health sciences.

Barriers to participation in medical research from the perspective of researchers.

BACKGROUND: The first step toward organizing research activities is to obtain a correct perception of available capabilities. This study was conducted to investigate the researchers' views about barriers affecting research activities. METHODS: This descriptive, cross-sectional study was conducted using the census method. The population consisted of the faculty members of Birjand University of Medical Sciences in 2014. The research tool was a questionnaire in six areas of financial, facility, professional, scientific, personal, and organizational- managerial barriers. The results were analyzed using descriptive statistics and Friedman test. RESULTS: Faculty members confirmed that although all barriers affected research activities, organizational-managerial barriers (3.73 ± 0.63) had the greatest and scientific barriers (3.15 ± 0.93) had the lowest effect, respectively. The results of Friedman test showed that there is a significant difference between the mean values of factors related to various barriers affecting research activities from the viewpoint of the participants' answers. CONCLUSIONS: Research activities are affected by numerous barriers. Strategies, such as empowering researchers, employing new technologies in the creation of research teams, and benefiting from research experts in various stages of research, may have a positive effect on the removal of the barriers.