شیرین عیانی

Anticoagulation therapy is one of the most important strategies for preventing clot formation and subsequent stroke, with warfarin representing the most widely used oral anticoagulant. However, predicting the outcomes of warfarin administration poses a major challenge for physicians because of the narrow boundary between the therapeutic and toxic levels of warfarin. Clinical decision support systems (CDSSs) can be used as a tool to improve both adherence to clinical guidelines and transfer of evidence-based knowledge to daily clinical practice for dose adjustment, thereby helping reduce medical errors. The aim of this study was to develop a prototype CDSS for predicting warfarin doses according to computerized clinical guidelines.

This applied developmental study involving a qualitative design was conducted in two major steps.First, computer-interpretable guidelines were extracted from existing clinical guidelines as a workflow diagram for warfarin therapy and were subsequently evaluated by an expert panel. Second, a prototype CDSS was designed with PHP programming language and SQL database, and Nielson’s heuristic evaluation checklist was used for usability testing.

In the first step, the findings were presented in two main workflows and two sub-workflows. In the second step, a prototype CDSS was designed. The overall usability of the prototype was found to be at a "relatively acceptable" level, with a rating percentage of 92.09.

The usability evaluation results suggest that CDSSs similar to the one presented herein could serve as valuable clinical decision support tools for estimating warfarin dosage. These promising results call for further research aimed at exploring the feasibility of implementing such systems in clinical settings.

One of the most effective ways to improve the management of asthma in primary care is using guidelines in the patient management process; but due to lack of time, their use is very limited. One way to solve this problem is mechanized guideline in a form of decision-support system that requires computer-interpreted guideline (CIG). In this study, a CIG was developed for asthma management in primary care.

This qualitative study was performed using mini-Delphi method uses a workflow-based approach to develop a CIG. The workflows and data components were extracted through Business Process Model and Notation (BPMN) language and Enterprise Architecture (EA) software. Afterwards, they were confirmed through an expert panel of five asthma specialists.

The developed CIG included three major workflows, four sub-workflows, and 21 data components. Main workflows included treatment, drug interaction, and follow-up time. Sub-workflows were related to treatment workflow that were developed based on the patient visit number and age.

Because the accuracy of this workflow was confirmed by asthma specialists, it is expected that the design of this CIG will lead to development of a cost-effective software for the management of asthma and better detection of drug interactions.

The ability to transfer data over the Internet of Things (IoT) to make right and timely decisions through accurate data collection has provided incredible interactive power and has resulted in an intelligent world with automated decision-making capability. The objective of this study was to investigate the status of IoT-based health information systems in a three-dimensional conceptual framework.
.

In this descriptive-applied study, first, a comprehensive literature review was conducted to extract studies related to the architecture of IoT-based health information systems from the PubMed, Scopus, Web of Science, and IEEE databases. Then, to analyze and classify the extracted information and reach a consensus on explaining the status of IoT-based health information systems, three sessions of contemplation were held with the formation of a specialized committee.

Based on the results of this study, the status of health information systems was elaborated according to the most important functions and applications in three levels including community communication, diagnostic and treatment protocols, and IoT infrastructure. The status of information systems in this framework reflects the relationship between different parts of an organizational structure in the field of health from data collection at the lowest level to knowledge production at the highest level.

The practical concept of the IoT as an underlying infrastructure has been overlooked in the design of most current health information systems. Therefore, the proposed model can be used as a guide for designers and specialists in information technology and medical informatics in designing these systems leading to an increase in the design quality of the systems.

Asthma is uncontrolled in more than half of asthma patients due to inadequate and incorrect management. The main reasons for inadequate management are non-adherence, inadequate knowledge of a general practitioner about patientchr('39')s clinical condition, and not following asthma management guidelines The purpose of this study was to develop a conceptual model for the asthma management system in primary care

In this study, according to the guideline of the Global Initiative for Asthma, workflows for the management of asthma were extracted. Then, the conceptual model of the system was developed with unified modeling language and evaluated by an expert panel, including five asthma and allergy specialists, three informatics specialists and two health information management experts who were selected through non-probability sampling method. Data collection tools were the discussion framework with open-ended questions that reached a collective agreement after discussion on the conceptual model. The collective agreements were applied simultaneously to the diagrams of the conceptual model.

The conceptual model was developed and evaluated in 10 diagrams, including business use-case, use-case, activities, sequences and class diagrams. The diagrams were reported after evaluation. The business use-case shows the main use-case, and the use-case diagrams show the more detailed use-case which is used for the system. The activity diagram shows how the patient was admitted, visited, and managed. The sequence diagram and the class diagram also present the order of asthma management operation, the objects required by the asthma management, and how they are related, respectively.

Given the validity of the conceptual model by asthma and allergy specialists together with informatics and health information management, it can be expected that the current conceptual model will significantly help to design and implement efficient systems that meet the needs of users.

Nowadays, the prevalence of ischemic heart diseases (IHDs) leads to destructive effects such as patient death. Late diagnosis of such diseases as well as their invasive diagnostic approaches made researchers provide a decision support system based on neural network techniques, while using minimum data set for timely diagnosis. In this regard, selecting minimum useful features is significant for designing neural network structure and it paves the way to attain maximum accuracy in obtaining the results.
In this systematic review, valid databases using sensitive keywords were initially searched out to find articles related to "diagnosing the ischemic heart disease using artificial neural networks" and afterwards, scientific methods were used to analyze and classify the content.
Findings: Researchers applied various extractable features from demographic data, medical history, signs and symptoms, and paraclinical examinations, to design the neural network structure. Among them, the features obtained from electrocardiographic test, embedded in paraclinical examinations, had led to a remarkable increase of efficiency in neural network.
Utilizing such diagnostic decision support systems in practical environments depends on their high confidence coefficient and physicians’ acceptability. Therefore, it can be useful to improve maturity in the design of the neural network structure depending on the choice of the minimum optimal features, and to create required infrastructures to input patients’ real, accurate, and flowing data in these systems.

Research has shown that although “Electronic Learning Approach” has played an important role in educational systems related to different industries and various scientific domains in the past decade and accepted by teachers and students, but it is not satisfactory in teaching Medicine domain. Refusing to use patient simulation systems in learning management system is the leading cause of this problem. The aim of this study is to evaluate the electronic learning components and strengths and weaknesses of virtual education to implement patient simulation and present a model consist of required components in order to implement patient simulation system.
In order to obtain components associated with E-learning models and various types of patient simulation systems, after carrying out a thorough search in books and accredited articles, resources analyzing and classifying procedures were accomplished in a scientific manner. Finally, Parsian model was delivered in order to implement patient simulation system.
Parsian Model provides powerful tools and techniques in three groups including: 1.software, 2. Techniques and Methods, 3. Medical Equipment, in order to implement patient simulation system in virtual education environment. It should be noted that in order to equip virtual education environment, medical informatics industry professionals can access to the tools of each group.
The main reason of failure in the previous models of electronic learning in implementing patient simulation systems is non-referring to implementation tools which can lead to necessary results. It is anticipated that the real and achievable tools mentioned in Parsian model can implement all types of patient simulation.