Parsian as a Model for Employing Patient Simulation in the Learning Management System

AUTHORS

Shirin Ayani 1 , Khadijeh Moulaei 2 , * , Ashraf Alimadadi 3 , Mahmoud Bakhtiari 4 , Rafat Bayat 5 , Faezeh Sadeghi 6 , Samaneh Nematolahi 7 , Mohammad Shahrabadi 7

1 PhD in Medical Informatics, Department of Computer Science, Faran (Mehr Danesh) Non-governmental Institute of Virtual Higher Education, Tehran, IR Iran

2 MSc Student of Medical Informatics, Medical Informatics Group, School of Management and Medical Information, Iran University of Medical Sciences, Tehran, IR Iran

3 MD of Endocrinology, Department of Internal Medicine, Endocrinology Branch, School of Medicine, Shahid Beheshti University of Medical Science, Tehran, IR Iran

4 Non-communicables Diseases Research Center, Alborz University of Medical Sciences, Karaj, Iran

5 PhD in Sociology, Department of Management, Faran (Mehr Danesh) Non-governmental Institute of Virtual Higher Education, Tehran, IR Iran

6 MA of English Language and Literature, Department of English Language, Faran (Mehr Danesh) Non-governmental Institute of Virtual Higher Education, Tehran, IR Iran

7 MSc of Information Technology, Faran (Mehr Danesh) Non-governmental Institute of Virtual Higher Education, Tehran, IR Iran

How to Cite: Ayani S, Moulaei K, Alimadadi A, Bakhtiari M, Bayat R, et al. Parsian as a Model for Employing Patient Simulation in the Learning Management System, Iran Red Crescent Med J. 2018 ; 20(S1):e57108. doi: 10.5812/ircmj.57108.

ARTICLE INFORMATION

Iranian Red Crescent Medical Journal: 20 (S1); e57108
Published Online: February 21, 2018
Article Type: Review Article
Received: June 27, 2017
Revised: November 5, 2017
Accepted: November 19, 2017
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Abstract

Background: E-learning is a recent approach in education, commonly appreciated for teaching students in most scientific fields, particularly in the industry. However, in medical education, this approach has difficulties that reduce its performance. Through the survey of the present models defining E-learning components, in respect to the patient simulation systems playing an important role in medical education, some deficiencies of these models have been revealed.

Objectives: In order to provide appropriate tools and techniques for implementing patient simulation within the learning management system, this research aimed at identifying the deficiencies of E-learning models and proposing a new model.

Methods: In this review article, published accredited articles or books were initially searched in order to obtain E-learning components and different types of patient simulation systems. Through a study of E-learning components in selected models, the shortcomings in implementing various kinds of patient simulation systems were determined and the “Parsian” model was subsequently introduced.

Results: According to the results of the conducted research, it was found that the group of component tools in E-learning models, which could be classified in 3 different groups, was not adequate for implementing patient simulation. In the “Parsian” model, necessary tools and techniques were introduced in 3 different groups of software, methods, and techniques and medical equipment. All these groups introduced in the “Parsian” model were applicable.

Conclusions: In the faculty of medicine, professors need patient simulation systems to provide students with E-learning. However, at the moment, there is not such patient simulation system in the existing LMS s all over the world. The LMSs are usually designed to teach courses that are mostly theoretical (rather than practical). Implementation of an LMS, exclusively applicable with high competence for teaching in all the realms of medical sciences, is provided by the means of “Parsian” tools and techniques.

Keywords

E-learning Patient Simulation Medical E-learning Virtual Patient

Copyright © 2018, Iranian Red Crescent Medical Journal. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited

1. Background

The development of Internet and digital technology growth have changed the web to an economic, global, and interactive media to create E-learning. E-learning is an innovative approach that facilitates availability of education and new skills in an interactive infrastructure, so that digital content could be utilized at anytime and anywhere. Adopting new educational methods based on recent technologies and the needs of communities are the 2 major features of E-learning (1-3).

During the recent decades, E-learning development has experienced many benefits and few deficiencies with respect to inclusive education. Providing a wide range of tools and components that allows teachers and students to participate in all related activities is one of these benefits; while maintaining the quality of education improves the rate of transferring theoretical and practical experiences (4, 5). Applying this method could be done by the means of different components; each of these components is used in a way that transfers the concepts to students (6). Although in different fields the combination of these components to implement E-learning has appeared to be successful, the combination of the same components for E-learning in medical education did not ensure its best performance (7). To address the main causes of this problem, examining face-to-face training appears to be crucial. In fact, patients, students, and professors can interact in face-to-face education. Medical students are trained under direct supervision of their professors in educational hospitals so that they will improve their knowledge and experience. They will also make decisions based on observations and results of diagnosis and clinical treatments (8, 9). Simulating the traditional educational method, E-learning in medical education requires components to reflect the dynamism of objects, the details of an action, and the results of senses like olfactory and tactile. The combination of E-learning components, which represent these activities in the form of a simulator, games or virtual reality will lead to a successful educational approach (10-12). In medical training, it is essential to visit patients, which can be carried out through a simulation system in E-learning (13), so that medical students can practice on simulated patients in a safe environment, neither experiencing fear nor jeopardizing the patients. Patient simulation allows these students to develop and evaluate necessary diagnostic and therapeutic skills before facing real patients (14). Based on the simulation system using clinical scenarios, evaluating students’ level of learning during clinical examination and also making careful and appropriate decisions is achievable (15, 16). While due to the lack of a patient simulation system in the existing environment of E-learning, the previously mentioned practices cannot be performed. Medical E-learning could be provided if the patient simulation system in E-learning is established. To achieve this goal, it is necessary to perform situation analysis, which was conducted in the present article.

2. Objectives

The aim of the present study was to survey E-learning components, and the strengths and weaknesses of E-learning in order to implement patient simulation and to present a new model consisting of E-learning components for implementing patient simulation in an LMS.

3. Methods

In this review article, a variety of databases and search engines, including Pubmed, Scopus, Elsevier, IEEE, Springer, Web of Science, Proquest, ACM, and Google Scholar were searched according to the below-mentioned pre-specified search strategy and the relevant Mesh terms. The databases were looked up from April 2017 to December 2017 and published accredited scientific papers or reference books in English were initially investigated in order to obtain E-learning components and different types of patient simulation systems. Due to the fact that there was no time limit for obtaining scientific papers and finding reference books, major retrieved papers were from years 2001 to 2017.

3.1. Search Strategy

A list of search terms commonly used by E-learning components and different types of patient simulation systems was obtained from the published literature. These terms included E-learning, Medical E-learning, Digital Library, Virtual Medical Education, Blended Learning, E-learning Components, E-learning Activities, E-learning Resources, Simulation-Based Learning, Patient Simulation, and Virtual Patient and Composed Simulation.

3.1.1. Inclusion Criteria:

  • The resources being in full text.

  • The resources with up-to-date contents.

  • The resources that define E-learning components in the “E-learning Models”.

  • The resources that define different types of patient simulation systems in the “patient simulation systems group”.

  • The resources that are defined through credible universal references.

3.1.2. Exclusion Criteria:

  • There were not enough E-learning components and different types of patient simulation systems in the resources.

  • Definitions were ambiguous and irrelevant to the E-learning components and different types of patient simulation systems in the resources.

  • In relation to E-learning and patient simulation systems, the resources were not comprehensive.

3.1.3. Resource Extraction

Resource extraction was done using the following methods:

One hundred and one retrieved scientific papers and reference books were chosen by the researchers. Eliminating 15 duplicate references, the remaining 86 articles were classified to 2 groups named “E-learning Model” and “Patient Simulation Systems”. The rest of the papers and books in both groups were compared based on certain inclusion and exclusion criteria.

In both groups, more comprehensive papers and more suitable samples of similar models were preferred. Accordingly, 17 articles and books introducing E-learning models were selected for the study (17-34), as well as 15 articles concerning patient simulation systems chosen for the analysis (35-49). The search results are shown in Figure 1. Additionally, the 5 most usable E-learning systems among top 10 open source management systems including: 1. eFront, 2. Dokeos, 3. Moodle, 4. LRN, and 5. Canvas (50) were preferred for further analysis.

A Scheme of the Systematic Research Processes of This Study
Figure 1. A Scheme of the Systematic Research Processes of This Study

3.2. Analysis of Models and Presenting “Parsian” Model:

3.2.1. Studying and Comparing E-learning Models

Due to the vardiation of names and concepts of E-learning components and their group in different E-learning models, in order to provide further comparison, it was necessary to have a unified definition of names and concepts for each one of the E-learning components and their group. For this purpose, the following procedures were accomplished respectively:

  • First, regarding the concept, those E-learning components that appeared to be extremely similar and overlapped each other were classified in the same group.

  • Then, E-learning components in each group were studied. Based on frequently used names assigned to the components, a unified name was chosen for each component. Meanwhile, similar definitions for each component resulted in a single description for each component. Ultimately, among frequently used names of the components, an appropriate name was selected for each component group.

  • A table containing components group, the components and their descriptions were provided for analysis.

3.2.2. Studying and Classifying Patient Simulation Systems:

  • The patient simulation system was studied and then classified to 3 groups.

  • Problems of implementing patient simulation in learning management system were introduced by E-learning components.

3.2.3. Introducing the “Parsian” Model:

To resolve the existing problems in E-learning models, the “Parsian” Model encompassing essential tools and techniques was presented to implement patient simulation systems.

4. Results

4.1. E-learning and Its Components

The components are inseparable parts of E-learning systems. In fact, E-learning provides teaching and learning with different components (23). In some resources of this study (17-34), E-learning components were identified. In the present research, accomplishing the processes discussed in the method section, a classification of components was proposed.

In Table 1, demonstrating a classification of the components group, the components of each group and the concept of each component were presented. The components and their concepts are discussed below in detail.

4.2. Strategies and Activities

This group contains components, such as educational missions, educational objectives, educational strategies, educational processes, and educational roles. Strategies and activities specify how teachers and students can interact (51).

4.3. Resources

Electronic libraries hold educational materials, such as books, e-journals, databases, web pages, CDs, and other electronic formats (52). Library resources can be available in the form of e-books, films, papers, files and links in various audio, video, and multimedia or text format. It is possible to define a particular library for each course and also define a general library for all the courses in an LMS (52).

4.4. Tools

E-learning tools include a wide range of various usages (53). They can be divided to 5 major components as follows:

  • Communication Tools: Synchronous and Asynchronous

  • Web Tools

  • Remote Access Tools

  • Monitoring Tools and Internet Navigation

  • Search Tools

4.5. Assessment

Assessment is an essential part of education. Assessment methods can be performed between teachers and their students, between students or as self-assessments (54).

The study of the use of this components group in selected LMSs (including: 1. eFront, 2. Dokeos, 3. Moodle, 4. LRN, and 5. Canvas) clarifies that although these systems utilize all components group, they approvingly emphasize on employing the components of Tools Group. Therefore, the systems use these components to provide high quality services.

The patient simulation system is a software for practicing and learning, which can simulate the characteristics of a real world. This kind of simulation helps the teacher represent reality, provide control, and evaluate the learning environment and receive feedback (35). The patient simulation system enhances patient safety and optimizes treatment outcomes. This system is a tool for practicing and designing a clinical decision-making. Patient simulation scenarios act like a bridge between theories and clinical experiences. Working on a patient simulator supports the students in visualizing the physiological reactions that may not be comprehensible through the study of their courses (11).

According to the resources reviewed in this study (35-49), patient simulation can be categorized to 3 general groups: 1. “Medical Equipment-based Simulation”, 2. “Screen-based Simulation” and 3. “Composed Simulation”. Medical equipment-based simulation can apply different mannequins or medical devices and sensors for patient simulation (55). The obtained data from this simulation equipment can be transferred to computer systems; subsequently, medical students’ feedback and their decisions are controlled based on them.

Table 1. Component Groups and Their Components
RowsComponents GroupsComponentsIndex
1Strategies and activitiesEducational missionEducational development in special scientific fields to achieve specific results
Educational strategiesProblem solving simplification
Promoting cooperation and social dialogue
Explaining diction and ideology
Supporting multiple perspectives
Supporting modeling comprehension
Defining a practical framework
Explaining appropriate learning processes, activities and tasks
Facilitating active roles
Blended learning
Educational activitiesDefinition of educational methods
Content management
Educational rolesTrainer, learner and technology
2ResourcesDigital Libraries and Electronic ResourcesIncluding e-books, films, papers, files and links
3ToolsSynchronous communication toolsText-based communication, such as chat, message and etc. or audio conferencing tools such as voice and video
Asynchronous communication toolsNews groups and e-mail
SoftwareReport builder, adobe connect and other systems
Web toolsBlogs, wikis, and social networks
Remote access toolsTelnet, file transfer protocol
Video Teleconferencing
Mobile
Monitoring tools and internet navigationText-based browser, graphical browser, VRML browser and plugins
Search toolsSearch engines, wikipedia and encyclopedia
4AssessmentBased on knowledgeUsing multiple-choice questions
Based on performanceScientific structured clinical examination
Based on behavior and attitudeDiscussion and negotiation in a dialogue forum or using tools such as wikis
Based on actionNotebooks and electronic records

In screen-based simulation, as an application, some software are used for patient simulation (56). In such simulations, there is a great deal of generated data concerning the questions, and their related answers should be previously recorded. This software can employ the data of the patient's history, physical, and para-clinical examinations (57). It can use two-dimensional or three-dimensional visual environments (55). Unlike medical equipment-based simulation, this kind of patient simulation does not require any special equipment.

In the composed simulation, medical equipment-based simulation, and screen-based simulation are used in combination. In Table 2, different types of patient simulation systems, their advantages, and disadvantages can be studied.

Table 2. Different Types of Patient Simulations
RowsPatient Simulation TypesFeatures and AdvantagesDisadvantages
1Medical equipment-based simulationThey have sensors and they are able to transfer the senses.There is no possibility of questioning, answering or monitoring diseases. For each disease, it should be designed in particular.
2Screen-based simulationObserving virtual realityThere is no sensor and there is no possibility of transferring senses. For each disease, it should be designed in particular.
Possibility of questioning and answering
Having massive data for decision-making
3Composed simulationIncluding the advantages of the groups aboveFor each disease, it should be designed in particular.

5. Discussion

In 2006, Issenberg introduced a patient simulation model of tools to the world. In Table 3, his model was presented to accommodate patient simulation in E-learning (58).

Table 3. “Issenberg” Model and Its Components
RowsComponents GroupsComponentsExplanation
1Strategies and aActivitiesRange of difficulty degreeStudents have to undergo skill training according to the degree of difficulty.
Multiple educational strategies
Clinical diversityLearning strategies based on simulation include the following: Coach-centered Educational Format, Small Group Instruction, and Independent Study.
Defined Results and CriteriaSimulation should comprise of a wide range of disease.
2ResourcesIntegration and combination of resources and training programsUsing a combination of reliable multiple resources
3ToolsRepeating exercisesLearners focus on repeating and redoing training in order to improve the skills and repeated action.
Self-learningFor active self-learning and training experiences should be standardized and then used.
Controlled environmentLearning will be more successful in a controlled training environment and under the supervision of simulation masters.
4AssessmentRealism and credibility of simulatorIt has been tried to approach the behavior of a simulated system to reality.
FeedbackThe feedback on the learning experience is an important feature of simulation-based training.

It is notable that in implementing the patient simulation system in LMS, this model or similar ones are not practical enough. According to the obtained results, it seems that the main reason for the inefficiency of such models is the shortage of required tools and techniques, yet no precise tool has been introduced for such model; however, the introduction of the “Parsian” model helps solve this problem.

5.1. “Parsian” Model

The “Parsian” model is introduced to provide accurate tools and techniques in order to solve the mentioned problems. In this model, all the components presented in Table 1 are accepted, excluding tools group named Tools and Techniques Group. Tools and Techniques group is classified to 3 subgroups, including software, methods and techniques, and medical equipment as shown in Table 4.

Table 4. Components Groups of the “Parsian” Model
RowsComponentsComponentsExplanation
1SoftwareElectronic medical recordsIncluding medical history, physical examination and para-clinical examination based on patient visits
Dynamic workflowIn this way, scenarios based on clinical guidelines are fed in the simulator software and accurate feedback that was supposed to be received from the students is defined.
Virtual realityShowing the real world through E-learning
Picture archiving and communication system (PACS)Picture Archiving and communication System used for storing and retrieving medical images
2Methods and techniquesArtificial intelligenceProviding the possibility of simulating in the absence of knowledge, based on certain volume of data
3Medical equipmentSensorsReflecting the patient’s condition

In the following section, each component group of the “Parsian” model, along with their characteristics will be discussed.

5.2. Software

5.2.1. Electronic Medical Records for Patient Simulation

The Electronic Medical Record can organize, store, and retrieve patient care information. This system transfers the required data to the physician at the right time, results in proper decision-making, and prevents medical errors (59). It is possible to use this system for educating medical students in 2 ways (60, 61): according to the first approach, the students can use real data available in Electronic Medical Records while the data is associated with the diagnosis and treatment of diseases and the confidentiality of patients’ information is taken into account. Based on the second approach, unreal but simulated data, related to diagnosis and treatment, should be embedded by professors in this system. Afterwards, the students can study the knowledge taken from the system's data and they can be asked to study a part of the data, make appropriate decisions, and compare them with existing responses in the system. In this way, it is possible to explore hidden knowledge established by the professors on the system.

5.2.2. Dynamic Workflow

A flowchart is a standard tool for preparing graphical documentation and logical design to create a model for a system. Furthermore, this diagram is used to design systems and conceptual model. The process flow can be modeled to various levels through this diagram (62-64). The professors can use this tool to design workflow diagrams obtained from medical books and guidelines in the educational system (65).

Various diagnostic and therapeutic scenarios, along with appropriate feedback that should be received from the students, can be defined by the professors in the educational system. There is no need to change the system structure or re-program the software, yet it is the professors' task to manage this flexible educational system.

The most challenging concern of the physicians and professors is entering medical scenarios to the computer that can be solved by using this tool. Solving this problem provides the possibility of rendering medical scenarios to computerized knowledge. Thus, it is feasible to have diverse scenarios designed by a professor in order to educate and evaluate the students. Due to the variety of diseases, diagnostic and therapeutic scenarios and the complexity of medicine, an educational system that allows users to draw workflows can be regarded as a fundamental infrastructure to implement the patient simulation system in LMS.

5.2.3. Virtual Reality

Virtual Reality (VR) is a computer-based software capable of simulating objects in a multi-dimensional environment. It utilizes various tools, such as glasses, or creates hologram images, stereo sound, and other things to create a sense of the real environment (66, 67). Formerly, large volumes of VR files and Internet bandwidth limitations would cause disruption in the use of this type of tool. However, today, because of the increasing bandwidth and improvement of compressed image algorithms to reduce the size of VR files, the virtual reality simulator is used as a valuable educational tool (68). Virtual Reality can represent an actual environment and also allows the students to feel the real elements. For example, medical students can observe virtual patients or virtual operating rooms and examine necessary equipment before performing practical exercises (69).

5.2.4. Picture Archiving and Communication System

Picture Archiving and Communication System (PACS) is an advanced technology, which is capable of storing, retrieving, and showing images with the use of special devices (70-72). This system stores pictures and videos received by medical equipment, and documents related to the diagnosis.

Since old pictures and videos of the patients are used for educating medical students, in a virtual learning environment, the system should provide high-quality images and pictures in full color. Physicians can give the students selected pictures and videos and once the educational phase is accomplished, they can assess the students’ knowledge.

5.3. Methods and Techniques

5.3.1. Artificial Intelligence

An approach, encompassing various techniques, is used to detect repeating patterns in order to predict the optimal diagnosis and treatments (73). In some cases, there is no accurate or specified rule to define the process flow by “dynamic workflow”. Artificial intelligence techniques can simulate a real environment. When there is no explicit knowledge, based on a certain volume of data, the AI approach can be used to simulate a disease. Representing complex conditions and having them under control can be provided by an AI technique.

5.4. Medical Equipment

5.4.1. Sensors

Sensors can reflect a wide range of physical or environmental conditions, such as temperature, humidity, vibration, pressure, sound, smell, and movement (74, 75). The internal memory, processing power, and wireless functionality of sensor devices provide a situation for integrating sensors in LMS in order to enhance the performance of education (74).

Medical sciences rely on the 5 senses of physicians to obtain signs and new findings. The absence of reflection to the 5 senses is considered as a major deficiency in simulation systems and sensors contribute to solve this problem.

5.5. Conclusion

In this study, in addition to evaluating component groups related to E-learning models, a patient simulation system was also surveyed and classified. Comparing the most practical models of E-learning, it was specified that all the models strongly emphasized on the tools components group. However, these tools were not adequate enough for patient simulation.

The main cause of the failure of patient simulation systems in E-learning was the absence of precise methods and techniques to achieve the desired results. As a solution to this problem, the “Parsian” model, holding the necessary tools and techniques for creating an infrastructure was proposed. The real and obtainable tools mentioned in the “Parsian” model can lead to all 3 types of patient simulation systems, including medical equipment-based simulation, screen-based simulation, and composed simulation.

In the “Parsian” model, all the objects introduced in tools and techniques group are available and can be used by medical informatics specialists. The simulation systems utilizing tools and techniques presented by the “Parsian” model can meet the needs of researchers and professors to develop E-learning in medicine.

Acknowledgements

Footnotes

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