Introduction Medicine « impossible ? » to teach on line ? Complexity of the human organism Intricacies of the patient-doctor-interaction Diversity of means for the exploration of the body / diseases: clinical examination, lab tests, imaging, etc.
Introduction Large availability of computers, laptops, palmtops, smartphones, Internet everywhere Changes in the Healthcare sector: – Ageing population – Decreasing lengths of patients’ stays – Less and less time for teaching students.
Introduction In the everyday life: – Use of the smartphone – Large use of computers and Internet for searching information – More and more interactions between computers and users – Large diffusion of video games
Introduction Simulation (mannequins + high-performance computers) – Patient simulation – Organ simulation – For surgical training – For radio training – For anesthesia training More and more simulation courses Insérer ici des images de simulateurs
Introduction: some possibilities Standardized patients: – Human actors playing the role of the patients Computer simulation of biological processes Virtual Patient – Computer based – Simulating the behavior of a real patient
Introduction Since 10 years: – Progressive development of Virtual Patients – Uniquely developed by means of healthcare records New opportunities: – Video games – Serious games
Virtual Patient: Objectives Patient-related medical data that can be organized in various forms Interactive systems between student- computer; between student-computer- teacher Auto-training; auto-evaluation
Insérer ici une copie d’écran de Virtual patient
Definition of Virtual Patient Set of patient-related medical data that can be organized in various forms Allowing the division of the medical data in different classes of systems
Virtual Patients: Different types of knowledge representation 1. Linear systems – The information is displayed in a fixed, pre- defined order – A user’s decision do not have an influence on how a case unfolds – Ex: CASUS system
Virtual Patients: Different types of knowledge representation 2. Branched systems – Offers the students various paths to the solution of a case – The student is confronted to a clinical situation and may select one from a set of options. The user’s decisions affect the treatment of the patient. That may result in different outcomes. – Underlying model: DIRECTED GRAPH with NODES – Ex: OPEN LABYRINTH
Virtual Patients: Different types of knowledge representation 3. Template-based systems – Offer students a large choice of options – The user may select from hundreds of interviews questions, lab tests, physical examinations, treatment methods – Pre-built templates assure the completeness of the data – Ex: CAMPUS or Web-SP
Virtual Patients: Different types of knowledge representation 4. Complex mathematical models – Enables the simulation of physiological regulations – As renal function, respiration or body-fluid balance. – Allows students to experiment the basics of physiology – Using non-linear differential and algebraic functions – Ex: GOLEM
Virtual Patients: Different types of knowledge representation 5. 3D-characters in virtula worlds – In such environment, the user may work on the cases collaboratively with fellow students through the Internet – Virtual worlds – Ex: Second Life
Virtual Patients: Two major groups 1.Problem-Solving: a student has to deal with a large set of raw information and has to decide himself what is relevant: more freedom in information collection. 2.Narrative models: a patient’s personal story line is presented: encourages reflective learning through experience gained in observing the correct medical treatment patterns.
Chapter 3: Virtual patients: advantages and limits
Virtual Patients: advantages Learning material accessible anytime and anywhere Fewer personnel and resources to conduct the courses Solve some ethical problems with bedside teaching Mistakes made by students have no significant consequences less stressful learning
Virtual Patients: advantages Virtual patients are more standardized in teaching than human actors they can convey a higher amount of didactic information. Updating knowledge is easy Multimedia simulations can be more stimulating than plain books.
Virtual Patients: limits Artificial models are not equivalent to real patients. Modern stimulations still require a long way for the realism of symptoms exhibited by real world patients Lack of personal face-to-face feedback from the tutor Connection with Internet can tempt the student with the wealth of distractions. It is difficult to align virtual patients with other didactic activities.
Virtual Patient: the choice of the best software Linear models (CASUS) are easier to implement and explain to experts Linear models do not give to the students the freedom of choices they can have in practice. Branched models (Open Labirynths) are more realistic Template-Based systems (CAMPUS) provide the students with a lot of choices: better for continuing medical education
VP Players VP Players are applications for displaying the content of patient cases. Most of the VP courses require an Internet connection Navigation – most commonly involves selection of options with the mouse – Several players are navigated by natural language recognition; some include speech recognition. M-Learning: use miniaturized devices
VP Authoring tools Components required for the creation of a content, or modification of existing cases. Authoring environment the expert constructs and can modify the core features of the virtual patient (ex: CASUS system) Sometimes, the authoring tools require special software environment (even if free access) for building realistic cases.
Course Managers VP are usually clustered in learning courses Students are enrolled individually or in groups by tutors. Grouping patient into courses facilitates the fulfilment of didactic goals
Student Assessment tools Potential evaluation of the students Provides the teacher with an insight into student’s activity in the learning module Can be exported under the CSV format
Reviews and Evaluation High quality Virtual Patients are a prerequisite Repositories: electronic catalogues Referatories: collections of metadata describing the case (eVIP) Large diversity of functions for Virtual Patient usage.
Serious Games: definition Definition (wikipedia) : A serious game is a game designed for a primary purpose other than pure entertainment. The "serious" adjective is generally prepended to refer to products used by industries like defense, education, scientific exploration, health care, emergency management, city planning, engineering, religion, and politics.game
Serious Game Sometimes called “smart games” Based on the technology of video games Objective: to create low-cost simulations that are both accurate and engaging. Initially: military projects
Serious game in medical education In Europe: “Game and Learning Alliance” (GaLA) to develop technology-enhanced learning Pulse!! (USA) is one of the best serious games: will be included in the training curriculum of many US universities Interaction Healthcare with industrial partners for the development of multimedia e-training applications
Examples of serious games Pulse!! Pulse!! is the first ever, immersive virtual learning space for training health care professionals in clinical skills. Cutting-edge graphics recreate a lifelike, interactive, virtual environment in which heath care professionals practice clinical skills. Dental Implant Training Simulation: Provides a PC, game-based simulation to improve dental student learning outcomes in the area of diagnostics, decision-making and treatment protocols for enhanced patient therapy outcomes and risk management.
Perspectives New perspectives for learning: – Learn by doing – Group learning – Individualization of the learning process – Importance of the simulation – Immersive learning environment Promising
Weaknesses and Limits Most of the serious games in healthcare are projects or prototypes They need strong investments They need the support and sponsorship of healthcare or pharmaceutical industries They have to be developed by companies specialized in the game design
Conclusion Simulation for e-training in healthcare is promising through: – Virtual patients – Simulation of physiological processes – Virtual games Accessible through Internet Current limits: they need – a high technical level – Time from the professors and teachers – Support from sponsors