ILVI App – Interdisciplinary Longitudinal Virtual Patient Management

ILVI (Interdisciplinary Longitudinal Virtual Patient Management) is a smartphone application that organizes students` learning experience from textbook knowledge to case-based learning. Our first module is tailored to teach medical students interdisciplinary diagnostic management in a resource-oriented setting.

Target group

University and college students.


In today’s era of accelerated scientific advancement, it is vital to equip learners with the skills to apply their textbook knowledge to real-life scenarios. ILVI aims to leverage case-based learning and encyclopedic learning resources into a cutting-edge learning platform that facilitates virtually augmented flipped classroom lectures and formative testing.


ILVI is a low-level smartphone application that aids students in their learning process by navigating them through gradually increasing levels of expertise. First, it introduces users to a multi-media database, where they can familiarize themselves with the background knowledge. ILVI then takes the students to a case-based learning scenario where they can interact with multidimensional avatars, typically patients, to assess their needs and medical complaints. At this point, ILVI employs a financial and a time budget as a gamification strategy in line with focused diagnostics. The student-patient interaction process is monitored and relayed to an interactive assessment tool that guides teachers in a stimulating case discussion that identifies the strengths and challenges of the student cohort using ILVI.

Project Outline

As a first use case, we are applying ILVI at the TUM School of Medicine and Health in the lecture on gerontology. Over the course of one semester, medical students meet longitudinally reappearing virtual patients who develop multiple age-related complications. Students determine the complete diagnostic management for these patients, thereby training clinical reasoning skills and experiencing the interdisciplinary care these patients require.

Studienbezogene Exzellenzstrategie der Technischen Universität München

Principal Investigator

PD Dr. Dr. Alexander Zink, MPH


To be announced

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