TY - GEN
T1 - Simulating clinical guidelines for medical education
AU - Bottrighi, Alessio
AU - Molino, Gianpaolo
AU - Piovesan, Luca
AU - Terenziani, Paolo
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/7/10
Y1 - 2019/7/10
N2 - Education is notoriously a challenging task in the healthcare context, where several new methodologies are being introduced to complement ―traditional learning. In particular, the importance of approaches based on (i) simulation and on (ii) clinical practice guidelines is continuously growing. While until now such approaches have been developed separately, in this paper we propose the first approach to education in medicine exploiting both techniques (i) and (ii). Indeed, clinical practice guidelines encode the best medical practices, and, in conjunction with simulation techniques, are suitable to teach ―how to operate on patients, but without the need of ―physically having\acting on real patients. In this paper, we propose such a new methodology, based on GLARE-Edu, an educational extension of GLARE (Guideline Acquisition, Representation and Execution), a domain-independent system for the management of GLs. GLARE-Edu can be used to ―simulate the direct application of GL ―best practices to a (simulated) patient or to provide a ―second opinion simulation: a student must indicate how s\he would treat a (real or invented) patient, and the system is used to indicate to the student where s\he has followed the recommendations of the GL, and where s\he has violated them.
AB - Education is notoriously a challenging task in the healthcare context, where several new methodologies are being introduced to complement ―traditional learning. In particular, the importance of approaches based on (i) simulation and on (ii) clinical practice guidelines is continuously growing. While until now such approaches have been developed separately, in this paper we propose the first approach to education in medicine exploiting both techniques (i) and (ii). Indeed, clinical practice guidelines encode the best medical practices, and, in conjunction with simulation techniques, are suitable to teach ―how to operate on patients, but without the need of ―physically having\acting on real patients. In this paper, we propose such a new methodology, based on GLARE-Edu, an educational extension of GLARE (Guideline Acquisition, Representation and Execution), a domain-independent system for the management of GLs. GLARE-Edu can be used to ―simulate the direct application of GL ―best practices to a (simulated) patient or to provide a ―second opinion simulation: a student must indicate how s\he would treat a (real or invented) patient, and the system is used to indicate to the student where s\he has followed the recommendations of the GL, and where s\he has violated them.
KW - Computer-Interpretable Guidelines
KW - Practitioners/ Medical Education
KW - Simulation
KW - Testing
UR - https://www.scopus.com/pages/publications/85072901941
U2 - 10.1145/3345094.3345099
DO - 10.1145/3345094.3345099
M3 - Conference contribution
AN - SCOPUS:85072901941
T3 - ACM International Conference Proceeding Series
SP - 66
EP - 72
BT - Proceedings of ICIEI 2019
PB - Association for Computing Machinery
T2 - 4th International Conference on Information and Education Innovations, ICIEI 2019
Y2 - 10 July 2019 through 12 July 2019
ER -