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SCAUT : using patient-generated data to improve remote monitoring of cardiac device patients. / Andersen, Tariq O.; Moll, Jonas.
Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. ed. / Nuria Oliver; Mary Czerwinski; Aleksandar Matic. Association for Computing Machinery, 2017. p. 444-447.
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Andersen, TO & Moll, J 2017,
SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients. in N Oliver, M Czerwinski & A Matic (eds),
Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. Association for Computing Machinery, pp. 444-447, the 11th EAI International Conference, Barcelona, Spain,
23/05/2017.
https://doi.org/10.1145/3154862.3154922
APA
Andersen, T. O., & Moll, J. (2017).
SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients. In N. Oliver, M. Czerwinski, & A. Matic (Eds.),
Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare (pp. 444-447). Association for Computing Machinery.
https://doi.org/10.1145/3154862.3154922
Vancouver
Andersen TO, Moll J.
SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients. In Oliver N, Czerwinski M, Matic A, editors, Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. Association for Computing Machinery. 2017. p. 444-447
https://doi.org/10.1145/3154862.3154922
Author
Andersen, Tariq O. ; Moll, Jonas. / SCAUT : using patient-generated data to improve remote monitoring of cardiac device patients. Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. editor / Nuria Oliver ; Mary Czerwinski ; Aleksandar Matic. Association for Computing Machinery, 2017. pp. 444-447
Bibtex
@inproceedings{02122239c9fe49b1948bdb8cec68aa28,
title = "SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients",
abstract = "The main problem with remote monitoring of cardiacdevice patients relates to inefficient communication.This is because patients and clinicians are separated inspace and time. In the SCAUT project (2014-2018) weexperiment with asynchronous interaction and explorehow different types of patient-generated data canimprove collaboration. The types of data that patientsgenerate using the SCAUT patient app includessymptom experiences (categories/audio/numericvalues), context (activity level/audio), medication listand travel information. We find that it is very importantto consider how the data that patients enter canbecome useful for patients and clinicianssimultaneously. ",
author = "Andersen, {Tariq O.} and Jonas Moll",
year = "2017",
doi = "10.1145/3154862.3154922",
language = "English",
isbn = "978-1-4503-6363-1",
pages = "444--447",
editor = "Nuria Oliver and Mary Czerwinski and Aleksandar Matic",
booktitle = "Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare",
publisher = "Association for Computing Machinery",
note = "the 11th EAI International Conference ; Conference date: 23-05-2017 Through 26-05-2017",
}
RIS
TY - GEN
T1 - SCAUT
T2 - the 11th EAI International Conference
AU - Andersen, Tariq O.
AU - Moll, Jonas
PY - 2017
Y1 - 2017
N2 - The main problem with remote monitoring of cardiacdevice patients relates to inefficient communication.This is because patients and clinicians are separated inspace and time. In the SCAUT project (2014-2018) weexperiment with asynchronous interaction and explorehow different types of patient-generated data canimprove collaboration. The types of data that patientsgenerate using the SCAUT patient app includessymptom experiences (categories/audio/numericvalues), context (activity level/audio), medication listand travel information. We find that it is very importantto consider how the data that patients enter canbecome useful for patients and clinicianssimultaneously.
AB - The main problem with remote monitoring of cardiacdevice patients relates to inefficient communication.This is because patients and clinicians are separated inspace and time. In the SCAUT project (2014-2018) weexperiment with asynchronous interaction and explorehow different types of patient-generated data canimprove collaboration. The types of data that patientsgenerate using the SCAUT patient app includessymptom experiences (categories/audio/numericvalues), context (activity level/audio), medication listand travel information. We find that it is very importantto consider how the data that patients enter canbecome useful for patients and clinicianssimultaneously.
U2 - 10.1145/3154862.3154922
DO - 10.1145/3154862.3154922
M3 - Article in proceedings
SN - 978-1-4503-6363-1
SP - 444
EP - 447
BT - Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare
A2 - Oliver, Nuria
A2 - Czerwinski, Mary
A2 - Matic, Aleksandar
PB - Association for Computing Machinery
Y2 - 23 May 2017 through 26 May 2017
ER -
