SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Standard

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. red. / Nuria Oliver; Mary Czerwinski; Aleksandar Matic. Association for Computing Machinery, 2017. s. 444-447.

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Harvard

Andersen, TO & Moll, J 2017, SCAUT: using patient-generated data to improve remote monitoring of cardiac device patients. i N Oliver, M Czerwinski & A Matic (red), Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. Association for Computing Machinery, s. 444-447, 11th EAI International Conference on Pervasive Computing Technologies for Healthcare, Barcelona, Spanien, 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. I N. Oliver, M. Czerwinski, & A. Matic (red.), Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare (s. 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. I Oliver N, Czerwinski M, Matic A, red., Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. Association for Computing Machinery. 2017. s. 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. red. / Nuria Oliver ; Mary Czerwinski ; Aleksandar Matic. Association for Computing Machinery, 2017. s. 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",

}

RIS

TY - GEN

T1 - SCAUT

T2 - using patient-generated data to improve remote monitoring of cardiac device patients

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

ER -

ID: 192383533