PADE: Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Standard

PADE : Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System. / Knudsen, Søren; Hornbæk, Kasper.

2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019. IEEE, 2019. p. 9-16 8945039.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Harvard

Knudsen, S & Hornbæk, K 2019, PADE: Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System. in 2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019., 8945039, IEEE, pp. 9-16, 10th IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019, Vancouver, Canada, 20/10/2019. https://doi.org/10.1109/VAHC47919.2019.8945039

APA

Knudsen, S., & Hornbæk, K. (2019). PADE: Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System. In 2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019 (pp. 9-16). [8945039] IEEE. https://doi.org/10.1109/VAHC47919.2019.8945039

Vancouver

Knudsen S, Hornbæk K. PADE: Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System. In 2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019. IEEE. 2019. p. 9-16. 8945039 https://doi.org/10.1109/VAHC47919.2019.8945039

Author

Knudsen, Søren ; Hornbæk, Kasper. / PADE : Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System. 2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019. IEEE, 2019. pp. 9-16

Bibtex

@inproceedings{bbc4ff0ceea24b6da57eb3e64bfaf227,
title = "PADE: Supporting Collaborative Visual Analysis of Patient Administrative Systems Data with a Large Touch Display System",
abstract = "We present PADE, a visual analytics tool for collaboratively exploring data from patient administrative systems on large touch displays in meeting contexts. Large touch displays are becoming commercially available, but we have limited knowledge about how they might be used in such a context. We designed PADE based on inquiries with healthcare data analysts tasked with understanding expenses in a healthcare system that serve about six million residents. Our goals in designing the system were to enable the analysts to collaboratively construct hypotheses, quickly generate and execute strategies, and support ad hoc discussions and QA sessions during meetings. We created a set of interaction techniques that let users create new visualizations and combine parts of existing ones. We illustrate these possibilities through a collaborative analysis scenario. Finally, we discuss the possibilities and limitations of PADE, its interaction techniques, and future work in this direction.",
keywords = "Human-centered computing, Information visualization, Interaction techniques, Large displays, multi-touch, multiple views, Visualization systems and tools",
author = "S{\o}ren Knudsen and Kasper Hornb{\ae}k",
year = "2019",
doi = "10.1109/VAHC47919.2019.8945039",
language = "English",
pages = "9--16",
booktitle = "2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019",
publisher = "IEEE",
note = "10th IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019 ; Conference date: 20-10-2019",

}

RIS

TY - GEN

T1 - PADE

T2 - 10th IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019

AU - Knudsen, Søren

AU - Hornbæk, Kasper

PY - 2019

Y1 - 2019

N2 - We present PADE, a visual analytics tool for collaboratively exploring data from patient administrative systems on large touch displays in meeting contexts. Large touch displays are becoming commercially available, but we have limited knowledge about how they might be used in such a context. We designed PADE based on inquiries with healthcare data analysts tasked with understanding expenses in a healthcare system that serve about six million residents. Our goals in designing the system were to enable the analysts to collaboratively construct hypotheses, quickly generate and execute strategies, and support ad hoc discussions and QA sessions during meetings. We created a set of interaction techniques that let users create new visualizations and combine parts of existing ones. We illustrate these possibilities through a collaborative analysis scenario. Finally, we discuss the possibilities and limitations of PADE, its interaction techniques, and future work in this direction.

AB - We present PADE, a visual analytics tool for collaboratively exploring data from patient administrative systems on large touch displays in meeting contexts. Large touch displays are becoming commercially available, but we have limited knowledge about how they might be used in such a context. We designed PADE based on inquiries with healthcare data analysts tasked with understanding expenses in a healthcare system that serve about six million residents. Our goals in designing the system were to enable the analysts to collaboratively construct hypotheses, quickly generate and execute strategies, and support ad hoc discussions and QA sessions during meetings. We created a set of interaction techniques that let users create new visualizations and combine parts of existing ones. We illustrate these possibilities through a collaborative analysis scenario. Finally, we discuss the possibilities and limitations of PADE, its interaction techniques, and future work in this direction.

KW - Human-centered computing

KW - Information visualization

KW - Interaction techniques

KW - Large displays

KW - multi-touch

KW - multiple views

KW - Visualization systems and tools

U2 - 10.1109/VAHC47919.2019.8945039

DO - 10.1109/VAHC47919.2019.8945039

M3 - Article in proceedings

AN - SCOPUS:85078203338

SP - 9

EP - 16

BT - 2019 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2019

PB - IEEE

Y2 - 20 October 2019

ER -

ID: 241598162