A web-based system for infectious disease data integration and sharing: Evaluating outcome, task performance efficiency, user information satisfaction, and usability

Paul Jen Hwa Hu, Dajun Zeng, Hsinchun Chen, Catherine A. Larson, Chunju Tseng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

To better support the surveillance of infectious disease and epidemic outbreaks by public health professionals, we design and implement BioPortal, an advanced Web-based system for cross-jurisdictional information sharing and integration. In this paper, we report two empirical studies that evaluate the outcomes, task performance efficiency, user information satisfaction, and usability associated with BioPortal. Overall, our results suggest that the use of BioPortal can improve users' surveillance performance as measured by analysis accuracy and efficiency (i.e., the amount of time required to complete an analysis task). Our subjects were highly satisfied with the information support of BioPortal and considered it reasonably usable. Our evaluation findings show the effectiveness and value of BioPortal and, at the same time, shed light on several areas where its design can further improve.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages134-146
Number of pages13
Volume4506 LNCS
StatePublished - 2007
Event2nd NSF BioSurveillance Workshop, BioSurveillance 2007 - New Brunswick, NJ, United States
Duration: May 22 2007May 22 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4506 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd NSF BioSurveillance Workshop, BioSurveillance 2007
CountryUnited States
CityNew Brunswick, NJ
Period5/22/075/22/07

Fingerprint

Web-based System
Data Sharing
Information Dissemination
Data integration
Infectious Diseases
Data Integration
Task Performance and Analysis
Surveillance
Usability
Communicable Diseases
Efficiency
Information Integration
Information Sharing
Public Health
Public health
Empirical Study
Disease Outbreaks
Outcome Assessment (Health Care)
Evaluate
Evaluation

Keywords

  • Cross-jurisdictional information sharing
  • Infectious disease informatics
  • Outbreak detection
  • Public health information systems
  • System evaluation

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Hu, P. J. H., Zeng, D., Chen, H., Larson, C. A., & Tseng, C. (2007). A web-based system for infectious disease data integration and sharing: Evaluating outcome, task performance efficiency, user information satisfaction, and usability. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4506 LNCS, pp. 134-146). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4506 LNCS).

A web-based system for infectious disease data integration and sharing : Evaluating outcome, task performance efficiency, user information satisfaction, and usability. / Hu, Paul Jen Hwa; Zeng, Dajun; Chen, Hsinchun; Larson, Catherine A.; Tseng, Chunju.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4506 LNCS 2007. p. 134-146 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4506 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hu, PJH, Zeng, D, Chen, H, Larson, CA & Tseng, C 2007, A web-based system for infectious disease data integration and sharing: Evaluating outcome, task performance efficiency, user information satisfaction, and usability. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4506 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4506 LNCS, pp. 134-146, 2nd NSF BioSurveillance Workshop, BioSurveillance 2007, New Brunswick, NJ, United States, 5/22/07.
Hu PJH, Zeng D, Chen H, Larson CA, Tseng C. A web-based system for infectious disease data integration and sharing: Evaluating outcome, task performance efficiency, user information satisfaction, and usability. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4506 LNCS. 2007. p. 134-146. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Hu, Paul Jen Hwa ; Zeng, Dajun ; Chen, Hsinchun ; Larson, Catherine A. ; Tseng, Chunju. / A web-based system for infectious disease data integration and sharing : Evaluating outcome, task performance efficiency, user information satisfaction, and usability. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4506 LNCS 2007. pp. 134-146 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{e180fb6ab8ea42fab80b3871dbbf557a,
title = "A web-based system for infectious disease data integration and sharing: Evaluating outcome, task performance efficiency, user information satisfaction, and usability",
abstract = "To better support the surveillance of infectious disease and epidemic outbreaks by public health professionals, we design and implement BioPortal, an advanced Web-based system for cross-jurisdictional information sharing and integration. In this paper, we report two empirical studies that evaluate the outcomes, task performance efficiency, user information satisfaction, and usability associated with BioPortal. Overall, our results suggest that the use of BioPortal can improve users' surveillance performance as measured by analysis accuracy and efficiency (i.e., the amount of time required to complete an analysis task). Our subjects were highly satisfied with the information support of BioPortal and considered it reasonably usable. Our evaluation findings show the effectiveness and value of BioPortal and, at the same time, shed light on several areas where its design can further improve.",
keywords = "Cross-jurisdictional information sharing, Infectious disease informatics, Outbreak detection, Public health information systems, System evaluation",
author = "Hu, {Paul Jen Hwa} and Dajun Zeng and Hsinchun Chen and Larson, {Catherine A.} and Chunju Tseng",
year = "2007",
language = "English (US)",
isbn = "9783540726074",
volume = "4506 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "134--146",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - A web-based system for infectious disease data integration and sharing

T2 - Evaluating outcome, task performance efficiency, user information satisfaction, and usability

AU - Hu, Paul Jen Hwa

AU - Zeng, Dajun

AU - Chen, Hsinchun

AU - Larson, Catherine A.

AU - Tseng, Chunju

PY - 2007

Y1 - 2007

N2 - To better support the surveillance of infectious disease and epidemic outbreaks by public health professionals, we design and implement BioPortal, an advanced Web-based system for cross-jurisdictional information sharing and integration. In this paper, we report two empirical studies that evaluate the outcomes, task performance efficiency, user information satisfaction, and usability associated with BioPortal. Overall, our results suggest that the use of BioPortal can improve users' surveillance performance as measured by analysis accuracy and efficiency (i.e., the amount of time required to complete an analysis task). Our subjects were highly satisfied with the information support of BioPortal and considered it reasonably usable. Our evaluation findings show the effectiveness and value of BioPortal and, at the same time, shed light on several areas where its design can further improve.

AB - To better support the surveillance of infectious disease and epidemic outbreaks by public health professionals, we design and implement BioPortal, an advanced Web-based system for cross-jurisdictional information sharing and integration. In this paper, we report two empirical studies that evaluate the outcomes, task performance efficiency, user information satisfaction, and usability associated with BioPortal. Overall, our results suggest that the use of BioPortal can improve users' surveillance performance as measured by analysis accuracy and efficiency (i.e., the amount of time required to complete an analysis task). Our subjects were highly satisfied with the information support of BioPortal and considered it reasonably usable. Our evaluation findings show the effectiveness and value of BioPortal and, at the same time, shed light on several areas where its design can further improve.

KW - Cross-jurisdictional information sharing

KW - Infectious disease informatics

KW - Outbreak detection

KW - Public health information systems

KW - System evaluation

UR - http://www.scopus.com/inward/record.url?scp=37249092973&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=37249092973&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:37249092973

SN - 9783540726074

VL - 4506 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 134

EP - 146

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -