Decision support based needs assessment for cancer patients

Authors:
Andrew Stranieri;Siddhivinayak Kulkarni;Alyx Macfadyen;Anthony Love;Stephen Vaughan
Affiliations:
University of Ballarat, Australia;University of Ballarat, Australia;LaTrobe University, Bendigo, Australia;Univesity of Ballarat, Australia;Grampians Integrated Cancer Services, Ballarat, Australia
Venue:
HIKM '11 Proceedings of the Fourth Australasian Workshop on Health Informatics and Knowledge Management - Volume 120
Year:
2011

Citing 7
Cited 0

Knowledge Based Systems in Law: In Search of Methodologies and Tools

Knowledge Based Systems in Law: In Search of Methodologies and Tools
Identifying Representative Trends in Massive Time Series Data Sets Using Sketches

VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Finding Frequent Items in Data Streams

ICALP '02 Proceedings of the 29th International Colloquium on Automata, Languages and Programming
An Approximate Lp-Difference Algorithm for Massive Data Streams

STACS '00 Proceedings of the 17th Annual Symposium on Theoretical Aspects of Computer Science
Maintaining variance and k-medians over data stream windows

Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Mining data streams: a review

ACM SIGMOD Record
Extended wavelets for multiple measures

ACM Transactions on Database Systems (TODS)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Regular assessment of wellness or quality of life for patients throughout a cancer journey is important so as to identify aspects of life that could lead to distress and impede recovery or acceptance. The emerging trends in assessment are to deploy validated, quality of life instruments on touchscreen computers in medical waiting rooms. However, these add to workload of health care professionals and can be impersonal for patients to use. In this article, an alternate approach is presented that involves a decision support system with natural dialogue that elicits the patient's specific context in a far finer grained manner than is possible with questionnaire based instruments. The system includes a model of heuristics that health care professionals in a locality use to make inferences regarding a patient's quality of life and avenues for referral.