The Evaluation of a Personalised Health Information System for Patients with Cancer

Authors:
Alison J. Cawsey;Ray B. Jones;Janne Pearson
Affiliations:
Department of Computing and Electrical Engineering, Heriot-Watt University, Edinburgh, EH14 4 AS, Scotland alison@cee.kw.ac.uk;Department of Public Health, Glasgow University, Glasgow, Scotland;Department of Public Health, Glasgow University, Glasgow, Scotland
Venue:
User Modeling and User-Adapted Interaction
Year:
2000

Citing 3
Cited 17

Computer-based patient education revisited

Journal of Medical Systems - Special issue on the open-joint conference health evaluation, personal preventive medicine, informatics: the new synergies
Generating Personalised Patient Information Using the Medical Record

AIME '95 Proceedings of the 5th Conference on Artificial Intelligence in Medicine in Europe: Artificial Intelligence Medicine
Using classification to generate text

ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics

Adapting Web-Based Information to the Needs of Patients with Cancer

AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Types of Knowledge Required to Personalise Smoking Cessation Letters

AIMDM '99 Proceedings of the Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making
Lessons from a failure: generating tailored smoking cessation letters

Artificial Intelligence
Invoking emotional support in a health crisis.

CHI '08 Extended Abstracts on Human Factors in Computing Systems
Automatic generation of textual summaries from neonatal intensive care data

Artificial Intelligence
User-centered evaluation of adaptive and adaptable systems: A literature review

The Knowledge Engineering Review
Using Natural Language Generation Technology to Improve Information Flows in Intensive Care Units

Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
From data to text in the Neonatal Intensive Care Unit: Using NLG technology for decision support and information management

AI Communications
User Modeling of Disabled Persons for Generating Instructions to Medical First Responders

UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Customization in a unified framework for summarizing medical literature

Artificial Intelligence in Medicine
Does adapted information help patients with cancer?

UM'03 Proceedings of the 9th international conference on User modeling
Adaptive information for consumers of healthcare

The adaptive web
Towards personalized decision support in the dementia domain based on clinical practice guidelines

User Modeling and User-Adapted Interaction
Personalized emergency medical assistance for disabled people

User Modeling and User-Adapted Interaction
Motivating reflection about health within the family: the use of goal setting and tailored feedback

User Modeling and User-Adapted Interaction
Design and implementation of a web-based Tailored Gymnasium to enhance self-management of Fibromyalgia

User Modeling and User-Adapted Interaction
SemScribe: automatic generation of medical reports

USAB'11 Proceedings of the 7th conference on Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society: information Quality in e-Health

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we describe the evaluation of a personalised information system for patients with cancer. Our system dynamically generates hypertext pages that explain treatments, diseases, measurements etc related to the patient's condition, using information in the patient's medical record as the basis for the tailoring. We describe results of a controlled trial comparing this system with a nonpersonalised one. The results of the trial slow significant results concerning the patients' preferences for personalised information. We discuss the implications of our evaluation and results for the development and evaluation of future personalised systems, and adaptive hypertext systems in particular.