help button home button JAMIA Bigger figures
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS

This Article
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Brennan, P. F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Brennan, P. F.

Journal of the American Medical Informatics Association, Vol 2, 250-259, Copyright © 1995 by American Medical Informatics Association


ARTICLES

Patient satisfaction and normative decision theory

PF Brennan
Case Western Reserve University, Cleveland, OH 44106-4904, USA.

This article explores the application of normative decision theory (NDT) to the challenge of facilitating and measuring patient satisfaction. Patient satisfaction is the appraisal, by an individual, of the extent to which the care provided has met that individual's expectations and preferences. Classic decision analysis provides a graphic and computational strategy to link patient preferences for outcomes to the treatment choices likely to produce the outcomes. Multiple criteria models enable the complex judgment task of measuring patient satisfaction to be decomposed into elemental factors that reflect patient preferences, thus facilitating evaluation of care in terms of factors relevant to the individual patient. Through the application of NDT models, it is possible to use patient preferences as a guide to the treatment planning and care monitoring process and to construct measures of patient satisfaction that are meaningful to the individual. Nursing informatics, with its foundations in both information management and decision sciences, provides the tools and data necessary to promote care provided in accord with patient preferences and to ensure appraisal of satisfaction that aptly captures the complex, multidimensional nature of patient preferences.





HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 1995 by the American Medical Informatics Association.