Assessing the quality of decision support technologies using the International Patient Decision Aid Standards instrument (IPDASi).
OBJECTIVE
To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids).


METHODS
Scale development study, involving construct, item and scale development, validation and reliability testing.


METHODS
There has been increasing use of decision support technologies--adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation.


METHODS
Scale development study, involving construct, item and scale development, validation and reliability testing.


METHODS
Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi). In the fourth Stage (reliability study), eight raters assessed thirty randomly selected decision support technologies.


RESULTS
IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100) for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30), enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68). Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items) was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92).


CONCLUSIONS
This work demonstrates that IPDASi has the ability to assess the quality of decision support technologies. The existing IPDASi provides an assessment of the quality of a DST's components and will be used as a tool to provide formative advice to DSTs developers and summative assessments for those who want to compare their tools against an existing benchmark.
Elwyn
Glyn
G
Department of Primary Care and Public Health, School of Medicine and the School of Psychology, Cardiff University, Cardiff, United Kingdom. elwyng@cardiff.ac.uk
O'Connor
Annette M
AM
Bennett
Carol
C
Newcombe
Robert G
RG
Politi
Mary
M
Durand
Marie-Anne
MA
Drake
Elizabeth
E
Joseph-Williams
Natalie
N
Khangura
Sara
S
Saarimaki
Anton
A
Sivell
Stephanie
S
Stiel
Mareike
M
Bernstein
Steven J
SJ
Col
Nananda
N
Coulter
Angela
A
Eden
Karen
K
Härter
Martin
M
Rovner
Margaret Holmes
MH
Moumjid
Nora
N
Stacey
Dawn
D
Thomson
Richard
R
Whelan
Tim
T
van der Weijden
Trudy
T
Edwards
Adrian
A
D003657:Decision Making; D003661:Decision Support Techniques; D006801:Humans; D010358:Patient Participation; D015203:Reproducibility of Results