A comparison of analytic hierarchy process and conjoint analysis methods in assessing treatment alternatives for stroke rehabilitation

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IJzerman, M.J. and Til, J.A. van and Bridges, J.F.P. (2012) A comparison of analytic hierarchy process and conjoint analysis methods in assessing treatment alternatives for stroke rehabilitation. Patient, 5 (1). 45 - 46. ISSN 1178-1653

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Abstract:Background: With growing emphasis on patient involvement in health technology
assessment, there is a need for scientific methods that formally elicit
patient preferences. Analytic hierarchy process (AHP) and conjoint analysis
(CA) are two established scientific methods – albeit with very different
objectives.
Objective: The objective of this study was to compare the performance of
AHP and CA in eliciting patient preferences for treatment alternatives for
stroke rehabilitation.
Methods: Five competing treatments for drop-foot impairment in stroke were
identified. One survey, including the AHP and CA questions, was sent to 142 patients,
resulting in 89 patients for final analysis (response rate 63%). Standard
software was used to calculate attribute weights from both AHP and CA.
Performance weights for the treatments were obtained from an expert panel
using AHP. Subsequently, the mean predicted preference for each of the five
treatments was calculated using the AHP and CA weights. Differences were
tested using non-parametric tests. Furthermore, all treatments were rank ordered
for each individual patient, using the AHP and CA weights.
Results: Important attributes in both AHP and CA were the clinical outcome
(0.3 in AHP and 0.33 in CA) and risk of complications (about 0.2 in both
AHP and CA). Main differences between the methods were found for the
attributes ‘impact of treatment’ (0.06 for AHP and 0.28 for two combined
attributes in CA) and ‘cosmetics and comfort’ (0.28 for two combined attributes
in AHP and 0.05 for CA). On a group level, the most preferred
treatments were soft tissue surgery (STS) and orthopedic shoes (OS). However,
STS was most preferred using AHP weights versus OS using CA weights
(p < 0.001). This difference was even more obvious when interpreting the
ORIGINAL RESEARCH ARTICLE Patient 2012; 5 (1): 45-56
1178-1653/12/0001-0045/$49.95/0 ª 2012 Adis Data Information BV. All rights reserved. individual treatment ranks. Nearly all patients preferred STS according to the AHP predictions, while >50% of the patients chose OS instead of STS, as most preferred treatment using CA weights. Conclusion: While we found differences between AHP and CA, these differences were most likely caused by the labeling of the attributes and the elicitation of performance judgments. CA scenarios are built using the level descriptions, and hence provide realistic treatment scenarios. In AHP, patients only compared less concrete attributes such as ‘impact of treatment.’ This led to less realistic choices, and thus overestimation of the preference for the surgical scenarios. Several recommendations are given on how to use AHP and CA in assessing patient preferences. [math mode missing closing $]
Item Type:Article
Copyright:© Adis Data Information
Faculty:
Management and Governance (SMG)
Research Group:
Link to this item:http://purl.utwente.nl/publications/79808
Official URL:http://dx.doi.org/10.2165/11587140-000000000-00000
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