Abstract
Background: Patient preferences for pharmaceutical treatment of osteoarthritis have been investigated using Conjoint Analysis. Studies have identified the importance of side effects in determining preferences, but noted that methodological limitations precluded further investigation of additional attributes such as hepatic and renal toxicity.
Objective: Following on from a feasibility study of adaptive choice-based conjoint (ACBC) analysis, the aim of this study was to evaluate 8 medication attributes for the pharmaceutical treatment of osteoarthritis (OA).
Setting and Participants: Eleven participants were recruited from members of a Research Users’ Group (RUG) who had been diagnosed with osteoarthritis. RUG members individually complete the ACBC task. Main outcome measures: The relative importance of each attribute and the utilities (part-worth) of each level of each attribute were estimated using ACBC built-in Hierarchical Bayes (HB).
Results: The combined relative importance of the 4 risk side-effect attributes when selecting osteoarthritis medication (kidney and liver side effects, heart attack and stroke side effects, stomach side effects and addiction) was 66% while the effectiveness attribute accounted for 8% of the relative importance of the medication decision.
Conclusions: In this study, the gap between relative importance of 4 side-effect attributes and expected benefit was 66% vs 8%. These preliminary findings indicate that OA patients are most concerned with the avoidance of adverse events and that there is a threshold above which expected benefit has little impact on patients’ medication preferences. The study highlights methodological features of ACBC that may be useful more generally in health services research, but the results must be interpreted in conjunction with the study limitations.
Objective: Following on from a feasibility study of adaptive choice-based conjoint (ACBC) analysis, the aim of this study was to evaluate 8 medication attributes for the pharmaceutical treatment of osteoarthritis (OA).
Setting and Participants: Eleven participants were recruited from members of a Research Users’ Group (RUG) who had been diagnosed with osteoarthritis. RUG members individually complete the ACBC task. Main outcome measures: The relative importance of each attribute and the utilities (part-worth) of each level of each attribute were estimated using ACBC built-in Hierarchical Bayes (HB).
Results: The combined relative importance of the 4 risk side-effect attributes when selecting osteoarthritis medication (kidney and liver side effects, heart attack and stroke side effects, stomach side effects and addiction) was 66% while the effectiveness attribute accounted for 8% of the relative importance of the medication decision.
Conclusions: In this study, the gap between relative importance of 4 side-effect attributes and expected benefit was 66% vs 8%. These preliminary findings indicate that OA patients are most concerned with the avoidance of adverse events and that there is a threshold above which expected benefit has little impact on patients’ medication preferences. The study highlights methodological features of ACBC that may be useful more generally in health services research, but the results must be interpreted in conjunction with the study limitations.
Original language | English |
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Pages (from-to) | 220-224 |
Journal | European Journal for Person Centered Healthcare |
Volume | 5 |
Issue number | 2 |
DOIs | |
Publication status | Published - 6 Jul 2017 |
Keywords
- Adaptive choice-based conjoint analysis
- osteoarthritis
- pharmaceutical treatment
- patient preferences.