Using Adaptive Choice Based Conjoint (ACBC) analysis to predict individual patient preferences for pharmaceutical treatment of osteoarthritis

Al-Omari, Basem, Frisher, Martin, Croft, Peter and Sim, Julius (2013) Using Adaptive Choice Based Conjoint (ACBC) analysis to predict individual patient preferences for pharmaceutical treatment of osteoarthritis. In: Northumbria Research Conference, 5th - 6th May 2011, Newcastle-upon-Tyne, UK.

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Eliciting individual patient preferences is important alongside eliciting group preferences. Group results are used to understand general population preferences and develop guidelines, while individual patient preferences assist patient-clinician shared decision-making.

To examine whether predicted preferences derived from individual patients through ACBC match their expressed preferences for pharmaceutical treatment of osteoarthritis.

11 participants with osteoarthritis (over 50 years of age) were recruited from the Research Users’ Group at the Arthritis Research UK Primary Care Centre, Keele University. Participants completed a computerised interactive ACBC questionnaire involving 8 attributes: medication availability, frequency, route of administration, expected benefit, risk of addiction, risk of stomach side effects, risk of kidney and liver side effects, and risk of heart attacks and strokes. Individual data were analysed using monotone regression. Patients were individually interviewed after being shown the ACBC predicted results.

For each individual, the ACBC-predicted individual patient’s preferences were in concordance with his or her expressed preferences of different attributes. Furthermore, ACBC assisted patients to trade-off attributes-levels against each other and make decisions about their preferences.

ACBC is a practical tool that can be used in primary care to analyse individual patient preference prior to consultation, without unduly consuming clinicians' time.

Item Type: Conference or Workshop Item (Speech)
Subjects: B900 Others in Subjects allied to Medicine
Department: Faculties > Health and Life Sciences > Nursing, Midwifery and Health
Depositing User: Paul Burns
Date Deposited: 08 Mar 2017 11:40
Last Modified: 01 Aug 2021 05:39

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