Dataset Information

What Matters Most to Patients and Rheumatologists? A Discrete Choice Experiment in Rheumatoid Arthritis.

ABSTRACT:

Introduction

To determine patient and rheumatologist preferences for rheumatoid arthritis (RA) treatment attributes in Spain and to evaluate their attitude towards shared decision-making (SDM).

Methods

Observational, descriptive, exploratory and cross-sectional study based on a discrete choice experiment (DCE). To identify the attributes and their levels, a literature review and two focus groups (patients [P] = 5; rheumatologists [R] = 4) were undertaken. Seven attributes with 2-4 levels were presented in eight scenarios. Attribute utility and relative importance (RI) were assessed using a conditional logit model. Patient preferences for SDM were assessed using an ad hoc questionnaire.

Results

Ninety rheumatologists [52.2% women; mean years of experience 18.1 (SD: 9.0); seeing an average of 24.4 RA patients/week (SD: 15.3)] and 137 RA patients [mean age: 47.5 years (SD: 10.7); 84.0% women; mean time since diagnosis of RA: 14.2 years (SD: 11.8) and time in treatment: 13.2 years (SD: 11.2), mean HAQ score 1.2 (SD: 0.7)] participated in the study. In terms of RI, rheumatologists and RA patients viewed: time with optimal QoL: R: 23.41%/P: 35.05%; substantial symptom improvement: R: 13.15%/P: 3.62%; time to onset of treatment action: R: 16.24%/P: 13.56%; severe adverse events: R: 10.89%/P: 11.20%; mild adverse events: R: 4.16%/P: 0.91%; mode of administration: R: 25.23%/P: 25.00%; and added cost: R: 6.93%/P: 10.66%. Nearly 73% of RA patients were involved in treatment decision-making to a greater or lesser extent; however, 27.4% did not participate at all.

Conclusion

Both for rheumatologists and patients, the top three decision-making drivers are time with optimal quality, treatment mode of administration and time to onset of action, although in different ranking order. Patients were willing to be more involved in the treatment decision-making process.

SUBMITTER: Diaz-Torne C

PROVIDER: S-EPMC7140752 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo comprehensively describe the identification, refinement, and selection of attributes and levels for a discrete choice experiment (DCE) on preferences of patients with rheumatoid arthritis (RA) regarding disease-modifying antirheumatic drugs (DMARDs).MethodsA mixed-methods approach, consisting of three consecutive steps: a literature review, expert recommendations, and focus groups. Attributes and levels were identified by a scoping review and compiled into a list that was evaluated on its relevance by an expert panel. The list that resulted thereafter was used to inform three focus groups, including 23 patients with RA. New attributes and levels could be identified during the focus groups. Also, a ranking exercise was performed. The patients individually ranked the attributes (ie, the ones on the list and newly identified attributes) by relevance. The patients' individual rankings were summed to derive a ranking at group level and make an a priori selection of the most relevant attributes. The group discussions were transcribed for qualitative analysis.ResultsNineteen attributes, each specified by two to seven levels, were identified by the scoping review. The expert recommendations resulted in the removal of one attribute. Furthermore, two new attributes and levels were identified and two attributes were split into two. One new attribute was identified during the focus groups. The results of the ranking exercise and qualitative analysis led to the refinement and selection of the following attributes: route of administration, frequency of administration, chance of efficacy, onset of action, risk of serious infections, risk of liver injury, and risk of cancer. Each attribute was specified by three levels.ConclusionThis study contributes to the limited literature on the development of attributes and levels. Future research should pay more attention to a comprehensive description of this process. It ensures transparency and thereby allows researchers to judge a DCE's quality and generalizability.