Using MaxDiff Analysis to Elicit Patients' Treatment Preferences for Distal Radius Fractures in Patients Aged 60 Years and Older

J Hand Surg Am. 2023 Jun;48(6):575-584. doi: 10.1016/j.jhsa.2023.03.004. Epub 2023 Apr 5.

Abstract

Purpose: The objective of our study was to determine how the attributes of surgical and nonsurgical distal radius fracture (DRF) treatments affect patient treatment preferences.

Methods: Two hundred fifty patients aged 60 years and older were contacted from a single-hand surgeon's practice, and 172 chose to participate. We built a series of best-worst scaling experiments for the MaxDiff analysis to determine the relative importance of treatment attributes. Hierarchical Bayes analysis was used to generate individual-level item scores (ISs) for each attribute that together have a total sum of 100.

Results: One hundred general hand clinic patients without a history of a DRF and 43 patients with a history of a DRF completed the survey. For the general hand clinic patients, the most important attributes to avoid when choosing a DRF treatment (in descending order) were the longer time to full recovery (IS, 24.9; 95% confidence interval [CI]: 23.4-26.3), longer time spent in a cast (IS, 22.8; 95% CI, 21.5-24.2), and higher complication rates (IS, 18.4; 95% CI, 16.9-19.8). Meanwhile, for patients with a history of a DRF, the most important attributes to avoid (in descending order) were a longer time to full recovery (IS, 25.6; 95% CI, 23.3-27.9), longer time spent in a cast (IS, 22.8; 95% CI, 19.9-25.7), and abnormal alignment of the radius on x-ray (IS, 18.3; 95% CI, 15.4-21.3). For both the groups, the least concerning attributes based on the IS were appearance-scar, appearance-bump, and the need for anesthesia.

Conclusions: Eliciting patient preferences is a vital component of shared decision-making and advancing patient-centered care. As conceptualized in this MaxDiff analysis, when choosing a DRF treatment, patients mostly want to avoid a longer time to full recovery and a longer time in a cast, whereas patients have the least concern about appearance and need for anesthesia.

Clinical relevance: Eliciting patient preferences is a vital component of shared decision-making. Our results may provide guidance to surgeons in discussions on the relative benefits of surgical and nonsurgical DRF treatments, by quantifying the most and least important factors to patients.

Keywords: Best-worst scaling; MaxDiff analysis; distal radius fractures; patient preferences.

MeSH terms

  • Aged
  • Bayes Theorem
  • Decision Making, Shared
  • Humans
  • Middle Aged
  • Patient Preference
  • Radius Fractures* / surgery
  • Wrist Fractures*