(215) Determining Patient Preferences for The Medical Management of Osteoporosis Using Conjoint Analysis

Publication Number: 889

Background: The growing number of medical treatment options for osteoporosis has made it increasingly difficult for patients to select the most appropriate therapy consistent with their own goals and values. Therefore, it is vital for healthcare providers to understand patients’ treatment preferences to improve disease management in a patient-centered way.

Objectives: We examined patient decision-making surrounding osteoporosis medications using conjoint analysis—a technique that quantitatively assesses decision-making.

Methods: We conducted a conjoint analysis survey to quantify the relative importance of 6 osteoporosis medication attributes. Patients with osteoporosis at an academic medical center were invited to complete the online conjoint exercises. The conjoint software determined each person's preferences by calculating importance scores for each medication attribute (higher=more important factor). We also used latent class analysis to identify distinct segments of respondents with similar choice patterns and then used logistic regression to determine if demographics and osteoporosis disease features were associated with latent class assignment.

Results: Overall, 304 participants completed the survey and their average importance scores were the following: efficacy at preventing hip fractures (31.0%), mode of administration (17.5%); risk of serious side effects (16.6%); dose frequency (13.9%); efficacy at preventing spine fractures (12.5%); risk of non-serious side effects (8.4%). Latent class analysis revealed that 60.9% of the cohort most highly prioritized efficacy of medicine at preventing fractures in their decision making, while 39.1% prioritized all factors equally or strongly prioritized other factors. In regression analysis, most demographics and osteoporosis characteristics were not associated with decision making, save for a few exceptions. For example, those who graduated from college (OR 2.14; 95% CI 1.11-4.13) were more likely to prioritize a medication’s efficacy at reducing fracture risk vs. those who did not graduate from college.

Conclusions: We found that only 60.9% of people with osteoporosis prioritize a medication’s efficacy at preventing fracture over all other considerations when selecting among medical treatment options. The remainder of the cohort placed greater value on non-efficacy factors. Furthermore, patient demographics and clinical factors minimally helped to classify what patients value most when selecting an osteoporosis treatment. Thus, to better align patients’ preferences with their medication choice, development of osteoporosis decision aids is warranted.