Patient Treatment Preferences and Decisional Needs for Heart Failure Medications
Goal: The overarching goal is to characterize the decisional needs, preferences, and values of heart failure (HF) with reduced ejection fraction (HFrEF) patients and their clinicians to improve HFrEF medication decision-making.
Background: Over 750,000 Canadians have HF, approximately half of which is classified as HFrEF. Critically, HFrEF impairs quality of life and has a higher mortality than most cancers. Moreover, despite high-quality evidence supporting several medication options for HFrEF, their use remains low. Shared decision-making (SDM) tools, such as decision aids, can bridge evidence-to-practice gaps and improve the integration of patient preferences to facilitate patient-centred care. However, at present no decision aid exists to facilitate SDM for contemporary HFrEF medications, and little is known about the preferences and decisional needs of patients regarding these medications. Based on the widely-used Ottawa Decision Support Framework (ODSF), SDM tools that address decisional needs can improve decision quality and result in better health outcomes.
Research Aim: During the two-year project period, our team will:
- Identify the decisional needs of HFrEF patients and clinicians regarding HFrEF medications; and
- Elicit patient treatment preferences and values regarding HFrEF medications.
Methods: We propose a comprehensive HFrEF medication decisional needs assessment. For Aim 1, we will conduct semi-structured interviews of 24 HFrEF patients and 12 Canadian HF clinicians, guided by the ODSF , to explore participants’ perceptions of HFrEF medication options and decisional needs, and to identify treatment attributes important to patients when making decisions about HFrEF medications. For Aim 2, we will conduct a discrete-choice experiment (DCE) in a minimum of 280 HFrEF patients to elicit treatment preferences among various medications, and identify patient subgroups based on their preference patterns. DCE is a gold-standard stated-preference technique to elicit relative preferences across several attributes impacting complex decisions. For both aims, we will recruit a representative sample of men and women. Qualitative data will be analyzed using thematic analysis using NVivo 12. We will analyze the DCE using a mixed logit model to estimate individual preference weights and latent class analysis to identify subgroups with distinct preference patterns. Sex and gender data will be collected, and outcomes will be disaggregated for sex and gender differences.
Knowledge Translation and Impact: We will disseminate the results in medical journals, scientific conferences, and directly to our network of primary-care and specialist clinicians, patients, caregivers, researchers, and policymakers, including the Canadian Cardiovascular Society/Canadian Heart Failure Society, Cardiac Services British Columbia, and the HeartLife Foundation. Furthermore, findings will subsequently be used to develop a novel, tailored, point-of-care HFrEF medication decision aid for use in clinical practice, for which we have created a prototype (hfmedchoice.com).