Scholarlink

<p>Patient Preference Information (PPI) is increasingly applied across the medical device lifecycle to inform product design, clinical trial planning, regulatory submissions, labeling, and shared decision-making. However, cross-company learnings remain fragmented. This review synthesizes five recent industry case studies illustrating diverse applications of PPI: Edwards Lifesciences (transcatheter tricuspid valve replacement), CVRx (Barostim neuromodulation therapy for heart failure), Medtronic (renal denervation for hypertension), Johnson and Johnson (lung cancer interception therapy), and Abbott (leadless pacemaker feature optimization). Across cases, quantitative stated-preference methods, particularly discrete-choice experiments, predominated. Evidence informed pivotal trial design and regulatory submissions (Edwards Lifesciences, Medtronic), FDA-approved labeling (CVRx), preventive therapy development (Johnson and Johnson), and device feature prioritization post-approval (Abbott). Common enablers included early engagement with regulators, rigorous instrument development with qualitative pretesting, and proactive dissemination. Recurring challenges involved recruiting representative samples, addressing preference heterogeneity, and demonstrating return on investment. These findings underscore the feasibility and value of PPI in advancing patient-centered innovation and regulatory decision-making across the medical device lifecycle.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Patient Preference Information (PPI) in Medical Device Development: A Cross-Industry Review of Use-Cases

  • 期刊论文

  • 发表日期：

    2026年6月20日

查看全文
  • Jonah Golder,
  • Vanessa DeBruin,
  • Alissa Hanna,
  • Ellen Janssen,
  • Korinne Jew,
  • Barry Liden,
  • Amy Pavlock,
  • Dan Stephens,
  • Liliana Rincon-Gonzalez

摘要

Patient Preference Information (PPI) is increasingly applied across the medical device lifecycle to inform product design, clinical trial planning, regulatory submissions, labeling, and shared decision-making. However, cross-company learnings remain fragmented. This review synthesizes five recent industry case studies illustrating diverse applications of PPI: Edwards Lifesciences (transcatheter tricuspid valve replacement), CVRx (Barostim neuromodulation therapy for heart failure), Medtronic (renal denervation for hypertension), Johnson and Johnson (lung cancer interception therapy), and Abbott (leadless pacemaker feature optimization). Across cases, quantitative stated-preference methods, particularly discrete-choice experiments, predominated. Evidence informed pivotal trial design and regulatory submissions (Edwards Lifesciences, Medtronic), FDA-approved labeling (CVRx), preventive therapy development (Johnson and Johnson), and device feature prioritization post-approval (Abbott). Common enablers included early engagement with regulators, rigorous instrument development with qualitative pretesting, and proactive dissemination. Recurring challenges involved recruiting representative samples, addressing preference heterogeneity, and demonstrating return on investment. These findings underscore the feasibility and value of PPI in advancing patient-centered innovation and regulatory decision-making across the medical device lifecycle.