The Latest

SEARCH BY KEYWORD
BROWSE BY Category
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.

RegenMed Sponsors University of Wisconsin Capstone Project to Advance Patient-Reported Outcomes in Healthcare

Article
September 1, 2025
RegenMed is proud to sponsor UW–Madison’s Computer Sciences Capstone Project, empowering students to innovate patient-reported outcome tools. Discover how this collaboration is shaping the future of healthcare technology and enhancing patient engagement.
Investing in the Next Generation of Healthcare Technology InnovatorsRegenMed is proud to sponsor a University of Wisconsin–Madison Computer Sciences Capstone Project (CS 639, Fall 2025), joining the ranks of leading organizations such as Epic Systems, Capital One, American Family Insurance, Google, GE HealthCare, and Medtronic that have supported this nationally recognized program.The Capstone program pairs senior undergraduate students with industry partners on real-world software development projects, giving students a chance to tackle meaningful challenges while sponsors gain fresh insights, prototypes, and future talent pipelines. Since launching in 2021, the program has expanded to engage 100+ students and up to 18 sponsors each semester, ranging from Fortune 500 companies to startups and nonprofits.The RegenMed Project: Enhancing Patient-Reported OutcomesRegenMed’s sponsored project, titled “Electronic Patient Reported Outcomes (ePRO) Data Capture”, focuses on improving how patients share their post-treatment experiences.RegenMed’s platform already collects critical treatment information from both clinicians and patients. But one persistent challenge remains: patients often fail to complete outcome surveys in a timely manner. These surveys, known as ePROs, are vital to understanding treatment effectiveness and advancing value-based care.The Capstone team will explore ways to:Redesign the User Experience for patient-facing survey modules.Incorporate Gamification and Rewards to make survey completion more engaging.Develop Web and Mobile Enhancements using tools such as React JS, .NET C#, and AWS Cloud technologies (ECS, Lambda, Cognito, and more).By combining creativity with technical expertise, students will help RegenMed improve patient engagement, generating richer datasets for clinicians, payers, and researchers.Experienced Mentorship for Student SuccessCapstone students benefit from direct mentorship by RegenMed’s leadership and engineering team, including:Dolph Courchaine, RegenMed CIO, with over 40 years of experience in healthcare software engineering.Will Graupmann, RegenMed Software Engineer and UW–Madison alumnus, who brings recent student and startup perspectives.Laura Prey, RegenMed Board Member and IT executive, with more than three decades of experience in healthcare and insurance technology.This mentorship model ensures students learn not only advanced coding and cloud infrastructure, but also the real-world dynamics of healthcare data, insurance, and patient engagement.Why It Matters: Democratizing Healthcare EvidenceThe U.S. spends more than $5 trillion annually on healthcare, much of it on treatments with limited evidence of effectiveness. RegenMed’s mission is to democratize access to treatment-effectiveness data, empowering clinicians, patients, and payers to make better decisions.By sponsoring this project, RegenMed is helping to:Train the next generation of healthcare software engineers.Advance the science of real-world evidence (RWE) and patient engagement.Position Wisconsin students at the forefront of solving one of healthcare’s most pressing challenges.A Proud Tradition of Industry PartnershipsWith sponsors like Epic, GE HealthCare, Google, Amazon/Shopbop, Medtronic, and PBS Wisconsin contributing in past semesters, UW–Madison’s Capstone Program has become a launchpad for impactful collaborations between academia and industry. RegenMed is honored to join this tradition — and to contribute to the future of patient-centered healthcare innovation.
See more
Arrow right

Transforming Musculoskeletal Research With Real-World Evidence

Article
September 1, 2025
RegenMed, in partnership with the Orthopaedic Research and Education Foundation (OREF), has launched M.O.T.I.V.™ — a pioneering initiative to generate structured, peer-reviewed, and clinically meaningful real-world evidence (RWE) datasets across the full spectrum of musculoskeletal (MSK) conditions.
RegenMed and OREF Launch MOTIV™: A Peer-Reviewed Real-World Evidence Library for Musculoskeletal Innovation RegenMed, in partnership with the Orthopaedic Research and Education Foundation (OREF), has launched M.O.T.I.V.™ — a pioneering initiative to generate structured, peer-reviewed, and clinically meaningful real-world evidence (RWE) datasets across the full spectrum of musculoskeletal (MSK) conditions. MSK disorders represent one of the largest global health burdens. Nearly one-third of the world’s population will experience an MSK-related condition in their lifetime, from degenerative joint disease and traumatic injuries to bone cancers and rare genetic disorders such as osteogenesis imperfecta. In the United States alone, MSK care costs are estimated to exceed $980 billion annually, nearly 5% of U.S. GDP. Yet despite this immense cost, outcomes for patients remain inconsistent. Scientific progress is slowed by reliance on traditional clinical trials, which are lengthy, expensive, and selective. Meanwhile, insurers and government payers are placing new emphasis on outcomes tracking — such as Medicare’s penalties for providers who fail to collect long-term results on hip and knee replacements. The Limitations of Today’s Data While “real-world evidence” has become a buzzword in healthcare, the vast majority of available datasets are derived from electronic health records, insurance claims, or proprietary algorithms. These sources, though large, are fragmented, unverifiable, and often lack correlation between diagnosis, treatment protocols, and long-term outcomes. The result is evidence that fails to meet clinical utility standards, limiting its role in advancing precision care, improving health equity, or accelerating innovation. What Makes M.O.T.I.V.™ Different The M.O.T.I.V.™ (Musculoskeletal Outcomes Through Informed Validation) program is designed to overcome these barriers. Each dataset in the library is: • Peer-Reviewed by OREF: Every observational protocol is vetted by leading MSK researchers. • Anatomically & Clinically Specific: Defined by one anatomical region, one pathology, one treatment protocol, and one standardized outcomes assessment. • Validatable to Primary Sources: Built for transparency and trust, avoiding unverifiable big-data manipulation. • Longitudinal & Fit-for-Purpose: Meeting FDA requirements for clinical and regulatory use. • Statistically and Clinically Relevant: Designed to support meaningful insights that improve patient care. By setting a new standard for structured, verifiable real-world data, M.O.T.I.V.™ ensures that research and innovation in orthopaedics are both clinically rigorous and widely accessible. Driving Value-Based Care and Innovation The launch of M.O.T.I.V.™ marks a critical step toward achieving value-based care in musculoskeletal medicine. By creating datasets that are trusted, transparent, and clinically actionable, RegenMed and OREF are empowering: • Providers to benchmark treatments and improve patient outcomes. • Insurers and payers to make evidence-based reimbursement decisions. • Researchers to accelerate the path from lab to bedside. • Patients to benefit from more equitable, data-driven care. This initiative positions RegenMed and OREF at the forefront of a healthcare transformation — one where real-world evidence is no longer an aspiration, but a validated, practical tool for medical advancement
See more
Arrow right

Circles: A New Model for Real-World Evidence in Life Sciences

Article
August 27, 2025
Big data RWE is convenient but flawed: stale, incomplete, and legally risky. RegenMed Circles provide a better way — clinically relevant, auditable, and continuously growing datasets that power HEOR, medical affairs, regulatory submissions, and AI.
Life sciences companies spend vast sums on real-world evidence, often relying on massive secondary datasets sold by big data aggregators. While these resources are convenient, familiar, and easy to license, they were never designed to address the nuanced questions that matter most to regulators, payers, and clinicians. The industry now faces an inflection point: the need for high-quality, longitudinal, verifiable evidence that is both strategically relevant and future-proof.The Problem With Big Data RWETraditional big data RWE draws primarily from electronic medical records (EMRs) and insurance claims. These datasets capture billing events and limited treatment codes, but they lack longitudinal outcomes, omit critical variables, and often arrive stale. Many areas of great importance — rare diseases, advanced therapies, and complementary interventions — are invisible in these datasets. Moreover, questions of ownership and legality loom large, with mounting costs and growing scrutiny around unauthorized data use. For artificial intelligence (AI) applications, which increasingly shape pharma’s strategy, these foundations are fragile and risky.Circles: A Better Way ForwardRegenMed’s Circles represent a new paradigm. Built on rigorously defined Observational Protocols (OPs), analogous to randomized controlled trial protocols, Circles generate datasets that are:‍Clinically Relevant: Tailored to specific therapeutic questions and aligned with HEOR, medical affairs, and regulatory needs. ‍Verifiable and Auditable: Every data point is timestamped, source-verified, and traceable. ‍Federated and Equitable: Data remains under local ownership, ensuring broader participation and inclusion of underrepresented populations. ‍Living and Continuously Growing: Unlike static datasets that depreciate, Circles appreciate over time as new cases and longitudinal outcomes are added. ‍AI-Ready: Standardized and proprietary, Circles provide a defensible foundation for training machine learning models without legal ambiguity. Benefits Across The Life CycleCircles provide critical advantages across the product lifecycle: Health Economics and Outcomes Research (HEOR): Strengthened cost-effectiveness models and payer negotiations through longitudinal, auditable outcomes data. Medical Affairs: Enhanced engagement with KOLs, support for outcomes-based contracts, and scientifically credible evidence generation. Post-Market Surveillance: High-quality longitudinal monitoring suitable for regulatory submissions and compliance with safety commitments. Rare Disease Research: Aggregation of small patient cohorts across institutions into statistically meaningful studies. Innovation Enablement: High-quality training datasets for AI, validation for digital health tools, and fuel for translational research. Future Proofing: Alignment with evolving regulatory standards, payer expectations, and AI-driven healthcare ecosystems. Comparative AdvantageWhile big data RWE will not vanish, Circles decisively outperform it in areas where big data structurally fails: rare diseases, post-market safety, outcomes-based reimbursement, and AI model training. Circles datasets are fresher, more complete, and strategically aligned with regulatory and payer needs. Unlike static licensed datasets, they grow in value, establishing a sustainable evidence ecosystem.Practical ImplementationCircles are not disruptive to adopt. They fit into existing budget categories (post-marketing, Phase IV, HEOR, rare disease) and can typically be launched in 4–6 weeks at costs lower than a single-year dataset license. Federated architecture ensures compliance and scalability across geographies, while AI-assisted coding workflows streamline data harmonization.ConclusionThe limitations of big data RWE are becoming more apparent as healthcare shifts toward value-based care, AI-driven analytics, and patient-centered outcomes. Circles are not merely a tactical supplement but a strategic imperative. By delivering clinically relevant, auditable, and continuously growing datasets, they provide life sciences companies with a credible, cost-efficient, and future-proof foundation for evidence generation. Early adopters will not only reap immediate advantages but also lead the industry into the next era of real-world evidence.Contact us to learn more.
See more
Arrow right
Nothing was found. Please use a single word for precise results.
Stay Informed.
Subscribe for our newsletter
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.