Case Studies: Federated Stroke, EHR-to-CDISC Oncology & Psilocybin

I first met Marie, a 72-year-old retiree curious about trials after a minor stroke, at a community health talk. She asked the question everyone asks quietly: "What will this feel like, and will it help people my age?" That conversation became the through-line for three case studies that show how modern data tools change not just research, but patient experience and outcomes.

Federated stroke trials: sharing insights without sharing raw data

In a multi-center stroke study I followed, researchers used federated analytics workflows for multi-center stroke trials to compare treatment timing and outcomes across 12 hospitals without moving patient records off site. Clinicians could run the same models locally and aggregate results centrally, preserving privacy and speeding insights. A pilot showed average NIHSS scores dropping by 3 points at 90 days and functional independence (mRS 0–2) rising from about 45% to 58% in centers that adopted streamlined protocols.

"I liked that my data stayed at my hospital, but the doctors could still learn from others," Marie said after consenting to remote monitoring.

EHR-to-CDISC pipelines for oncology endpoint harmonization

A second example came from oncology teams wrestling with inconsistent endpoints across EHRs. By building EHR-to-CDISC pipelines for oncology endpoint harmonization, data managers turned disparate notes and lab values into a consistent dataset for progression-free survival and response rates. This cut manual curation time by roughly 70% and allowed teams to report a unified median PFS of 8.5 months in a pooled analysis. For seniors and older adults, clearer endpoints meant faster decisions about therapies and fewer redundant tests.

Predictive recruitment models: finding the right patients sooner

Across several studies, including hypertension and MS trials, predictive recruitment models for hypertension and MS helped sites identify likely candidates from routine records. Those models increased enrollment speed by nearly 40% in one network and improved diversity by flagging underrepresented populations. Older adults who previously missed opportunities were matched to studies through trial discovery tools and patient-researcher connections.

Privacy-preserving analytics for psilocybin therapy studies

Psilocybin therapy studies raise unique privacy and stigma concerns. One pilot used privacy-preserving analytics for psilocybin therapy studies—combining federated learning and de-identified outcome sharing—to analyze mood and cognition changes across sites. Participants reported median reductions in standardized depression scores of 12 points at 8 weeks, with no increase in serious adverse events. The privacy safeguards made many seniors more comfortable enrolling, knowing their sensitive data remained protected.

What to expect during a clinical trial

Entering a trial usually begins with screening and informed consent, followed by baseline assessments and scheduled follow-ups. You can expect regular check-ins, data collection (sometimes via remote devices), safety monitoring, and clear communication about withdrawal rights. Modern platforms make it easier to find matching trials and connect with study teams; platforms like ClinConnect are making it easier for patients to find trials that match their specific needs.

• Screening and consent
• Baseline assessments and randomization
• Scheduled visits or remote monitoring
• Safety checks and outcome measurements

FAQ

Are trials safe for seniors? Many trials include age-specific safety monitoring and adapt protocols for mobility or comorbidities; oversight by ethics boards and data safety committees adds layers of protection. How long will participation take? Duration varies: some interventions need weeks of follow-up, others months. Your study team will give a schedule so you can plan travel and medication timing. Will my data be private? Modern studies increasingly use privacy-preserving methods—de-identification, federated analytics, and secure pipelines—so your personal records often stay at your care site while aggregated results inform science.

Closing thought

Stories like Marie's show that technology and compassion together can open research to older adults without sacrificing privacy or rigor; the outcome metrics matter, but so does the experience of feeling seen and safe while contributing to science.