1) Why post-market studies quietly fail
Post-market and long-term clinical studies rarely collapse in a single moment. They erode. Compliance drift starts as small misses and becomes normalized data loss over time — especially when follow-up spans years.
Typical early signals (months 6–9)
- Missed diaries or questionnaires
- Uncharged devices and sync dropouts
- Incomplete wearable streams
- Sites overwhelmed by follow-up
- Patients disengaging without escalation
What it becomes (year 2+)
- Data gaps accepted as “expected”
- Protocol deviations accumulate
- Rework and extensions emerge
- “Good enough” replaces “complete”
- Signal quality degrades for endpoints
This is not a technology shortage. It’s an operational shortage: the absence of a compliance operating model that identifies drift early and closes the loop quickly.
2) Why sites can’t own long-term compliance alone
Sites are essential to trials — but they are not structurally designed to own continuous multi-year compliance. They’re optimized for visits and episodic touchpoints, not always-on adherence recovery across distributed data sources.
The structural mismatch
Long-term compliance requires consistent outreach, device support, escalation management, and follow-through. That is a different job than running visits and documentation. The result is predictable: drift becomes invisible until it’s expensive.
Follow-up is deprioritized when staffing is constrained.
Device and app issues compound without rapid support.
Alerts exist, but interventions are inconsistent.
This is not a criticism of sites. It’s a systems issue: compliance execution needs a dedicated owner and an escalation loop.
3) Why eCOA + wearables degrade after month 6
Technology collects data — until it doesn’t. Long-term studies create predictable friction: device fatigue, life events, support gaps, and slow drift that dashboards rarely fix by themselves.
The hidden assumption most stacks make
Many eCOA and wearable programs assume patients self-correct, sites intervene, and automation is enough. In practice, automation detects issues — but someone must recover adherence.
The root cause of data loss is rarely missing tools. It’s missing accountability. When ownership is fragmented, drift wins.
4) What automation can and cannot do
Automation is powerful when it’s part of an operating model — not the operating model itself.
Automation can
- Detect missed tasks and lagging adherence
- Flag device sync failures and battery risk
- Surface cohort-level drift patterns early
- Trigger alerts and escalation rules
Automation cannot
- Restore patient confidence after frustration
- Walk someone through setup and troubleshooting
- Recover adherence after silent disengagement
- Replace human follow-through and accountability
Compliance is not a software problem. It’s an execution problem — the kind solved by monitoring + intervention + follow-through.
5) How Delve Health owns compliance execution
Delve Health is built for the part of studies many vendors avoid: everything after enrollment. We combine execution-grade eCOA, wearables, real-time compliance monitoring, and human-led support to close gaps quickly.
Delve’s compliance operating model
Identify missed tasks, device failures, and drift early.
Focus on what threatens endpoint integrity first.
Human support to recover adherence quickly.
Confirm resolution and prevent recurrence.
Delve doesn’t just surface problems. We close them — so compliance drift is managed as an operational function, not a passive metric.
Related resources
Optional internal links to keep users on-site and strengthen topical authority.
6) What happens when no one owns compliance
When compliance is “shared,” it is effectively owned by no one. That’s when drift becomes standard operating behavior.
The predictable failure mode
- CROs escalate too late
- Sites burn out and deprioritize follow-up
- Patients disengage silently
- Sponsors absorb extensions and unusable data
Ownership changes outcomes. If long-term follow-up matters, compliance has to be operated like a core workstream — not a hope.
7) FAQ for sponsors, CROs, and clinical ops
Why do post-market and long-term studies lose compliance over time? +
Long-duration studies degrade because compliance ownership fragments across sponsors, CROs, sites, and tech vendors. Automation detects issues, but without a loop to intervene and recover adherence, data gaps compound and engagement declines.
Who should own compliance in a post-market study? +
Compliance needs a single accountable operating model with defined escalation paths. Sites are essential but rarely resourced for continuous multi-year engagement and device support. The best approach pairs real-time monitoring with human follow-through.
Why does eCOA alone often fail in long-term follow-up? +
eCOA captures tasks and can generate alerts, but it does not guarantee intervention. In long-term follow-up, adherence failures are driven by friction, device fatigue, competing priorities, and silent disengagement. Without a recovery loop, alerts pile up.
How can sponsors reduce wearable data loss in post-market studies? +
Reduce wearable data loss by pairing validated devices with proactive monitoring, early detection of sync/battery failures, and rapid support. The key is preventing drift rather than reacting after weeks of missing data.
What does Delve Health do differently for post-market compliance? +
Delve combines execution-grade eCOA, wearables, real-time compliance monitoring, and a human-led Concierge-as-a-Service model. That means issues are identified early and closed quickly — so compliance drift is actively managed after enrollment, not just reported.