Recruitment, not science, is what most often stalls a trial, and recruitment is a data access problem. Standards-based connectivity between EHRs and research operations, using FHIR queries, consent-aware workflows, and reliable patient matching, lets sites pre-screen against real clinical data instead of manual chart review, which is where the largest time savings in study startup are available.
Recruitment is a data access problem
Published analyses of trial performance keep landing in the same place: enrollment, not efficacy, is the most common reason studies fail or terminate. A 2020 review in Perspectives in Clinical Research reported that 55% of terminated trials ended because of low accrual, that average enrollment efficiency is under 40% for Phase III and IV studies, and that more than 80% of trials globally fail to enroll on time.
The same review noted that more than 40% of trials amend the protocol before the first subject visit, which is often a signal that eligibility criteria were written without visibility into how the target population actually appears in clinical data.
What standards-based connectivity changes
When research operations can query structured clinical data through FHIR rather than waiting on extracts or manual review, three things change: feasibility assessment becomes evidence-based, pre-screening can run continuously instead of in bursts, and site burden drops because coordinators review a filtered list rather than a chart pile.
- Feasibility: test eligibility criteria against real population counts before the protocol is locked.
- Pre-screening: automate the mechanical portion of eligibility, leaving clinical judgment to coordinators.
- Consent: capture and honor consent state as data, with an auditable trail.
- Matching: resolve identity across EHR, registry, and study systems so candidates are not duplicated or missed.
- Site enablement: give each site a repeatable technical playbook instead of a bespoke build.
Governance is the gating factor
Research access to clinical data carries obligations that operational integration does not: IRB oversight, minimum necessary use, de-identification where appropriate, participant consent scope, and clear separation between care and research use. Building these rules into the data flow, rather than layering them on as manual review, is what makes a connected recruitment workflow sustainable across studies.
A practical first step
Pick one study and one site, define the eligibility criteria that can be evaluated from structured data, connect that narrow query path end to end with consent handling and audit in place, and measure the coordinator time it displaces. That single proven path is a far better basis for a research connectivity program than a platform selection made before any data has moved.
How BlockInterop supports this work
- FHIR and API Implementation consulting and implementation — Design and implement FHIR-based APIs, SMART on FHIR applications, US Core-aligned workflows, and scalable integration services.
- Clinical Trial Interoperability consulting and implementation — Connect clinical research workflows with EHR and healthcare data to improve trial matching, recruitment, consent, and study operations.
Sources
Every figure cited in this article links to its public source. BlockInterop publishes no client names, outcomes, or internal performance statistics.