7 Patient Recruitment Metrics That Show Where Trial Enrollment Is Leaking

Smit Shah
CTBM

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Tufts CSDD research on non-rare disease trials put the average screen failure rate at 36.3%, up from 34.7% in 2012. In rare disease trials, 81% of patients screened were not eligible (Applied Clinical Trials). An earlier Tufts CSDD study of 151 global trials found that, on average, 928 patients were screened, 622 enrolled and 516 completed, with one in six enrolled patients dropping out (Applied Clinical Trials).

Most studies track one recruitment number: patients randomised against target. By the time that number is behind, the cause happened weeks earlier, somewhere between the first referral and the screening visit. The seven metrics below show where patients are being lost, so the team can act before enrollment falls behind.

The recruitment funnel and where it leaks

Funnel stage

What is lost here

Metric that shows it

Outreach

Channels that bring interest but not eligible patients

Yield by referral source

Pre-screening

Ineligible people reaching the site

Pre-screen pass rate

First contact

Interested people who go cold

Time from referral to first contact

Screening

Patients failing specific criteria

Screen failure rate by criterion

Consent to randomisation

Eligible patients who don't start

Consent-to-randomisation rate

Treatment and follow-up

Patients who leave the study

Dropout rate

Whole funnel

Spend that doesn't produce patients

Cost per randomised patient by channel

1. Yield by referral source

Count how many randomised patients each source produces: site databases, physician referrals, advertising, social media, patient communities. Channels that generate many enquiries and few randomisations take up coordinator time without adding patients.

2. Pre-screen pass rate

The share of pre-screened people who go on to a screening visit. A low rate means pre-screening questions are missing a criterion that later rules people out. A very high rate followed by high screen failure means the same thing.

3. Time from referral to first contact

Interest fades quickly. Track how long it takes for a referral to receive a call or message from the site, and set a target. This metric is entirely in the study team's control.

4. Screen failure rate by criterion

An overall screen failure rate tells you there is a problem. Screen failures broken down by the criterion that caused them tell you which one. If one criterion accounts for most failures, either pre-screening should check it, or the protocol team should review it.

5. Consent-to-randomisation rate

Patients who consent but are never randomised point to problems between screening and the first treatment visit, such as long washout periods, scheduling or travel. These are often fixable with logistics support.

6. Dropout rate

With one in six enrolled patients leaving before completion in the Tufts data, retention is part of recruitment. Track dropout by site, visit and reason, and look at visit burden, travel and reimbursement for the visits where people leave.

7. Cost per randomised patient by channel

Spend divided by randomised patients, per channel, shows which campaigns are worth continuing. Cost per enquiry flatters channels that bring volume but not eligibility.

Recruitment tracking checklist

  • Record the source of every referral
  • Log pre-screen outcomes and the reason for each fail
  • Time-stamp referral and first contact
  • Capture the criterion behind every screen failure
  • Track consent, randomisation and dropout dates by site
  • Link recruitment spend to the channel it paid for
  • Review all seven metrics weekly during active enrolment

What this means by role

  • Clinical operations directors and associate directors: the funnel shows whether to add sites, change channels or review the protocol, before enrollment falls behind.
  • Clinical operations managers and CTMs: screen failure by criterion and contact time are the quickest levers to pull.
  • CRAs: dropout and consent-to-randomisation patterns by site are useful topics for monitoring visits.
  • CRCs and principal investigators: faster first contact and better pre-screening mean fewer wasted screening visits.
  • Site networks and SMOs: yield and cost by channel show where recruitment budgets work across studies.

How Cloudbyz approaches this

Cloudbyz Patient Recruitment is built natively on Salesforce for sponsors, CROs, site networks and sites. According to Cloudbyz product materials, it covers study websites, social media and email or SMS campaigns, a volunteer portal, pre-screening by web, SMS and chatbot, eligibility and study matching, phone screening with call tracking, appointment booking, travel and hospitality management, recruitment budget management, eConsent and eCheck-in, cohort segmentation, and recruitment metrics and dashboards. Because it shares a platform with Cloudbyz CTMS and EDC, a volunteer's progress from referral to randomisation can be tracked in one place. Which metrics are available depends on how campaigns and screening workflows are configured.

See the recruitment funnel in one place

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