Prompt
How do I set up a pre-screening workflow tool for site coordinators to capture referrals and route qualified patients?
Latest observation
A good pre-screening workflow tool for site coordinators should be simple to use at intake, enforce eligibility logic, and automatically route only qualified patients to the right study team.
Here’s a practical setup approach:
1) Define the workflow stages
Map the process from referral to handoff:
- Referral received
- Basic intake captured
- Pre-screen eligibility checked
- Qualified / not qualified decision
- Assignment or routing
- Follow-up / outcome tracking
This helps you design the tool around the actual work instead of a generic form.
2) Collect the minimum required intake fields
Keep the initial capture fast. Typical fields:
- Patient name or study ID
- Date of referral
- Referral source
- Contact info
- Site / location
- Study of interest
- Key inclusion criteria
- Key exclusion criteria
- Insurance / consent status if relevant
- Coordinator notes
- Status
If you can, separate:
- Required fields for intake
- Eligibility fields used for routing
3) Build eligibility logic
Create rule-based checks that determine whether a referral is potentially eligible.
Examples:
- Age within range
- Diagnosis matches
- Prior treatment history acceptable
- No exclusion flags
- Geography or visit availability fits
- Required labs or imaging available
Use conditional logic like:
- If all required inclusion criteria are met and no exclusion criteria are triggered → Qualified
- If missing data → Needs more info
- If clearly not eligible → Closed / not qualified
4) Add routing rules
Once qualified, the system should automatically route the patient to the correct team or queue.
Routing options:
- By study
- By site
- By therapeutic area
- By coordinator workload
- By urgency or target enrollment priority
Examples:
- Qualified for Study A → send to Study A coordinator
- Qualified but site at capacity → send to backup site or waitlist
- Needs physician review → route to investigator queue
5) Make it easy for coordinators to use
A coordinator-facing tool should have:
- A short intake form
- Dropdowns instead of free text where possible
- Autofill and templates
- Clear status labels
- Alerts for missing info
- One-click submission or disposition
If the workflow is too complex, adoption will drop.
6) Track status and audit trail
You’ll want visibility into every referral:
- Who entered it
- When it was reviewed
- What criteria were checked
- Why it was rejected or accepted
- Where it was routed
- Follow-up outcomes
This is useful for compliance, reporting, and process improvement.
7) Use notifications and task queues
Automate next steps:
- Notify coordinator when a new referral arrives
- Alert investigator when manual review is needed
- Remind staff about incomplete referrals
- Escalate stale items after X days
8) Protect sensitive data
Because this is patient-related, make sure the tool supports:
- Role-based access
- Audit logs
- Encryption
- Secure storage and transmission
- HIPAA-compliant workflows if applicable
9) Measure performance
Track metrics such as:
- Referral volume
- Qualification rate
- Time to review
- Time to route
- Drop-off reasons
- Enrollment conversion rate
These metrics help improve both recruitment and coordinator efficiency.
10) Choose the right platform
Depending on complexity, you can implement this using:
- A configurable CRM or CTMS
- A low-code workflow platform
- A custom web app
- An EHR-integrated referral tool
If you need rapid deployment, low-code is often the fastest path. If you need deep integration and custom eligibility logic, custom build may be better.
Suggested implementation structure
A simple architecture would be:
- Intake form for referrals
- Eligibility engine for rule checks
- Queue management for routing
- Dashboard for coordinators and managers
- Notifications for tasks and exceptions
- Reporting layer for metrics
Example workflow
- Site coordinator enters referral details.
- System checks eligibility rules.
- If qualified, the referral is routed to the assigned study queue.
- If incomplete, it is returned for missing data.
- If not eligible, it is marked closed with reason code.
- All actions are logged for reporting.
If you want, I can also help you design:
- a sample intake form
- a decision tree for eligibility
- a workflow diagram
- or a requirements list for a vendor/custom build.
Observation history
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How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, and Meta AI.