# Trial matching inside the electronic record at the moment a treatment is chosen

Source: https://onco.cc/ideas/idea-tr1-ehr-point-of-care-trial-alert/  
OnCo record `idea-tr1-ehr-point-of-care-trial-alert` (Idea). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

When an oncologist opens the order screen to prescribe a new line of treatment, the record would show the trials this patient may fit, with the nearest open site and a one-click referral.

## Summary

Eligibility criteria are encoded in a structured, computable form (mCODE/FHIR profiles for stage, biomarkers, prior lines, performance status) and matched against the patient's record inside the EHR order-set workflow, not in a separate portal. Alerts fire only at decision points (new line of therapy, progression documented) to avoid fatigue. Several AI matching tools exist; the missing piece is embedding at the point of decision with a referral action.

## Fields

- Kind: Idea
- Last checked: 2026-09-08
- Hypothesis: Point-of-decision matching will double the proportion of eligible patients who are offered a trial in participating practices, measured by chart review, compared with practices using the same matching tool in a stand-alone portal.
- Rationale: Most patients are never told about a trial; the failure is at the moment of prescribing, when the physician's attention is on the standard option. Decision-support that appears at that moment changes prescribing behaviour in other fields (antibiotic stewardship, anticoagulation).
- Proposed test: Cluster-randomised trial across 20 community oncology practices sharing one EHR vendor: embedded alert versus portal-only, primary outcome trial offer rate documented in notes, secondary enrolment rate.
- Maturity: early-clinical
- Actor: engineering

## Sources

- mCODE (minimal Common Oncology Data Elements): https://mcodeinitiative.org/
- HL7 FHIR: https://hl7.org/fhir/

## Connected records

- collections: [ClinicalTrials.gov](https://onco.cc/collections/clinicaltrials-gov/)
- technologies: [AI trial matching & clinical decision support](https://onco.cc/technologies/ai-trial-matching/)
- companies: [Cancer Commons](https://onco.cc/companies/cancer-commons/), [Tempus AI](https://onco.cc/companies/tempus/)
- bottlenecks: [Data silos](https://onco.cc/bottlenecks/b-data-silos/), [Trials enrol too few, too slowly](https://onco.cc/bottlenecks/b-trial-enrolment/)
- roadmaps: [AI in oncology roadmap: pattern readers → foundation models → agents in the workflow](https://onco.cc/roadmaps/ai-oncology-roadmap/), [Trial modernisation roadmap: the randomised trial → platforms and adaptive designs → decentralised, pragmatic and always-on](https://onco.cc/roadmaps/trial-modernisation-roadmap/)

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