Most cancer patients who enroll in clinical trials learn of these opportunities from their providers or from study staff, but most hospitals do not run trials.
Existing patient-facing tools for clinical trial matching typically require a challenging amount of manual clinical data entry and / or manual review of trials.
Develop open data standards and open APIs that enable interoperable, scalable, and accessible clinical trial matching services
Drive awareness of and commitment to use these standards in the industry
Thereby improve clinical trial matching for patients and their care teams
A cancer patient identifies clinical trials for which she may be eligible. She uses tools that she can access directly, and she does not have to do manual transcription of clinical data. Rather, the patient facing matching tools leverage structured patient data from the electronic health record (EHR) and structured descriptions of clinical trial eligibility criteria to assess matches.
Patient wants to identify clinical trials for which she meets the eligibility criteria to enroll.
Required patient data exists in a structured computable format
Patient has access to use clinical trial matching tool
Patient views a list of clinical trials in which she may be eligible to enroll.
What if there are no matching clinical trials?
What do we accept to be true? May need to be validated by partners.
This use case addresses patients finding clinical trials. Providers use of the clinical trial matching tool on behalf of their patients is covered in a separate use case.
ACS CAN is involved in a workgroup that is analyzing which data elements are most impactful for capturing trial eligibility criteria. Candidate elements include:
Diagnosis (secondary subtype/histology)
Metastatic status and location
Biomarkers (options may vary by cancer type)
Immune function /viral infection status (Hepatitis, HIV)