Discuss a pilot
Patient Screening
ARO screens patient records against your protocol criteria and gives coordinators a ready-to-review worklist, for biobank specimen collection and cancer clinical trial pre-screening.
Biobanks still screen patients for specimen collection almost entirely by hand, and trial pre-screening is often manual too. Coordinators read schedules, pathology reports and notes one patient at a time.
Coordinators spend much of their week looking for patients instead of consenting and collecting.
When a potential candidate is identified after surgery, the opportunity for planned prospective collection may already have passed.
Screening criteria, review notes, and decisions can sit across separate records, making the screening history difficult to reconcile.
Your team sets the protocol criteria, ARO screens the records, and coordinators review each patient with the supporting evidence before recording a decision. The whole screening workflow lives in one place.
One place for your screening workflow.
Criteria your team approves.
Worklists with the evidence attached.
A record of every screening decision.
Your team sets up and approves each study's inclusion and exclusion criteria before screening begins.
ARO checks patient records against those criteria and sorts them into potential matches, possible exclusions and cases that need a closer look, with the evidence attached.
Coordinators review each patient and the evidence, then confirm or rule them out. Every decision is recorded.
Each patient arrives with the protocol they may fit, the criteria behind it, and where the evidence came from. One patient in this example matches none of the protocols.
ARO is built for biobanks and cancer research teams. The same screening workflow also supports industry collections, clinics and retrospective studies.
Prospective collection depends on finding eligible patients ahead of surgery, while there is still time to consent and plan. ARO surfaces likely candidates from the schedule and the record, so coordinators can act in time.
Pre-screening for open cancer studies means reading many charts to find a few patients. ARO narrows the pool first and shows why each patient is on the list.
Industry collections. Screen records against study and collection requirements, then review candidates the same way.
Clinics. Community practices that collect specimens or join research can identify candidates from their own records.
Retrospective studies. Screen existing records to find cohorts and estimate feasibility before committing to a study or collection target.
ARO can run in an environment your institution controls, limits access by role, and records who reviewed each patient and what they decided.
No. ARO identifies likely matches and shows its evidence. A coordinator confirms or rules out every patient.
ARO can be self-hosted in your own environment and can run without sending patient data to outside services. Data flows are confirmed with your team during deployment planning.
ARO is not tied to one EHR vendor. Compatibility, available data, and integration requirements are assessed with your institution.
ARO is ready for pilots. It has been tested on synthetic data, and a benchmark study against independent human review is in development.
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