The copilot application assists in extracting, processing, and normalizing patient information, including family history, individual risk factors, clinical guidelines, and data. It uses this data to answer questions like, “What screenings should the patient be doing?” to identify missing diagnostics and create a personalized screening plan. It also generates necessary documentation for completing diagnostic workups, such as medical necessity documents and insurance pre-authorizations.

A clinician reviews the output of the copilot application at each step and can make modifications if needed before presenting it to the patient. Once satisfied with the result, the clinician can add the information to the patient’s existing treatment plan.

Laraki wrote about the frustrating process of pre-treatment workups that patients and doctors often have to go through before initiating treatment. Different tests may be required based on the type of cancer, patient history, and other specific factors to inform the treatment recommendations.

Color has already initiated the use of the copilot tool for its clinicians in a limited capacity, resulting in the identification of 4 times more missing labs, imaging, or biopsy and pathology results compared to those without the copilot. Additionally, clinicians can now analyze patient records and identify gaps in just 5 minutes, rather than the weeks it would normally take.

The primary goal is to detect cancers at an early stage. More than a third of Color’s patients need earlier and different screening approaches based on individual risk factors not covered by standard guidelines. Even a four-week delay in treatment can lead to a 6–13% higher risk of mortality,according to a study.


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