JMIR Publications

ABSTRACT

Background:

Identifying patients at risk of hereditary cancer based on their family health history is a highly nuanced task. Frequently, patients at risk are not referred for genetic counseling because providers lack time and training to collect and assess family health history. Consequently, patients at risk are not receiving the genetic counseling and testing they need to determine the preventive steps they should take to mitigate their risk.

Objective:

Enable patients to receive clinical practice guideline recommendations for their hereditary cancer risk based on their family health history with mobile friendly technology.

Methods:

We combined chatbots, web application programming interfaces, clinical practice guidelines, and ontologies into a web service oriented system that can automate family health history collection and assessment. We used Owlready2 and Protégé to develop a lightweight, patient-centric, clinical practice guideline domain ontology using hereditary cancer criteria from the American College of Medical Genetics and Genomics and the National Cancer Comprehensive Network.

Results:

The domain ontology has 758 classes, 20 object properties, 23 datatype properties, and 42 individuals and encompasses 44 cancers, 144 genes, and 113 clinical practice guideline criteria. So far, it has been used to assess over 5,000 family health history cases. We created 192 test cases to ensure concordance with clinical practice guidelines. The average test case completes in 4.5 seconds, the longest in 19.6 seconds, and the shortest in 2.9 seconds.

Conclusions:

By engaging the chatbot, patients can collect and assess their family health history prior to visiting with their provider. Earlier identification of patients at risk of hereditary cancer leads to earlier and more effective preventive actions for managing hereditary cancer risk.