2_use_case_name: Classify clinical pathway for cancer patients
3_agency: Department of Veterans Affairs
3_abr: VA
4_bureau: VHA: Veterans Health Administration
8_topic_area: Health & Medical
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: The VA National Oncology Program has invested in creating clinical pathways that guide providers to provide high quality evidence-based standard of care treatments to Veterans with cancer. However at this time, it is unclear how many or how often providers are ‘on pathway’ or are concordant with this recommendation. Work will focus on leveraging AI to assess degree of adoption of various pathways. For example:  To assess care quality across the VA in regards to genetic testing in Veterans with prostate cancer, and provide the needed information to engage in quality improvement efforts, the VA NOP proposes to develop, evaluate and implement an informatics workflow that is capable of extracting information regarding whether a Veteran with prostate cancer has been offered access to germline and somatic genetic testing. Work will follow the framework NOP developed to assess germline genetic testing in Veterans with breast cancer in response to the Advances in Mammography and Medical Options (MAMMO) for Veterans Act of 2022. Briefly, Veterans receiving care for prostate cancer in VA will be identified using electronic health information in the VA Corporate Data Warehouse, and their latest relevant clinical notes will be retrieved. Data from VistA CPRS prostate cancer pathway templates will provide a gold standard for developing and evaluating the feasibility of using an open-source generative large language model to determine whether a Veteran has been offered genetic testing according to clinical notes. Earlier work has been successful using zero-shot (or few-shot) prompt development. Model fine tuning can be considered should these approaches fail. Upon achieving acceptable accuracy, the model will then be implemented for near real time determination of access to genetic testing at scale, especially in sites where this information is not available. 
This work will allow assessment of quality of care as it relates to adherence to VA endorsed clinical pathways on genetic testing in Veterans with prostate cancer. It will also facilitate efforts for improving care delivered through identification of sites that can be supported through existing efforts such as the National Tele-oncology Office, or cancer care navigation and tracking initiatives.
We do not anticipate this AI to be either safety impacting or rights impacting. The output does not serve as a principal basis for a decision. Stakeholders are expected to review the output at the population level, increasing their awareness of how the system as a whole is attending to Veteran needs per program office policy. Any use of the system to address needs at the site level or Veteran level will involve human review and corroboration of the output veracity using source information obtained from the EHR. The system resides completely within approved VA IT boundaries that are fully compliant with FISMA and HIPAA rules with availability and reliability set by OI&T. The information that the algorithm uses for input and its output relates to documentation of patient, disease, and prior treatment features related to cancer diagnoses and therefore are unlikely to perpetuate inequalities related to protected characteristics. They are unrelated to educational benefits, housing grants, loans, risk assessment for insurance, job training programs, employment services, vocational rehabilitation, or hiring. It does not impact claims and benefits processing.
While the system is envisioned to increase the effectiveness and efficiency of stakeholders identifying information elements related the Veteran’s cancer diagnoses and treatment, these elements are not envisioned to be related to race, nor creating or promoting disparities. On the contrary, by improving identification of off pathway care, we believe the system will offer the opportunity for stakeholders to identify areas where Veterans, or systems in need more support, decreasing any existing inequities. It will not be used for diagnosing disease
12_outputs: Class for clinical pathway, i.e., which clinical pathway the cancer patient is on. This will be highlighted in the original context and output along with the original context for nurse coordinators to review.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither