2_use_case_name: Care Assessment Needs (CAN) Score
3_agency: Department of Veterans Affairs
3_abr: VA
4_bureau: VHA: Veterans Health Administration
8_topic_area: Health & Medical
10_commercial_ai: None of the above.
11_purpose_benefits: CAN is a set of risk-stratifying logistic regression models run on Veterans receiving health care through VHA.
12_outputs: 90-day hospitalization or 90-day death
16_dev_stage: Operation and Maintenance
17_impact_type: Both
18_date_initiated: 1/1/2011
19_date_acq_dev_began: 6/1/2011
20_date_implemented: 1/1/2012
22_dev_method: Developed in-house.
24_hisp_support: Yes
25_hisp_name: Veterans Health Administration
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: Yes
33_agency_data: Patient demographics, medical conditions, laboratory results, medications, health care utilization, social determinants of health, social history, vital signs.
34_data_docs: Documentation is complete: Documentation exists regarding the maintenance, composition, quality, and intended use of the training and evaluation data, as well as any statistical bias across model features and protected groups. 
35_demo_features: Race/Ethnicity, Sex/Gender, Age, Socioeconomic Status
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: No
42_dev_tools_wait: 6-12 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: Documentation has been published: Complete documentation has been published to a repository or data catalog within the agency and is made accessible to other data science teams for review and feedback.
51_extension_request: No – Agency did not request an extension for this use case.
52_impact_assessment: Yes
53_real_world_testing: Performance evaluation in operational environment: The AI use case has been tested in an operational environment before being fully implemented as a solution, or has been tested in simulated or controlled environment using operational or synthetic data.
54_key_risks: Drift. Monitoring routinely
55_independent_eval: TRUE
56_monitor_postdeploy: Automated and Regularly Scheduled Updates: Some aspects of the plan to monitor the AI system post-deployment are automated including re-training of models after detecting drift; however, data science teams are still significantly involved in the monitoring and re-deployment process.
57_autonomous_impact: No - Some individual decisions or actions require direct human oversight.
59_ai_notice: Online - in the terms or instructions for the service.
61_adverse_impact: No
62_disparity_mitigation: Included in pool of candidate variables and model tested for bias
63_stakeholder_consult: Direct user testing
65_appeal_process: No – it is not operationally practical to offer this.
66_no_appeal_reason: The model is for use by physicians as one additional clinical input. Ultimately the physician makes decisions after looking at all patient clinical information including demographics.  Physicians can offer feedback but the patient is not directly exposed to this model.
67_opt_out: Yes
67_question_type: Physicians can choose to use the model or not and their decision is always with human input.