2_use_case_name: Implementation of a Severe COVID-19 Risk Prediction Tool
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: The project seeks to implement a Severe COVID-19 Risk Prediction Tool to effectively identify Veterans at higher risk of developing severe COVID-19 symptoms through a machine-learning model to address one of the key barriers to increased vaccination offerings identified, i.e., the lack of tools for assessing risk of severe disease progression and potential vaccination benefit. It is expected by facilitating the estimated risk for severe COVID-19 progression, as well as a patient's current vaccine eligibility, that these patients can be outreached to and offered the vaccine in a more timely manner to improve vaccination rates and ultimately health outcomes.
12_outputs: The model will output a relative risk score for currently hospitalized patients based on their COVID-19 progression severity risk, and will generate a task notification to clinical teams to notify them of patients within that cohort output who also currently meet eligibility for receiving the COVID vaccine based on CDC guidelines (i.e. no recent history of already receiving vaccine, or recent COVID-19 infection).
16_dev_stage: Acquisition and/or Development
17_impact_type: Both
18_date_initiated: 3/1/2024
19_date_acq_dev_began: 3/1/2024
22_dev_method: Developed with both contracting and in-house resources.
23_contract_piids: Contract Number: GS-35F-0086U Contract Order Number: 36C10B21F0353
24_hisp_support: Yes
25_hisp_name: Veterans Health Administration
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: VA data input variables for this model were adapted from prior work done at VA Boston through Office of Research / IRB work, and included: Time since infection prior to vaccination Use of glucocorticoids Lymphocyte levels Presence of various comorbidities including:  -Alzheimer's Disease -Anemia -Atrial fibrillation -Chronic Kidney Disease -Chronic obstructive pulmonary disease -Epilepsy -Heart failure -Liver disease -Mobility impairments -Pressure and chronic ulcers -Acute myocardial infarction -Hypertension -Lung Cancer -Schizophrenia Tobacco use Body Mass Index categorization  -Extreme Obesity -Obesity I / Obesity II -Overweight -Unknown -Underweight Vaccine type (manufacturer) Age group
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: Age, Sex/Gender, Other
35_question_type: Mobility impairment
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: Corporate Data Warehouse (VASI ID #1152)
42_dev_tools_wait: 6-12 months
43_infra_provisioned: No
45_compute_request: No
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: Limited documentation for review: Some information regarding the model’s performance on specific benchmarks are available or have been shared with specific stakeholders within the agency.