GreatNorthCollective/greatnorth-us-federal-ai-inventory huggingface dataset:
US federal AI use case: Voluson Expert 22, Voluson Expert 20, Voluson Expert 18
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The systems are full-featured Track 3 ultrasound systems, primarily for general radiology use and specialized for OB/GYN with particular features for real-time 3D/4D acquisition. They consist of a mobile console with keyboard control panel; color LCD/TFT touch panel, color video display and optional image storage and printing devices. They provide high performance ultrasound imaging and analysis and have comprehensive networking and DICOM capability. They utilize a variety of linear, curved linear, matrix phased array transducers including mechanical and electronic scanning transducers, which provide highly accurate real-time three-dimensional imaging supporting all standard acquisition modes.
https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices The systems are all intended for diagnostic ultrasound imaging and fluid flow analysis.
Purpose and benefits: Accelerate ultrasound workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Volta AF-Xplorer
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: Biotronik Home Monitoring System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: Synthetic Data Generation:  Experimenting with OpenSource, Third Party and GenAI
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: CareLink Home Monitoring
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Address high frequency of false positive alerts in patients with implanted Medtronic electrocardiogram (EKG) loop recorders
Purpose and benefits: Minimize work related to the review of false positive alert transmissions.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: GE Portable Critical Care Suite 2.x
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Critical Care Suite is a software module that employs AI‐based image analysis algorithms to identify pre‐specified critical findings (pneumothorax) in frontal chest X‐ray images and flag the images in the PACS/workstation to enable prioritized review by the radiologist.
Purpose and benefits: Triage pneumothorax cases. It identifies pre‐specified critical findings (pneumothorax) in frontal chest X‐ray images and flags the images in the PACS/workstation to enable prioritized review by the radiologist.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Dragon Medical One
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Solution to decrease the provider administrative burdens of typing medical notes.
Purpose and benefits: Enhancing patient outcomes by increasing provider-patient time, decreasing provider burnout, increasing efficiency in documentation, and therefore improving patient access due to providers having more availability to see patients.
Topic area: Health and Medical
Development stage: Deployed
US federal AI use case: Stratification Tool for Opioid Risk Mitigation (STORM)
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Patients exposed to opioid drugs often have complex medical needs and are at risk of multiple negative outcomes, including overdose, suicide, development of addiction, and other behavioral health challenges. Numerous strategies have been developed to minimize risks and treat conditions that underly them, but coordination of care across patient treatment providers and conditions can be challenging and interventions to reduce risk can be time consuming.  Decision support to systems are needed to ensure recognition of a patient’s current conditions and consideration and tracking of recommended interventions. Risk estimation is needed to ensure that the most complex and at-risk patients receive adequate clinical attention in time-constrained health care environments.
Purpose and benefits: The effectiveness of the targeted prevention program was tested during a randomized staged roll-out of the targeted prevention program using a stepped wedge evaluation design. The targeted prevention program utilizes the STORM model to identify patients for interdisciplinary case review (i.e. by a team of clinicians which includes those with pain, behavioral health and recovery expertise). Inclusion in the mandate for team-based case review of patients, the predictive model estimated that "very high" risk of overdose or suicide events in the next year was associated with a significant 22% reduction in all-cause mortality within 4 months of inclusion (Strombotne et al., 2023). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060407/ 
Inclusion in the case review program was also found to reduce all-cause mortality and reduce likelihood of opioid analgesic discontinuation, in the subpopulation of patients on long-term opioid analgesics (Li et al., 2023).
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Aquilion ONE (TSX-306A/3) V10.12 with Spectral Imaging System, Vitrea Software Package, VSTP-001A
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: This device is indicated to acquire and display cross-sectional volumes of the whole body, including the head, with the capability to provide images of whole organs in a single rotation. Whole organs 
include, but are not limited to, brain, heart, pancreas, etc.
Purpose and benefits: Reduces image noise.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Deep-Learning approaches to develop candidate lists of terms for use in text searches
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The intended use is to increase the comprehensiveness of term lists to be used in text-matching approaches to identifying concepts of interest in free-text medical record notes. Text-matching approaches are an efficient method for identifying text of interest in medical notes.  The success of text-matching approaches depends on the quality of term lists used to search for a concept of interest.  While humans can generate word lists for text-matching approaches, the generated word lists are likely to be limited and biased by the vocabulary, language habits, population exposure, and local dialects of the human generating the list.  Deep learning methods can help to augment candidate term lists to help overcome some of these challenges.  Once generated these augmented candidate terms are reviewed by subject matter experts for appropriateness and accuracy of the suggested terms for the concept and use case of interest.
Purpose and benefits: Here we (1) query pre-trained large language models (e.g., ChatGPT or Llama) through a user interface that allows prompting (such as the OpenAI API or CodeLlama) and/or (2) query word and phrase “embedding” models (e.g., Word2Vec and Phrase2Vec) to expand candidate term lists for review by subject matter experts.  Our team has found both approaches effective for expediting the generation of more comprehensive term to concept mappings for use in text-matching algorithms that increase the accuracy of clinical concept extraction.   We expect this use of AI to improve initial brainstorming of terms related to a given concept, resulting in a more sensitive approach to finding information of interest in free-text clinical notes. Experience to date has found that this approach enriches term sets in ways that increase sensitivity for identification of text of interest in clinical TIU notes when used in our CLEVER natural language processing pipeline.
Topic area: Health and Medical
Development stage: Deployed
US federal AI use case: Vereos PET/CT
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The positron emission tomography (PET)/computed tomography (CT) system is used for the purpose of detecting, localizing, diagnosing, staging, re-staging, and follow-up for monitoring therapy response of various diseases in oncology, cardiology and neurology.
Purpose and benefits: Supports diagnosis and treatment planning.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Patient Care Services Integration Platform (PCSIP)
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: 1. Improve patient flow at VAMCs so that 20% more Veterans are provided care with existing staff and resources.
2. Enable use of FDA approved devices in FISMA compliant manner.
3. Optimize veteran journey from direct care to community care and back.
Purpose and benefits: 1. Improve patient flow at VAMCs so that 20% more Veterans are provided care with existing staff and resources.
2. Enable use of FDA approved devices in FISMA compliant manner so that staff can get the job done easily from VA provided workstations for authentication, authorization, access for read and write to multiple clinical systems 
3. Optimize veteran journey from direct care to community care and back.
Topic area: Health and Medical
Development stage: Pilot
Risk category: High-impact
US federal AI use case: REACH VET Suicide Risk Prediction and Recovery Engagement
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Suicide is a low frequency event, but clinical attention and intervention can reduce the risk of suicide and other adverse behavioral health outcomes. REACH VET offers a targeted suicide prevention approach to focus attention on Veterans with the greatest risk/need. This AI system is designed to support identification of Veterans at an elevated risk of suicide or other preventable adverse outcomes to support mitigation of risks, if indicated.
Purpose and benefits: The REACH VET 2.0 model is expected to identify a population of Veterans at elevated risk of suicide and other adverse outcomes for review by providers. Providers conduct outreach to identified Veterans when appropriate. This model and the targeted prevention in which it is used (i.e. the REACH VET clinical program), is used to augment VHA's extensive clinical suicide prevention program. While VHA conducts universal screenings for suicide risk by asking patients structured questions regarding suicidality, this screening process does not identify all Veterans at elevated risk. The REACH VET model is intended to supplement clinical screening and assessments and support identification of changes in risk. The REACH VET model supplements clinical practices by identifying Veterans at statistical risk of suicide, given similarities in their health care data with prior suicide decedents. After identification, reevaluation of care and outreach are completed to support risk mitigation. This targeted prevention program was nationally implemented in VHA in 2017 and there was an evaluation of the effects of the REACH VET program. This evaluation found that REACH VET implementation was associated with greater treatment engagement, new safety plan documentation, and fewer mental health admissions, emergency department visits, and documented suicide attempts. Full findings of this program evaluation are available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524305/.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Venue Fit
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Venue Fit is a general-purpose diagnostic ultrasound system intended for use by qualified and trained healthcare professionals to evaluate the body, by ultrasound imaging and fluid flow analysis. The Venue Fit is a compact, portable system with a small footprint. The system can be hand-carried using the integrated handle, placed on a horizontal surface (if kickstand is attached), attached to a mobile cart, or mounted on the wall. It has a high resolution color LCD monitor, with a simple, multi-touch user interface that makes the system intuitive. The system can be powered through an electrical wall outlet for long-term use or through an internal battery for a short time with full functionality and scanning. The Venue Fit utilizes a variety of linear, convex, and phased array transducers that provide high imaging capability, supporting all standard acquisition modes. Compatible biopsy kits can be used for needle-guidance procedures. The system is capable of displaying the patient's Electrocardiogram (ECG) trace, synchronized to the scanned image. This allows the user to view an image from a specific time of the ECG signal, used as an input for gating during scanning. The ECG signal can be input directly from the patient or as an output from an ECG monitoring device. ECG information is not intended for monitoring or diagnosis.
Purpose and benefits: Supports ultrasound procedures.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Velacur
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Velacur is a portable device intended to measure the stiffness and attenuation of the liver in a non-invasive way, via measurement of liver tissue shear modulus and ultrasound attenuation. This is done by measuring the wavelength or wave speed of mechanically created shear aves within the organ of the patient. Attenuation is measured directly via the loss in power of the ultrasound beam. The device is designed to be used at the point of care, in clinics and hospitals. The device is used by a medical professional, an employee of the clinic/hospital. The activation unit is placed under the patient, while lying supine on an exam bed. The activation unit vibrates at frequencies of 40, 50, and 60 Hz, causing shear waves within the liver of the patient. The ultrasound transducer is placed on the patient’s skin, over the intercostal space, and is used to take volumetric scans of the liver while shear waves are occurring. The device includes two algorithms designed to help users detect good quality shear waves and identify liver tissue. From the scan data, the device calculates tissue stiffness and attenuation. Minor hardware and software changes were made to the device. The organ guide (cleared in K223287) was also extended to add more optional overlays on top of the liver overlay to help with optimizing the scan and training users to obtain adequate images. The significant change is the addition of a new output measure for Velacur, an ultrasound derived fat fraction (VDFF).
Purpose and benefits: Support liver stiffness measurements.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: 2268 Next Generation (2268NextGen)
Agency: Department of Veterans Affairs - OSVA: Office of the Secretary
Development stage: Retired
US federal AI use case: Syngo Application Software
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Syngo Application Software is a medical software for real-time viewing, image manipulation, 3D-visualization, communication, and storage of medical images and data on exchange media. It is used for diagnostic image viewing and post-processing and for viewing and post-processing during interventional procedures.
Purpose and benefits: Accelerates radiology workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Coronary Artery Calcium Model
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: This is operationalization of a Coronary Artery Calcium (CAC) scoring computer vision model that can predict cardiovascular disease risk. This will help clinicians identify and prioritize patients at high risk for cardiac events to intervene. The input is CT chest images and the output will be calcium scores and calcium masks that physicians can review to verify high patient cardiovascular risk. This will help clinicians identify and prioritize patients at high risk for cardiac events to intervene. It will improve the quality of veteran healthcare.
Purpose and benefits: We expect this project to improve patient care outcomes by helping direct provider attention to patients that were identified as high-risk via findings.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Rapid AI
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Rapid is a software package that provides the visualization and study of changes in tissue using digital images captured by diagnostic imaging systems including CT (Computed Tomography) and MRI (Magnetic Image Resonance), as an aid to physician diagnosis. Rapid AI is designed to streamline medical image processing tasks that are time consuming and tiring in routine patient workups.
Purpose and benefits: Streamline medical image processing tasks that are time consuming and tiring in routine patient workups.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Spine Planning (2.0), Elements Spine Planning, Elements Planning Spine
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Spine Planning is intended for pre- and intraoperative planning of open and minimally invasive spinal procedures. It displays digital patient images (computed tomography (CT), Cone Beam CT, Magnetic resonance (MR), X-ray) and allows measurement and planning of spinal implants, such as screws and rods.
Purpose and benefits: Supports spine procedure planning.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Vocational Rehabilition Services (VRS) Employment Support
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: Reportability of Cancer Diagnosis Information
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Try to identify if a cancer diagnosis is present in the pathology reports and what diagnosis the patients have, including histology, site, and subsite.
Purpose and benefits: Improve patient outcomes, save cost, and increase efficiency: Information extracted by the system will be highlighted and shown within the original context for review by the coordinators, within health informatics tools currently in production. This will decrease the time for information gathering for coordinators and improve their efficiency. This information may also help identify Veterans with diagnoses of interest for review by the coordinator, allowing for additional resources to be activated to support the Veteran if they meet program criteria.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Post-Discharge 30-day Readmission or Death Prediction
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: Predict Patient Suicide
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Prevention of Veteran suicide is VHA’s top clinical priority. We use AI to identify patients with key risk factors for death by suicide. It is a tool that can help point clinicians to potentially critical information that they might not otherwise have been aware of.
Purpose and benefits: Improve ability to identify Veterans at high-risk for suicide and intervene to reduce the risk of suicide.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: RayStation 11B
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: RayStation is a software system for radiation therapy and medical oncology. It is a treatment planning system for planning, analysis and administration of radiation therapy and medical oncology treatment plans.
Purpose and benefits: Supports radiation treatment planning.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Identify access to genetic testing in Veterans with breast cancer.
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Try to identify which Veteran with breast cancer has or does not have access to germline genetic testing from unstructured medical notes.
Purpose and benefits: Providers are more aware of if a Veteran has access to germline genetic testing, this helps improve the quality of care VA delivers, since it is recommended to have germline genetic testing for everyone with breast cancer.
Topic area: Health and Medical
Development stage: Deployed
US federal AI use case: Clinical Pathways for Cancer Patients
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The VA National Oncology Program (NOP) has invested in creating clinical pathways that guide providers to provide high quality evidence-based standard of care treatments to Veterans with cancer. However, it is currently unclear how many or how often providers are ‘on pathway’ or are concordant with this recommendation. The work will focus on leveraging AI to assess the degree of adoption of various pathways. For example, 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. This will assess care quality across the VA in terms of genetic testing in Veterans with prostate cancer and provide the necessary information to engage in quality improvement efforts. The 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 the VA will be identified using electronic health information in the VA Corporate Data Warehouse and their latest relevant clinical notes will be retrieved.
Purpose and benefits: Increase efficiency: it will speed up providers' review of patients' treatment plans based on the National Oncology Program guideline, since patients' pathway information will be highlighted. This makes it easier for the providers to make better treatment decisions for the patient, therefore potentially improving patient outcomes.
Topic area: Health and Medical
Development stage: Pre-deployment
US federal AI use case: Automated Incident Analysis
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Problem addressed: The Enterprise Command Operations (ECO) Major Incident Management (MIM) team will develop an AI Agent to assist in Major Incident bridge calls. The agent will gather insights from the Major Incident bridge transcription, ServiceNow Incidents, and Observability telemetry to assist in isolating the cause of a Major Incident. The agent would reduce the Mean Time to Repair (MTTR) Major Incidents impacting Veteran care and/or benefits.
Purpose and benefits: This agent would result in improved availability of Veteran-impacting services providing patient care and benefits. It would also significantly improve efficiency as Major Incident bridge calls tie up many system administrators in bridge calls which can be redirected to areas of greater impact.
Topic area: IT
Development stage: Pre-deployment
US federal AI use case: Extract patients’ diagnosis information and map the diagnosis to oncotree
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Extract patient diagnosis from unstructured patient notes and map the diagnosis to oncotree, because these information typically is extracted manually and it takes a long time to be put into the database.
Purpose and benefits: This project could increase efficiency, save cost, and enhance patient outcomes. With real time diagnosis tracking, the national oncology program is able to better support the patient with cancer diagnosis and understand each veterans' individual needs. While AI extract the information from the unstructured notes, it speed up the review process, providers can save time to help more patients rather than taking a long time to review each notes.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Adobe Creative Cloud
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: QLAB Advanced Quantification Software
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Philips QLAB Advanced Quantification Software System (QLAB) is designed to view and quantify image data acquired on Philips ultrasound systems. QLAB is available either as a stand-alone product that can function on a standard PC, a dedicated workstation, and on-board Philips' ultrasound systems.
https://www.accessdata.fda.gov/cdrh_docs/pdf20/K200974.pdf
Purpose and benefits: Supports ultrasound workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Cancer Patients Symptom Burden
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Attempt to extract patients' symptom burden information from unstructured notes to increase the speed of providers identifying patients that may benefit from additional support for symptom management or mental health.
Purpose and benefits: Providers are able to identify patients that might benefit from additional support more quickly rather than reviewing entire notes as AI would highlight the parts that are relevant to the symptoms. This increases efficiency and saves cost as well. With providers more aware of patients' symptoms, they can spend less time and effort identifying patients that suffer from high symptom burdens. Providers would be more able to reach out and support the patients in need of support, therefore improving patient outcomes.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Preventice 	BodyGuardian Remote Monitoring System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The BodyGuardian System detects and monitors cardiac arrhythmias in ambulatory patients, when prescribed by a physician or other qualified healthcare professional.
Purpose and benefits: Early detection of arrhythmias.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: VEO Insights Engine
Agency: Department of Veterans Affairs - VEO: Veterans Experience Office
Development stage: Retired
US federal AI use case: EPIQ Series Diagnostic Ultrasound System; Affiniti Series Diagnostic Ultrasound System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The R-Trigger algorithm software feature on Philips EPIQ and Affiniti Ultrasound System is intended to support detection of R-wave peak (R-trigger) as an input to certain transthoracic echo (TTE) clinical applications, initially including AutoStrain LV, AutoEF, 2D Auto LV (collectively referred to as “AutoStrain”), and AutoMeasure applications. The R-trigger algorithm is expected to be implemented as workflow enhancement for transthoracic clinical applications on EPIQ and Affiniti Ultrasound Systems in the VM13 software release.
The Auto-Measure and AutoStrain features, cleared on Philips EPIQ and Affiniti systems (K211597, K190913 resp.) support users during B-mode (2D), CW-, PW- and TDI-Doppler measurements by automating some of the measurements needed to complete a routine transthoracic echo (TTE) exam for adult patients.
The current AutoMeasure and AutoStrain applications require input from physio signal (ECG), using electrodes, because the modules and their detectors work on single cardiac cycles, starting and ending with the End Diastole (ED), or more precisely, with delimiting R-trigger events as a good approximation. Determining the R-triggers is currently done on the EPIQ and Affiniti Ultrasound Systems by a dedicated physio board. To enable clinical users to be able to use AutoMeasure and AutoStrain application without the R-trigger (ECG based) input, R-trigger feature (non-ECG-based) has been developed.
Purpose and benefits: Accelerate ultrasound workflows: the R-trigger algorithm is expected to be implemented as workflow enhancement for transthoracic clinical applications on EPIQ and Affiniti Ultrasound Systems in the VM13 software release. The Auto-Measure and AutoStrain features, cleared on Philips EPIQ and Affiniti systems (K211597, K190913 resp.) support users during B-mode (2D), CW-, PW- and TDI-Doppler measurements by automating some of the measurements needed to complete a routine transthoracic echo (TTE) exam for adult patients.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Billing Claims Prediction
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The AI solution is designed to help the VHA Office of Finance, Revenue Operations in several ways:

Identify missed revenue opportunities, ensuring no income potential is lost.
Highlight, predict and analyze trends in actionable denials, helping to resolve systemic issues.
Reduce the administrative burden on staff by simplifying processes.
Develop a national denial management analytics platform for consistent and effective financial operations across the VA healthcare network.
Purpose and benefits: Increased revenue, decrease in denials, and increase efficiency and staff satisfaction.
Topic area: Other
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Glassbeam Clinsights
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The system medical device data and then uses AI to predict medical device failure. So it uses wear and tear data to determine if the components are failing to prevent patient harm.
Purpose and benefits: It expects to detect medical device component wear and reports it to HTM to give the tech the knowledge that a part is failing so that it can be replaced before it wears out or breaks.
Topic area: Health and Medical
Development stage: Pre-deployment
US federal AI use case: VX Insights Hub Agent
Agency: Department of Veterans Affairs - VEO: Veterans Experience Office
Development stage: Retired
US federal AI use case: Persyst 14 EEG Review and Analysis Software
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Automatic electroencephalogram (EEG) measurement and seizure detection: Persyst 14 EEG Review and Analysis Software is intended for the review, monitoring and analysis of EEG recordings made by EEG devices using scalp electrodes and to aid neurologists in the assessment of EEG.
Purpose and benefits: Provides EEG measurements and detects seizures.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: OPTIS Mobile Next Imaging System, OPTIS Integrated Next Imaging System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: With the Ultreon 1.0 software application, these systems perform Optical Coherence 
Tomography (OCT) imaging of coronary arteries using compatible Dragonfly imaging catheters. Resting Full-cycle Ratio (RFR), Fractional Flow Reserve (FFR), and Pd/Pa at rest physiological waveforms are also measured by the system to assess the severity of a coronary lesion by measuring the pressure drop across the lesion (distal vs proximal pressure). The physician may use the resting full-cycle ratio (RFR) or fractional flow reserve (FFR) parameter, along with the knowledge of patient history, medical expertise, and clinical judgment to determine if therapeutic intervention is indicated.
Purpose and benefits: Support coronary artery scans.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Automated Decision Support
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: Identify medical evidence for claims processing. Automated Decision Support (ADS) is the utilization of technology to maximize operational efficiency by reducing administrative tasks to produce desired outcomes. These tools will improve the efficiency of the existing claims process, reduce future claims backlog, and will result in faster, more accurate and consistent decisions for Veterans and beneficiaries. ADS is not intended to replace trained claims processors – it provides tools to assist with development tasks at a time when VBA is receiving more claims than ever before.
Purpose and benefits: Automated Decision Support (ADS) automates some of the up-front time-consuming development activities of retrieving information and identifying potentially relevant VA Schedule of Rating Disabilities (VASRD)-related evidence of record. It accelerates the ordering of exams and assists in marking claims as Ready for Decision (RFD). This can lead to faster and more consistent decisions for Veterans and unlock VBA’s ability to uncover data trends.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Compliance Made Easy
Agency: Department of Veterans Affairs - Office of the Executive Secretary
Problem addressed: AI is being added to a new version of Compliance Made Easy (CME) in development to assist with grammar and tone checks along with tracking Style Guide updates. This is intended to improve compliance with VA Style Guide and reduce staffing time for correspondence.
Purpose and benefits: Increased efficiency in developing and processing correspondence.
Topic area: Admin Functions
Development stage: Pre-deployment
US federal AI use case: O-arm O2 Imaging System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The O-arm O2 Imaging System is a mobile X-ray system designed for 2D and 3D imaging for adult and pediatric patients weighing 60lbs or greater and have an abdominal thickness greater than 16cm. It is intended to be used to benefit physicians with 2D and 3D information of anatomic structures and objects with high X-ray attenuation, such as bony anatomy and metallic objects.
Purpose and benefits: Supports X-ray workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Mail Automation Services
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: Mail Automation Services (MAS) is an if-this-then that (ITTT) logic-based service which is utilized to process inbound mail across the VBA enterprise, including the receipt of claims materials from Veterans, Veteran Service Organizations, and other stakeholders. The platform ingests and reviews approximately 40k packets of information per day, primarily derived from the Centralized Mail Portal. It utilizes prescribed machine learning and Natural Language Processing (NLP), Intelligent Form Recognition (IFR), Optical Character Recognition (OCR), and Intelligent Character Recognition (ICR) to extract and process data from an average of 95 fields on over 1,500 form layouts within VA’s purview.
Purpose and benefits: MAS has completed over 2 million actions in the 2024 calendar year to date. It completes initial intake processing actions to support workload and claims management and has led to cost savings and increased efficiency - cost savings and increased efficiency data is available upon request.
Topic area: Benefits Processing
Development stage: Deployed
Risk category: High-impact
US federal AI use case: NeuroQuant
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: NeuroQuant is a medical device with a fully automated Magnetic resonance (MR) imaging post-processing software that provides automatic labeling, visualization, and volumetric quantification of brain structures and lesions from a set of MR images and returns segmented images and morphometric reports.
Purpose and benefits: Accelerate magnetic resonance imaging (MRI) workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Master Claims Assistance Tool (M-CAT)
Agency: Department of Veterans Affairs - VBA: Veterans Benefits Administration
Problem addressed: M-CAT is designed to automatically classify, extract, and validate critical information from diverse regulatory and/or policy references. This includes the automation of complex data extraction tasks, which are traditionally time-consuming and prone to human error.  M-CAT provides quick access to regulatory and/or policy guidance and summarizes information within the prescribed Retrieval-Augmented Generation (RAG) model. These retrieval results are maintained for each user and aggregated to inform focused training support needs. The overall generated response includes contextual integration, interactive elements for source expansion, feedback mechanism, displays current trending topics as suggested queries, and provides prompted follow-up questions post query.
Purpose and benefits: M-CAT provides quick access to regulatory and/or policy guidance and summarizes information within the prescribed RAG model, guiding end-users to achieve a clearer understanding and clearer implementation of VA policy. Access to this information improves processing capabilities which immediately transition to more timely and accurate delivery of benefits.
Topic area: Benefits Processing
Development stage: Pilot
US federal AI use case: MAGNETOM Vida; MAGNETOM Lumina; MAGNETOM Aera; MAGNETOM Skyra; MAGNETOM Prisma; MAGNETOM Prisma fit
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross-sectional images, spectroscopic images and/or spectra, as well as displays the internal structure and/or function of the head, body, or extremities
Purpose and benefits: When interpreted by a trained physician, these images and/or spectra and the physical parameters derived from the images and/or spectra yield information that may assist in diagnosis.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: 3D Quorum
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Identifies clinically relevant regions of interest through overlapping slices (3mm) to ensure no loss of 3D data. Reduces the number of 3D images to be reviewed by the Radiologist by 2/3.
Purpose and benefits: Early breast cancer detection and enhances patient outcomes.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: TeraRecon iNtuition-Structural Heart Module
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The iNtuition-Structural Heart Module is an iNtuition (K121916) based optional feature that employs all standard features offered by iNtuition. These standard features include convenient image manipulation tools (like drawing of region of interests), manual and automatic segmentation of structures, image assessment and measurement tools (linear, diameter, perimeter, angle, area and volume) and tools that support report creation, transmission and storage of reports in digital form, and tracking of historical information about the studies analyzed by the software. iNtuition Vessel analysis and calcium scoring features are utilized to support automatic and manual centerline extraction and analysis and calcium quantification.
Purpose and benefits: Accelerate standard cardiology workflows.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Intelligent 2D
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: QVCAD System
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: QVCAD is designed to process and display a projection image, using the ABUS image stack on a customer supplied computer, and monitor it for review, with certain areas highlighted and/or marked for attention.
Purpose and benefits: Identify potentially suspicious findings in breast scans.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Actions for Application Vulnerabilities
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
US federal AI use case: Medical Imaging Auto-segmentation
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: FFRangio
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: FFRangio analysis is intended to support the functional evaluation of coronary artery disease. The results of this analysis are provided as a supportive aid for qualified clinicians in the evaluation and assessment of the physiology of coronary arteries.
Purpose and benefits: Support coronary artery analysis.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: ScienceLogic Artificial Intelligence Operations (AIOPS) Software Subscriptions with Maintenance and Professional Support Services.
Agency: Department of Veterans Affairs - OIT: Office of Information & Technology
Development stage: Retired
US federal AI use case: Quantra
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Quantra software is designed to estimate breast composition categories by analyzing the distribution and texture of parenchymal tissue patterns, which can be responsible for the masking effect during mammographic reading.
Purpose and benefits: Support mammographic image analysis.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: VSTOne – AI-Driven Patient Monitoring and Care Delivery
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Development stage: Retired
Risk category: High-impact
US federal AI use case: Surveillance and Reporting of Suicidal Ideation Assessment in PTSD Specialty Care Clinical Notes using Natural Language Processing (NLP)
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: In light of the known elevated suicide risk among individuals diagnosed and in treatment for mental health conditions, and the associated need for ongoing monitoring of suicidality in this population, we are proposing to surveil and monitor nationally both the conduct and quality of suicide ideation (SI) assessment during treatment in PTSD specialty care. Our methods entail the use of natural language processing (NLP) of progress note documentation of treatment being conducted in the PTSD Clinical Team (PCT) specialty care clinics, to identify SI mentions, to quantify consistency of documented SI assessments by providers, and to classify SI mentions with respect to their clinical quality. We will report SI assessment rates nationally with break downs by VISN and facility to support administrative monitoring. This use case will help to identify rates of failure of mental health providers to conduct or document ongoing suicide risk screening throughout the conduct of mental health treatment for PTSD.
Purpose and benefits: Enhance VA system monitoring of suicide risk screening in a population at increased risk for suicide
Topic area: Health and Medical
Development stage: Pre-deployment
US federal AI use case: FastStroke, CT Perfusion 4D
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: CT perfusion 4D is an image analysis software package, which allows the user to produce dynamic image data and generate information with regards to changes in image intensity over time. It supports the analysis of CT Perfusion images (in the head and body) after the intravenous injection of contrast and calculation of the various perfusion-related parameters (i.e. regional blood flow, regional blood volume, mean transit time and capillary permeability).
Purpose and benefits: This software will aid in the assessment of the extent and type of perfusion, blood volume, and capillary permeability changes, which may be related to stroke or tumor angiogenesis and the treatment thereof.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact
US federal AI use case: Koios
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: FDA Cleared. Used with Automated Breast Ultrasound (ABUS). Classifies breast ultrasound lesions and automates reporting for improved efficiency and streamlined workflows. Increased sensitivity and specificity with reduced variability.
Purpose and benefits: Reduces unnecessary treatments (existing BI-RADS 3's can be accurately and safely downgraded) and provides probability of malignancy aligned to BI-RADS categorization.
Topic area: Health and Medical
Development stage: Pre-deployment
Risk category: High-impact
US federal AI use case: Using AI to read PDFs and parse the information to SharePoint list
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: Deviation forms are submitted via email, the AI will grab the pre selected PDF information and parse the data into a SharePoint List. Due to the size of the files received the AI will save hours off the Analysts workload. The problem to be solved is parsing the Party administrators contractual deviations from the submitted PDF forms.
Purpose and benefits: Increased efficiency
Topic area: Admin Functions
Development stage: Pre-deployment
US federal AI use case: Discovery MI Gen2
Agency: Department of Veterans Affairs - VHA: Veterans Health Administration
Problem addressed: The Discovery MI Gen2 PET/CT system is intended for CT attenuation corrected, anatomically localized PET imaging of the distribution of positron-emitting radiopharmaceuticals. It is intended to image the whole body, head, heart, brain, lung, breast, bone, the gastrointestinal and lymphatic systems, and other organs. The system is also intended for stand-alone, diagnostic CT imaging.
Purpose and benefits: The introduction of the 30 cm configuration comes with several clinical benefits. Compared to other Discovery MI configurations, the higher AFOV coverage allows a patient to be scanned using fewer field of views and can result in scanning in shorter time. Additionally, sensitivity of the 30 cm system is higher compared to other configurations, like the Discovery MI 25 cm, which assists in dose reduction and better detectability of small lesions.
Topic area: Health and Medical
Development stage: Deployed
Risk category: High-impact