Clinician-Administered PTSD Scale for DSM-5 (CAPS-5) Clinician Training Simulator

Overview

Development stage

In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

Not reported

Withheld from public reporting

Not reported

Mission

Topic area

Other

Operational functions

Search and knowledge retrieval, Procurement and acquisition, Clinical and medical Derived by keyword rules; see methodology

Problem the AI is intended to solve

The level of effort required to train clinicians, researchers, and examiners to administer and score the Clinician-Administered PTSD Scale for DSM-5. The CAPS-5 Clinician Training Simulator comprises three online courses, available in TMS and TRAIN, that provide instruction in the administration and scoring of the CAPS-5. The courses use voice recognition, 3-D technology, and artificial intelligence to create an immersive learning experience. The courses are intended for clinicians, trainees, researchers, and examiners in VA and in the community. They use AI in the following ways: 1. In the three current CAPS-5 virtual patient courses, learners have the option to speak the prompts, with their spoken prompts transformed to text using speech recognition. 2. The learners’ prompts, whether spoken or typed, are programmatically compared to the required prompts in the CAPS-5. The system analyzes whether the prompts were delivered exactly (“verbatim”), with slight variations (“paraphrased”), or with unacceptable variations (“off-script”). 3. One of the courses analyzes learner prompts in order to trigger comments –corrections or praise -- from a virtual coach. 4. We’re currently revising one of the courses to take better advantage of sematic similarity to analyze learners' inputs. 5. In the future, we may deploy generative AI. Here’s how the vendor described it in their response to our solicitation: “This new design will also leverage a separate backend to handle AI multi-agency and retrieval augmented generation (RAG) to ensure large language models (LLMs) used will always operate as designed.” This will be a closed system that does not pull information from or input information to publicly-available platforms (e.g., GPT-4, Bard).

Expected benefits

Saving time and human resources that can be better deployed in patient care. Improving accuracy of diagnosis of PTSD in Veterans.

System outputs

Courses in TMS and TRAIN. AI assists learners in understanding how to accurately administer and score the CAPS-5. Courses are helpful in providing clinical care but are not required, nor is it a requirement for clinicians to use the CAPS-5 with their patients.

Technology

AI classification

Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.

System name(s)

Not reported

Custom-developed code

Not reported

Public source code

Not reported

Sourcing

How it was built

Not reported

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported