Surveillance and Reporting of Suicidal Ideation Assessment in PTSD Specialty Care Clinical Notes using Natural Language Processing (NLP)

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

Health and Medical

Operational functions

Clinical and medical Derived by keyword rules; see methodology

Problem the AI is intended to solve

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.

Expected benefits

Enhance VA system monitoring of suicide risk screening in a population at increased risk for suicide

System outputs

Surveillance rates of absent treatment documentation for recommended suicide risk screening at the national, VISN, and facility levels

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