# Acuity - A Clinical Decision Support System for Applied Behavior Analysis

> **NIH NIH R44** · EXPERIAD, LLC · 2022 · $679,957

## Abstract

PROJECT SUMMARY / ABSTRACT
This proposal will result in a major new clinical decision support software system, Acuity, which will assist
Behavior Analysts (BAs) and Behavior Technicians (BTs) in the delivery of Applied Behavior Analysis (ABA),
which is the leading treatment for autism. This is a proposal to develop software and perform a functional
impact and implementation outcomes study on 34 BAs recruited from 12 autism therapy clinics who will use
Acuity as part of their daily practice. The new Acuity software will integrate with existing ABA software that
clinics are already using to collect data and view charts. Acuity will offer significant improvements in treatment
planning, progress tracking, trend monitoring, dosage management, and staff assessment. Research has
shown that first-generation systems do not do enough to support overworked BAs who are overwhelmed with
the data being collected. Acuity will address critical shortfalls by enabling more agile clinical decisions across
multiple aspects of treatment, providing practitioners with new levels of rigorous, real-time insight into their
clinical data. Acuity will employ machine-learning and statistical algorithms to facilitate more accurate and
accountable timeline management for ABA treatment plans, using estimations derived from analysis of past
performance metrics and target-level effort assessment that is calibrated for the current learner. Acuity will then
help the BA compare actual to expected progress as the child with autism works towards time-based
milestones. Acuity will proactively alert BAs whenever a target exhibits notable performance trends, or when a
behavior spikes above a threshold, or dosage falls below prescribed levels. Additionally, Acuity will help with
supervision by providing a dashboard for evaluation and comparison of staff members’ overall efficiency in
therapy delivery and their adherence to prescribed target dosage. In these ways, Acuity will help BAs provide a
more responsive and effective treatment. This research will determine the success of clinics’ ability to adopt
and use Acuity, and the extent to which Acuity impacts BAs and BTs by (1) making their timeline estimates
more accurate, (2) increasing the timeliness of corrective treatment actions, and (3) improving adherence to
prescribed dosage.

## Key facts

- **NIH application ID:** 10552494
- **Project number:** 1R44MH131510-01
- **Recipient organization:** EXPERIAD, LLC
- **Principal Investigator:** REX M JAKOBOVITS
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $679,957
- **Award type:** 1
- **Project period:** 2022-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10552494

## Citation

> US National Institutes of Health, RePORTER application 10552494, Acuity - A Clinical Decision Support System for Applied Behavior Analysis (1R44MH131510-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10552494. Licensed CC0.

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