News & articles > How AI, ML, and NLU Can Reduce Provider Burnout in Behavioral Health

How AI, ML, and NLU Can Reduce Provider Burnout in Behavioral Health

Executive Report

Category:  Whitepapers
Category:  Whitepapers

The challenge of provider burnout is growing – but technology can help

In 2018, the American Psychological Association estimated that 21–61% of mental health practitioners were burning out. And when the APA conducted a follow-up study in 2020, the percentage of providers that screened positively for burnout symptoms had shot up to 78%. This is contributing to high vacancy rates that can range from 20%-40% or more. In addition to impacting access to care, burnout can impact quality of care for the people you serve.

High administrative burdens are a top driver of burnout. Did you know that the average provider spends 12-15 minutes documenting progress notes for every 45-60 minute session? That’s one session’s worth of time spent on ops for every four sessions delivered.

We can’t afford to keep burdening clinicians with this work. The good news is, there is technology that can help. Learn more in our latest white paper.

Download this paper to learn:

  • How advances in AI, machine learning (ML), and natural language understanding (NLU) help organizations to interpret, analyze, and document behavioral health conversations automatically
  • How to reduce the time providers spend on progress note documentation by over 30%
  • How to identify and track the use of 30+ evidence-based therapeutic approaches and techniques related to CBT, MI, DBT and ACT
  • How leadership teams can improve supervision and training through unprecedented visibility into staff activity, caseloads, performance, and population health

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