JMIR Publications

ABSTRACT

Background:

In the United States, innovation is needed to address the increasing need for mental health care services and widening patient to provider ratio. Despite the benefits of digital mental health interventions (DMHIs), they have not been effective in addressing patients’ behavioral health challenges as stand alone treatments.

Objective:

The current study evaluates the implementation and effectiveness of Precision Behavioral Health (PBH), a digital-first behavioral health care model embedded within routine primary care that refers patients to an ecosystem of evidence-based DMHIs with strategically placed human support.

Methods:

Patient demographic information, triage visit outcomes, multidimensional patient-reported outcome measure, enrollment and engagement with the DMHIs were analyzed using data from the electronic health record and vendor-reported data files. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework was used to evaluate the implementation and clinical effectiveness outcomes of PBH.

Results:

PBH had 47.58% reach rate, defined as patients accepting the PBH referral from their behavioral health integrated clinician. PBH patients had high DMHI registration rates (79.62%), high activation rates (76.54%), and high retention rates at 15 days (57.69%) and 30 days (44.58%) compared to literature benchmarks. 74.01% of patients showed clinical improvement, 22.47% no clinical change, and 3.52% showed clinical deterioration in symptoms. PBH had high adoption rates, with behavioral health integrated clinicians referring on average 4.35 (SD=0.46) patients to PBH per month and 90-100% of clinicians consistently referring at least 1 patient to PBH each month. A third (32%) of patients were offered PBH as a treatment option during their triage visit.

Conclusions:

PBH as a care model with evidence-based DMHIs, human support for patients, and integrated within routine settings, offers a credible service to support patients with mild to moderate mental health challenges. This type of model has the potential to address real-life access to care problems faced by healthcare settings.