Direct to Consumer Strategies
DTC-10 - Machine-Learning in Tele-Behavioral Health: Improving Convenience and Treatment Fit
Monday, April 30
10:35 AM - 10:44 AM
Location: Innovation Zone, Booth 434
Overview: By leveraging machine learning technology, telemedicine can build upon its delivery advantages and enhance outcomes with personalized treatment options. Tele-Behavioral Health has been successful, but diagnosis and treatment can frequently involve trial-and-error.
This presentation will describe an approach that aims to improve outcomes and efficiencies through 1) better screening and triage; 2) more accurate, personalized treatments; and 3) improved tracking of patient progress. As a multi-state medical practice of mental health therapists, psychiatrists, and primary care physicians, Spring set out to integrate personalized, evidence-based treatment recommendations into its care standards. Impacts to screening and treatment patterns will be shared with the audience.
Beyond machine learning, the presenter will share other key processes that can be used to enhance access and outcomes in telemedicine:
1) Streamlined Screening and Care Collaboration: The presenter will discuss how digital screening/assessment can drive personalized reports and enhance care outcomes. Through better collaborative care and treatment fit, patient engagement can be driven higher. Additionally, depression treatment response rates (50-60%) will be shared which improve dramatically upon the status quo (approximately 35%).
2) Personalized, Patient-Focused Solutions: To provide measurement-based care, patients can monitor their progress via a patient portal and report outcomes. Providers can leverage these outcomes to drive more efficient care. As a result, patients are better engaged in their care.
By combining timely/convenient access to services (telemedicine) with personalizing treatment plans (machine-learning), practices can markedly improve the patient care experience.
- Upon completion, participant will be able to understand how machine learning can be applied to virtual care.
- Upon completion, participant will be able to understand how patients can benefit from utilizing personalized treatment recommendations to improve care.
- Upon completion, participant will be able to understand how health systems can scale their telemedicine efforts to improve the treatment outcomes.