Direct to Consumer Strategies

Ignite Sessions

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.

Learning Objectives:

Edward Wu

Chief Medical Officer

Dr. Edward Wu is the Chief Medical Officer of Spring, where he oversees clinical and telemedicine operations. In addition to managing a provider network of therapists and physicians, he works closely with companies and health systems to achieve better, safer, and more efficient behavioral health. As a practicing internist, he has seen first hand the importance of integrating behavioral health within primary care to achieve optimal outcomes. Dr. Wu holds a fellowship in medicine and public health from New York University and his MD from Northwestern University.


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DTC-10 - Machine-Learning in Tele-Behavioral Health: Improving Convenience and Treatment Fit

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