Company: TALK
Filing Date: 2025-03-12
Form Type: 10-K
Source: 0000950170-25-038107
Chunk: 8

Company: Talkspace, Inc.
Filing Date: 2025-03-12
Form: 10-K
Item: Item 1
Chunk 8
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 Contents

The following table depicts the technology-enabled process flow that supports our platform: 

Matching algorithm: We utilize machine learning to create a custom match for each new member. Our matching algorithm combines information from both structured and unstructured sources to predict which therapists have the greatest chance of success with each patient. Our matching model concurrently gathers member and historical outcomes and screens the therapists’ population to match the patient’s characteristics, clinical needs and preferences. Our machine learning technology also enables us to track the frequency and quality of clinical interactions, allowing us to provide a better therapist match should the patient request a new clinician.

Robust data ecosystem: We have a closed-loop data ecosystem providing a multi-dimensional view of the individuals who seek treatment on our platform. This data provides a holistic picture of each user – diagnoses, treatment plans, medical history, personal history, and clinical outcomes. Our data contains 8 billion words sent by millions of users via more than 140 million anonymized messages. We have approximately 6.2 million completed psychological assessments. Our data contains information about members collected by therapists, including over 1.2 million diagnoses and 4.3 million progress and psychotherapy notes. Our data also contains information about therapists reported by members, including approximately 3 million therapist ratings. We believe the size and depth of our clinical data is vast relative to the industry and is a differentiating element of our digitally-native modality.

Empowering providers to deliver enhanced care: Our providers are equipped with tools that allow them to optimize time utilization and improve clinical efficacy. One of the leading challenges in behavioral healthcare is a patient’s premature termination of engagement with the provider and, thus, a core focus of our machine learning strategy is to drive member engagement and increase care continuity, helping members to continue treatment long enough to reap its benefits. In order to extend the lifetime duration of our member base, we provide our providers insights on their patients’ needs and behaviors and offer techniques and suggestions that we believe are likely to maximize their patients’ satisfaction and engagement. These insights, delivered through our fully-integrated data intelligence platform, help providers to deliver effective treatments to their patients, and raise members’ awareness when tracking their own clinical progress.

Performance tracking and feedback: Our “Intro and Expectations” system detects whether providers have followed best practices in the crucial introductory phase of the therapy relationship and reminds them to do so if they have not. Our “Crisis Risk system” monitors all incoming members’ messages for linguistic features associated with potential danger or self-harm and draws providers’ attention