Jessica Lin
Jul 12, 2018 · 4 min read

Building a Data-Driven Approach for Personalized Mental Healthcare

We’re excited to announce Work-Bench’s investment in Spring Health’s $6M raise alongside a top group of investors including Rethink Impact, BBG Ventures, and the Partnership Fund for New York City.

A core part of our investment strategy at Work-Bench is engaging deeply with corporate buyers in our NYC network — across our Corporate Roundtables, Executive Briefings, and more — to hear and learn directly about pain points and priorities in the enterprise.

One thing that continually stood out in the Future of Work Sessions we host with corporate executives across Johnson & Johnson, Morgan Stanley, Pfizer, Capital One, Conde Nast, and others is the war for talent, and how this translates into human capital strategies for companies to differentiate.

I was fortunate to meet April Koh, CEO of Spring Health, at a conference, where I learned about her and her team’s incredible vision to completely transform mental health, by applying machine learning to cutting-edge behavioral research.

When we come across those rare founders who have an extraordinary vision for how the world should be and who pair it with deep customer empathy and an ability to execute — we get excited.

Mental health conditions are the most expensive medical condition in the U.S. due to their high prevalence rates and high costs of care, with 1 in 5 Americans struggling with a mental health issue.¹

Yet despite its prevalence, treatment for mental health continues to feel like a black box approach: a slow, painful, trial-and-error experience of diagnosis and treatment on top of what may be already a painful condition, whether it is selecting an effective antidepressant medication or prescribing a medication regimen for those suffering from clinical depression.

What excites us about Spring Health is their application of machine learning paired with deep domain and clinical expertise in mental health, which led to the development of a highly technical and effective product that has taken over 3 years to commercialize. The platform is derived from the research and work of co-founder Adam Chekroud, Assistant Professor and PhD at Yale, whose research showed that algorithms can actually better predict a patient’s outcome than a human provider can. With papers published in The Lancet and JAMA, this leading behavioral health research serves as the bedrock of their impressive core IP and robust technical product.

Spring Health’s data-driven approach to mental healthcare is based on “precision medicine” — this idea of a highly personalized psychiatry tool. After receiving their personalized health reports, users have two treatment options: They can connect with one of Spring Health’s internal network providers, or they can seek outside care. If they choose to meet with a Spring Health provider, they do so virtually.

In so many ways, the time and market is now for Spring Health’s technology. Spring Health can apply the latest developments and advancements of machine learning to this massive and painful problem space of mental health, that 10+ years ago, would not have been possible.

And when you pair this with our enterprise buyer perspective from the Fortune 1000 and other high growth corporations, the time is now because a focus on benefits demonstrates a corporations’ long term investment in their employee base. And in the war for talent, this empathetic approach will enable traditional companies to compete with webscale giants like Google, Amazon, and Facebook.

Beyond “feel good” benefits for employees, critical to an enterprise buyer is that with better treatment, mental health costs will actually decrease for corporations. We have already seen impressive customer traction from leading enterprises such as Gap, Whole Foods, MongoDB and more.

Spring Health doesn’t just stop with their leading technology. They wrap the technology into a seamless end-to-end platform, to ensure that patients are actually getting better care. This means a personalized employee diagnostic and onboarding experience, high-touch wellness plans, all the way to a highly-vetted, best-in-class provider network. Their platform also cuts down the average wait time to see a mental health provider to less than 2 days (compared to the 21 day national average) and engages 1 out of every 3 employees consistently across all enterprise customers.

This makes Spring Health’s platform an incredibly valuable and evidence-based asset for the enterprise, where employees can benefit personally, and corporations save costs on health spend and boost employee retention.

It’s clear that machine learning and AI will become increasingly important for applications in healthcare, and we could not think of a more important mission and vision than mental health, with the potential to touch the lives of millions of people. We are excited for the opportunity work side by side alongside April, Adam, and Abhi as they completely transform how we deliver care for mental health patients.

See more coverage of the announcement in TechCrunch, VentureBeat, and AlleyWatch, and join us in welcoming Spring Health to our Work-Bench family.

Teams Spring Health <> Work-Bench



Work-Bench is an enterprise technology VC fund in NYC. We support early go-to-market enterprise startups with community, workspace, and corporate engagement.

Jessica Lin

Written by

co-founder & VC @Work_Bench | GED educator | rethinking work


Work-Bench is an enterprise technology VC fund in NYC. We support early go-to-market enterprise startups with community, workspace, and corporate engagement.

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