The whole landscape, the whole journey.

We designed Spring Health to eliminate every barrier to mental health, so that your employees could feel better—faster.

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Screening

Using the most advanced personalized treatment selection tools in the world, we match individuals to the care that is most likely to work for them.

Your Personalized Plan Might Include:

  • Specific Medication if Appropriate

  • Psychotherapy Program

  • Exercise

We have seen Spring improve mental health awareness, address workplace stress management, and make better mental health very accessible.

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Matching

Mental illness is invisible and can go undetected. Our program enables early detection and uses clinically validated screening tools to identify a variety of conditions.

  • Depression

  • Attention Deficits

  • Eating Disorders

  • Post-Partum Depression

  • Anxiety

  • Bipolar Disorders

  • Alcohol Abuse

  • Suicide Risk

4.5min

on average to complete


33%

of employees complete the screening


100%

secure and confidential

Navigation

Technology is most powerful when paired with the human touch. Every member is paired with a Care Navigator, a mental health professional trained to answer any questions you might have — unlimited support available via text, email, phone, or video.

Access

Give your employees convenient and fast access to the best providers. Our national provider network is vetted through a six-stage vetting process. We use tools that help your members track their progress over time.

  • Visits within 1.7 days

  • Fully vetted providers

  • Bundled care visits available

  • Direct online scheduling with providers

  • Network includes therapists & psychiatrists

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“Spring Health has helped me immensely and if it wasn’t available through my company, I wouldn’t have sought help.”

-A.M.

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“The Spring Health Care Team helped me figure out that I needed care from both a therapist and my primary care physician. Thanks for the comprehensive guidance!”

-T. A.

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“Spring Health helped me in a way that I didn’t know I was missing and wouldn’t have sought out on my own. It’s a life-changer, and I feel so much happier.”

-B.L.

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“Spring offers easy Care Navigation and connection to mental health treatment. My employer has made a commitment to my well-being, and I really appreciate it.”

-J.J.

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“Spring Health's Care Team is understanding, kind, and helpful-- it's rare to feel that a customer service-like figure is also my healthcare champion.”

-M.K.

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“I have had mental health providers and info sheets sitting at home, but I wasn’t doing anything about it. When our company launched with Spring Health, and it was what I needed to move forward with getting better.”

-L.E.

Our Clients

The Science

We set ourselves apart with an unwavering commitment to evidence. Our research group has published over 24 peer-reviewed journal articles in the field of precision psychiatry.

JANUARY 2016

Can we predict whether a patient will respond to a specific medication, before they start treatment?

This is an original research article, and becoming a landmark study in the field of psychiatry. The goal was to develop a predictive algorithm that would tell us whether a depressed patient will respond to a specific antidepressant medication (Citalopram). We showed that it was statistically possible to predict -- before the patient started treatment -- just by using data from a brief online assessment. This was the first time in medicine that anyone had successfully developed a machine learning algorithm that worked on an independent clinical trial, which also outperformed psychiatrists.

Read original article.

JANUARY 2016

What is the relationship between physical exercise and mental health?

This is an original research article, and becoming a landmark study in the field of psychiatry. The goal was to develop a predictive algorithm that would tell us whether a depressed patient will respond to a specific antidepressant medication (Citalopram). We showed that it was statistically possible to predict -- before the patient started treatment -- just by using data from a brief online assessment. This was the first time in medicine that anyone had successfully developed a machine learning algorithm that worked on an independent clinical trial, which also outperformed psychiatrists.

Read original article.

April 2017

When do antidepressants work, and when do they not work?

This is an original research article, using multiple Randomized Controlled Trials involving over 7,000 patients and 10 different treatments, which focus on the effectiveness of antidepressants, and how we can better predict treatment outcomes. We show that there are different clusters of symptoms in depression and that antidepressants only help with some clusters, which allowed us to extend our medication matching abilities to a plurality of common antidepressants.

Read original article.

JANUARY 2016

Once a patient recovers from depression, how likely are they to relapse?

This is an original research article in which we use multiple clinical trials and thousands of patients data to better describe and understand the process of relapse once a patient has initially recovered from depression. We develop trajectory-based models and predict whether individuals are likely to follow a relapse trajectory, or stay in remission.

Read original article.

JANUARY 2016

Can we match patients with First Episode Psychosis to specific Antipsychotic medications, before they start treatment?

This is an original research article extending our machine learning treatment selection approach to another clinical disorder, first episode psychosis, which is treated with a type of medication called antipsychotics. We show that before a patient starts treatment, you can reliably predict outcomes after 1 month and 1 year, and more effectively allocate specific medications to improve the chance of recovery.

Read original article.

April 2017

How can we use Big Data to improve Psychiatry?

This is an editorial that our Chief Scientist was asked to write in JAMA Psychiatry about how we can use Big Data and Machine Learning to improve mental health.

Read original article.

DECEMBER 2017

Can we predict suicide risk, and why is it so hard to do so?

This editorial tackles the big question of whether we can predict suicidal behaviors in advance of an event, a big clinical goal in the field. It also offers perspective on why this is such a statistically challenging task, and why solutions will be hard to implement.

JANUARY 2016

What are the barriers that stop people from getting treatment, and can we anticipate these barriers?

This is an original research article where we use nationally representative data to understand the various barriers that people face when getting treatment for mental health conditions. We describe the percentage of people who will face each difficulty (e.g. can’t afford treatment, too busy, worried about stigma), and also show that we can use machine learning to predict which specific barriers a person will face. We can use this information to better understand where a patient is coming from, and offer them treatment options that they are more likely to accept.

Read original article.

DECEMBER 2017

Why is it so difficult to turn research into practice?

This is a Review article that explains the barriers that are currently stopping research from being translated into practice, specifically concerning Machine Learning research and its use in psychiatry.

Read original article.