Precision mental health care may be the key to removing barriers and improving treatment outcomes.
Mental health support is expensive in the US, with individual sessions often costing well over $100. This already puts it well out of reach of many Americans but becomes especially problematic when considering the first treatment can fail 70% of the time. The global mental health crisis cannot be handled with the resources and efficiency challenges alone. Getting everyone the help they need will require innovative new technology that can stretch resources further.
Many components result in initial treatments having such a high rate of failure. With over 200 mental health diagnoses, it’s not always apparent during initial assessments what the patient might be dealing with and the best next steps. Medications can also be problematic, frequently requiring dosage adjustments and medication changes before finding the best treatment program for the individual patient. Furthermore, therapists can use hundreds of modalities to help their clients, but identifying the most beneficial modalities for the individual can take time.
Spring Health was founded in 2016 with the mission to reduce significantly trial and error in mental health support. Making mental health care more efficient right from the start will allow clinicians to treat more patients, make treatment more affordable, and encourage patients to seek treatment. Using machine learning, Spring Health can identify individual needs based on how patients with similar profiles respond to treatments and modalities.
Spring Health collects information on the patient to build a comprehensive profile. It looks at personal preferences, socio-demographic info, family history, symptoms, and more. Then, spring Health compares the information to hundreds of thousands of data points and develops a care plan based on what is most likely to help the patient right from the start. This can be medication, meditation, therapy or proven treatment options that are most likely to help.
Precision medicine in mental health care has more than 2X the success rate of traditional methods and a reduced recovery time. In addition, their innovation has led to a $2 billion valuation after a successful Series C round brought in an additional $190 million in funding.