Challenges in mental health
In the U.S., one in five adults experiences mental illness in a given year . At nearly $200 billion in lost earnings per year , the associated economic impact is undeniably significant, but almost 60% of those experiencing mental illness today are left untreated . The field of mental healthcare desperately needs to improve outcomes, and digitization has immense potential to transform it by connecting patients, providers, services and data in innovative ways.
Historically, patient-reported outcomes (PROs) on mental, physical and social health status were the primary inputs used to assess a patient’s risk for mental health issues and facilitate clinical decisions . The incomplete and biased nature of PROs often led to costly repercussions when diagnoses were missed or delayed. However, obtaining continuous data on patient health-related behavior was difficult and costly, involving proprietary hardware or labor-intensive monitoring .
Harnessing big data and machine learning to disrupt mental health delivery
Ginger.io’s business model is built on obtaining and analyzing data that is timely, objective, and much less costly to collect. The company monitors patient behavior through smartphones and provides timely, objective data to providers. Providers are empowered to intervene effectively, boosting preventative measures and lowering overall costs (e.g., before patients fill up ERs or run up medical bills). Therefore, the business model targeted hospitals and provider groups as customers, since they bore the “financial risk” of poor outcomes .
By amassing and analyzing large sets of “passive” mobile data, Ginger.io can detect if a patient with mental illness is acting symptomatic . The company uses machine learning to detect complex patterns of behavior across multiple dimensions and predict when a user may need help. For example, a sudden decrease in social interactions (e.g., reduced volume of calls or texts) or physical activity (e.g., less movement captured by motion sensors) could signify that a user with depression is experiencing problems. When the app detects unusual patterns, it promptly notifies both patient and provider to take action as needed .
Other key components of the operating model included:
- Establish credibility through scientific validation – In order to attract and sell the platform to top-tier providers; Ginger.io must deliver significantly improved outcomes . To that end, the company launched several trials and pilots with over 25 leading institutions and academic centers across the nation. .
- Build analytics pipeline to ensure data platform improvement – Ginger.io has already gathered and processed over 600 million hours of data from over half a million people with anxiety and depression . As behavioral patterns are very individualistic, Ginger.io’s algorithms allow some degree of customization to create better predictive models. With this capability built into machine learning algorithms, the company can make continuous improvements and learn from mistakes .
- Target higher-acuity, care-intensive conditions to demonstrate value – For example, Ginger.io enabled UC Davis to improve early intervention for youth with psychosis which has historically involved expensive patient assessment and monitoring . The company also partnered with McLean Hospital to reduce readmissions of hospital patients with schizophrenia .
In spring of 2016, Ginger.io announced a change to their business model . Instead of targeting providers and just offering the data platform as a tool to enable interventions, the company decided to go after employers and payers instead. Under this new model, employers and payers would purchase Ginger.io services as a corporate benefit for employees and members.
Ginger.io’s mission remained mostly unchanged: lower overall costs to employers and payers by improving members’ well-being through preventative and responsive measures. However, instead of operating as a “connector” between outside providers and patients, Ginger.io transformed into a licensed medical provider to directly deliver holistic mental healthcare to patients .
Consequently, this new business model meant substantial changes to the operating model:
- Build digital exercises and tools – Digitized exercises (based on cognitive behavioral therapy, mindfulness, etc.) provide patients with self-management tools . Ginger.io also built robust communication tools (e.g., video conferencing, secure messaging) to facilitate relationship-building between Ginger coaches and patients.
- Shift to a “high tech, high touch” approach – Ginger.io incorporated personal coaches into the core product offering, complementing existing data platform and in-app exercises . Coaches directly interact with patients, manage patient progress holistically, review patient data, and serve as an referrer for more specialized care (e.g., licensed therapists, psychiatrists) .
- Target lighter-acuity patients instead of clinical grade cases – Focus on anxiety and depression which are more prevalent and better suited for the new product.
How to include human care in a scalable manner?
Ginger.io’s business change raises some interesting questions. Why has the company evolved from a data platform to a licensed medical provider? Being a care provider requires more human capital (e.g., hiring coaches and licensed medical professions) which may not turn out to be a sustainable business model. It’s still too early to say if companies see value in Ginger.io’s service and how willing they are to pay for it.
Though this shift may seem less scalable and more difficult operationally, it may also be a reflection of limitations in technology. Perhaps technology alone is not enough to completely replace the human component in mental health care – at least not yet. While self-help interventions are poised for digitization and mass distribution, human connection remains a critical element in mental health treatment. Therefore, the real challenge (and arguably, the biggest opportunity) is finding the right balance between human services and technological complements to create and capture the most value.
Word count: 821
 Behavioral Health Trends in the United States: Results from the 2014 National Survey on Drug Use and Health, September 2015, http://www.samhsa.gov/data/sites/default/files/NSDUH-FRR1-2014/NSDUH-FRR1-2014.pdf).
 Insel, T.R (2008) Assessing the Economic costs of Serious Mental Illness. American Journal of Psychiatry. 165(6), 663-665.
 APA “By the Numbers,” 7-27-2015.
 Callaghan, “Disrupting Health Care with Ginger.io,” True Ventures Blog, November 28, 2012, https://trueventures.com/disrupting-health-care-with-ginger-io/
 “mHealth: Ginger.io & Personal Zen – New Approaches To Data,” MobileCloudEra, July 1, 2014, http://www.mobilecloudera.com/mhealth-ginger-io-personal-zen-new-approaches-to-data/
 Matheson, “Mental-health monitoring goes mobile,” MIT News Office, July 16, 2014, http://news.mit.edu/2014/mental-health-monitoring-goes-mobile-0716
 Huang, “Ginger.io Raises $1.7M for Mobile Health IT, Rides Wave of MIT Media Lab Startups Trying to Understand People,” Xconomy.com, October 18th, 2011, http://www.xconomy.com/boston/2011/10/18/ginger-io-raises-1-7m-for-mobile-health-it-rides-wave-of-mit-media-lab-startups-trying-to-understand-people/?single_page=true#
 Madan, “Your smartphone, your therapist?” World Economic Forum, January 21, 2016, https://www.weforum.org/agenda/2016/01/your-smartphone-your-therapist/
 Comstock, “Ginger.io is working with UCSF, Duke, Partners on diverse pilots,” MobiHealthNews, November 06, 2014, http://www.mobihealthnews.com/37976/ginger-io-is-working-with-ucsf-duke-partners-on-diverse-pilots
 Ginger.io Employer Information Page https://ginger.io/employers/details/
 Rao, “Tea leaves and ginger: What does success mean for a digital health startup?” Health Standards, June 16, 2016, http://healthstandards.com/blog/2016/06/16/digital-health-success/