Digital tools and platforms are a natural fit for overcoming the top barriers to getting mental healthcare: accessibility, cost and social stigma, says Emily Thayer, a Senior Consultant within Cognizant Consulting’s Healthcare Practice.
Untreated mental health conditions have long been a top healthcare concern. In 2019, fewer than half of Americans with a diagnosed mental illness received treatment for that condition, according to the US National Institute of Mental Health.
Not only is untreated mental illness detrimental to patients’ health — it’s also a strain on national healthcare costs. In fact, mental health disorders cost the US economy an estimated $4.6 billion per year in unnecessary ER visits and $300 billion in lost workplace productivity, making mental health disorders among the most costly untreated conditions in the US.
The pandemic has only accelerated the need for care — according to a Kaiser Family Foundation study, over 40% of US adults reported symptoms of anxiety or depression in January 2021, compared with 11% in the first six months of 2019. Given the well-documented therapist shortages that have resulted, the concern of connecting patients with care has only grown more acute.
It’s no wonder, then, that interest and investment are growing in digitally oriented mental healthcare, from platforms that match therapists with patients, to chatbots, to online cognitive behavioral therapy tools. Although emerging digital solutions are nascent and will inevitably encounter friction, virtual remedies show great promise in lowering the barriers that both practitioners and patients face.
Consider how digital tools can address the top three factors that have historically kept patients from seeking mental health care: accessibility, cost and social stigma.
Improving accessibility to mental health treatment
As of May 2021, over 125 million Americans live in a behavioral or mental health professional shortage area. This gap will continue to widen as the pandemic exacerbates the therapist shortage.
To expand accessibility to behavioral health services, companies like Quartet and Talkspace are using telehealth platforms to connect patients and therapists. By leveraging clinical algorithms, these platforms identify available therapists based on the patient’s symptoms, state of residence (due to cross-state licensing restrictions), insurance carrier, preferred mode of communication (synchronous video or audio and asynchronous text messaging) and desired appointment cadence.
In other words, if you have a connected device, you can receive on-demand care for your behavioral health condition. Digital accessibility also addresses physician shortages and burnout on a national scale.
As these entities are still relatively new to the market, challenges and questions remain, such as the fundamental disconnect between virtual treatment and physician intervention in a clinical setting. As patient adoption grows, enough accurate data will be generated to prompt when physician intervention is necessary.
Additionally, these telehealth platforms are more geared toward mild cases, as these services do not replace the necessary stages of the care continuum that may be needed for more serious mental health conditions such as schizophrenia and bipolar disorder.
Lowering behavioral healthcare costs
An estimated 47% of US adults with an untreated behavioral or mental health illness do not seek treatment due to high costs.
Many entities in the private and public sectors are turning to virtual services to help patients better afford behavioral and mental health services. For instance, traditional in-person therapy ranges from $64 to $250 per hour, depending on patient insurance, whereas digital solutions can cost under $32 per hour.
Accordingly, many workplaces are incorporating digital solutions into their employee-sponsored health plans through health platforms like Ginger, which offers 24×7 access to behavioral health coaches via asynchronous texting for low-acuity conditions like anxiety and depression.
Recent moves by the federal government further bolster the effort to make behavioral healthcare affordable. In addition to the US Department of Health and Human Services announcing an additional $3 billion in funding to address pandemic-related behavioral and mental health issues, the Biden administration has signaled commitment to expanding access to telehealth services for underserved communities. Such efforts will need to be combined with further work in the private sector to ensure mental healthcare affordability through virtual means.
Overcoming negative social stigma
Perceived social stigma is an additional barrier for many people seeking mental health treatment. In a study of patients with schizophrenia, 86% of respondents reported concealing their illness due to fears of prejudice or discrimination.
To circumvent these challenges, some mental health providers have embraced artificial intelligence (AI) chatbots and online cognitive behavioral therapy (CBT) tools. Although chatting with a bot may seem counterintuitive to the “high-touch” nature of the healthcare industry, the anonymity of this approach can ease patient anxiety about opening up to another potentially judgmental human.
In a randomized control trial with a conversational agent that delivers CBT treatment, patients reported a 22% reduction in depression and anxiety within the first two weeks. This study shows promise for the effectiveness of chatbot-based therapy, particularly for younger generations, many of whom already share many intimate details of their lives on digital forums and hence have a higher level of acceptance of these tools. Older generations may view the adoption of this new behavioral care model with more incredulity and hesitancy.
A virtual future for behavioral healthcare
It is clear that the virtual care industry is poised for future growth, as there is a clear correlation between our understanding of behavioral healthcare challenges and the evolution of treatment modalities to bridge those gaps.
While digital services may not be a cure-all remedy for behavioral health, they certainly offer a promising long-term solution to one of the country’s most prominent and costly diseases.
To learn more, visit our Healthcare solutions section or contact us.
Emily Thayer is a Senior Consultant within Cognizant Consulting’s Healthcare Practice, who specializes in driving digital transformation. Emily has a proven track record in both the private and public sectors, most notably in health plan strategy and operations, business development and project management. Emily earned her bachelor’s degree in business management and psychology from the University of Nebraska-Lincoln and University of Oxford, and an MBA from Washington University in St. Louis. She can be reached at Emily.Thayer@cognizant.com
Source: Using Digital To Address The Mental Health ‘Silent Epidemic’
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- “Mental health informatics – Clinfowiki”.
- https://www.nimh.nih.gov/news/science-news/2017/different-approaches-to-understanding-and-classifying-mental-disorders.shtml
- https://sdqinfo.org
- “Dawba”.
- Aledavood, Talayeh; Triana Hoyos, Ana Maria; Alakörkkö, Tuomas; Kaski, Kimmo; Saramäki, Jari; Isometsä, Erkki; Darst, Richard K. (2017). “Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype”. JMIR Research Protocols. 6 (6): e110. doi:10.2196/resprot.6919. PMC 5483244. PMID 28600276.
- Kenny, Rachel; Dooley, Barbara; Fitzgerald, Amanda (2016). “Developing mental health mobile apps: Exploring adolescents’ perspectives” (PDF). Health Informatics Journal. 22 (2): 265–275. doi:10.1177/1460458214555041. hdl:10197/6275. PMID 25385165. S2CID 21044041.
- Ben-Zeev, Dror; Scherer, Emily A.; Wang, Rui; Xie, Haiyi; Campbell, Andrew T. (2015). “Next-Generation Psychiatric Assessment: Using Smartphone Sensors to Monitor Behavior and Mental Health”. Psychiatric Rehabilitation Journal. 38 (3): 218–226. doi:10.1037/prj0000130. PMC 4564327. PMID 25844912.
- LiKamWa, Robert; Liu, Yunxin; Lane, Nicholas D.; Zhong, Lin (2013). “MoodScope: building a mood sensor from smartphone usage patterns”. Proceeding of the 11th Annual International Conference on Mobile Systems, Applications, and Services – MobiSys ’13. doi:10.1145/2462456.2464449. S2CID 14419803.
- Luxton, David D.; McCann, Russell A.; Bush, Nigel E.; Mishkind, Matthew C.; Reger, Greg M. (2011). “mHealth for Mental Health: Integrating Smartphone Technology in Behavioral Healthcare” (PDF). Professional Psychology: Research and Practice. 42 (6): 505–512. doi:10.1037/a0024485. S2CID 33228597.
- Slack, Donovan (March 3, 2017). “Inaccurate VA wait times preclude thousands of vets from getting outside care, probe finds”. USA Today. WASHINGTON. Retrieved April 30, 2019.
- Kruse, Clemens Scott; Krowski, Nicole; Rodriguez, Blanca; Tran, Lan; Vela, Jackeline; Brooks, Matthew (2017). “Telehealth and patient satisfaction: a systematic review and narrative analysis”. BMJ Open. 7 (8): e016242. doi:10.1136/bmjopen-2017-016242. PMC 5629741. PMID 28775188.
- Kruse, Clemens Scott; Mileski, Michael; Moreno, Joshua (2017). “Mobile health solutions for the aging population: A systematic narrative analysis”. Journal of Telemedicine and Telecare. 23 (4): 439–451. doi:10.1177/1357633X16649790. PMID 27255207. S2CID 206705210.
- Hyatt, Jen (May 9, 2016). “How Big Data is Improving Mental Healthcare”. Youtube. Wired UK. Retrieved April 30, 2019.
- Lam, Megan (July 24, 2018). “How Your Digital Data Can Help Mental Health Research”. Youtube. TEDxWanChai. Retrieved April 30, 2019.
- Sims, Hannah; Sanghara, Harpreet; Hayes, Daniel; Wandiembe, Symon; Finch, Matthew; Jakobsen, Hanne; Tsakanikos, Elias; Okocha, Chike Ify; Kravariti, Eugenia (2012). “Text Message Reminders of Appointments: A Pilot Intervention at Four Community Mental Health Clinics in London”. Psychiatric Services. 63 (2): 161–168. doi:10.1176/appi.ps.201100211. PMID 22302334.
- Ardis Hanson and Bruce Lubotsky Levin. Mental Health Informatics. Oxford University Press USA, 2013, 288 pp, ISBN 9780195183023.
- Smith MF. Computer Systems in Healthcare: Management and Strategy. Kindle (2012) ISBN 978-1-301-36918-8.
- “Informatics Committee”.
- http://www.healthcareconferencesuk.co.uk/news/newsfiles/Netta_Hollings_61.pdf
- Rotheray, Sebastian; Racey, Daniel; Rodgers, Lauren; McGilloway, Sinead; Berry, Vashti; Ford, Tamsin (2014). “Innovations in Practice: Further evidence on the effectiveness of the strengths and difficulties added value score as an outcome measure for child and adolescent services” (PDF). Child and Adolescent Mental Health. 19 (4): 270–273. doi:10.1111/camh.12059. PMID 32878351.
- Stringaris, A.; Goodman, R. (2009). “Longitudinal outcome of youth oppositionality: Irritable, headstrong, and hurtful behaviors have distinctive predictions”. Journal of the American Academy of Child & Adolescent Psychiatry. 48 (4): 404–412. doi:10.1097/CHI.0b013e3181984f30. PMID 19318881.
- “Interview med Robert Goodman”.