Behavioral health is a complicated and expensive issue in U.S healthcare today. It’s also a field that is underfunded and ripe for technology-led innovation.
Mental health and substance abuse treatment are on track to be a $280 billionproblem by 2020. This is the tip of the iceberg. If you include untreated individuals and people with developmental disabilities, age-related conditions and so on, the magnitude of the problem is much higher.
Behavioral health (BH) issues — which include substance abuse in addition to mental health conditions — correlate with increased mortality, unemployment and homelessness, among other things. In response to the growing seriousness of the issue, the Senate health committee has announced the Mental Health Reform Act of 2016.
However, BH is underfunded given the scale of the problem and is underequipped in terms of treatment infrastructure. The costs, relative to the size of the affected population, are disproportionately high: Consulting firm McKinsey estimates that this group represents 20% of the population but accounts for 35% of the total healthcare expenditure in the country today.
Using data to address risks and costs
As with accountable care models in population health management (PHM), the key to reining in BH costs is to understand population health risks and intervene with preventive care models that reduce costs while improving the quality of care.
A couple of partnership models provide examples of how technology innovators and care providers are collaborating to address the problem. One involves the South Florida Behavioral Health Network (SFBHN) and ODH Inc.; the other involves Quest Diagnostics and UC San Francisco (UCSF). Let’s take a look at both of them.
The South Florida Behavioral Health Network (SFBHN) and ODH Inc.
The BH sector is not well prepared to deal with taking on risk, says John Dow, CEO of SFBHN, a nonprofit that deals with the prevention and treatment of behavioral health disorders at the community level. To begin with, unlike in a medical field such as oncology, there are no registries with longitudinal data on BH patients. Additional complications include confidentiality and sensitivity to data that might hurt individuals if handled improperly (such as data on criminal history and incarceration). Aggregating the data can be a significant challenge that requires collaboration among stakeholders.
To bring technology innovation to address the problem, SFBHN has partnered with ODH Inc., an offshoot of Japanese pharma company Otsuka that has developed Mentrics, a PHM platform for behavioral health. The key aspect of the platform is a risk-scoring algorithm that identifies high-risk patients for targeted intervention by using predictive analytics on medical records, behavioral health data and data on the individual’s justice issues. The latter, a major element of the program, is an outcome of the White House Data Driven Justice (DDJ) initiative that focuses on reducing incarceration and recidivism within the population. SFBHN, which has accumulated five to six years of behavioral health data, works with local hospitals to combine this data with medical records to identify and target at-risk individuals. SFBHN is careful about the confidentiality of the data and takes extreme care to comply with the government’s CFR 42 regulations on the same.
Quest Diagnostics and UC San Francisco (UCSF)
A unique partnership between lab test leader Quest Diagnostics and the academic medical center at UCSF focuses on dementia, a $215 billion costthat is bigger than cancer and heart disease and is set to increase significantly due to the aging population.
Using a population health approach, Quest leverages its vast clinical database of over 20 billion lab test records for early detection of dementia using an integrated care pathway for diagnosis and treatment of dementia developed at UCSF that focuses on early detection and treatment. Using technology innovation, the dementia care protocol starts with a five-minute cognitive assessment test named CogniSense that is administered through an iPad application during a physician office visit. Quest’s Quanum platform, an integrated suite of healthcare information technology and predictive analytics tools, analyzes the data from the test along with other patient medical data to help primary care physicians identify patients with early onset of memory loss and dementia.
Quest estimates that early identification and treatment of reversible causes of dementia saves $50,000 to $70,000 in costs by delaying admissions to assisted living centers.
The rise of behavioral health startups
BH is a complex and expensive issue in U.S healthcare today. This is also a sector that is ripe and ready for technology-led innovation. And the startup ecosystem is rising to meet the challenge.
There are over 200 behavioral health startups today, many of them funded by venture capital. Many of these startups are attracting the attention of health insurance companies looking to rein in the costs of behavioral health in their member populations by buying innovation from the market. Some of the early providers of behavioral health solutions have already been acquired by larger insurance companies, while others have received venture capital from the investing arms of health plans.
However, as in the case of digital health, many of these solutions are not based on clinical evidence and are not FDA-approved, which limits their use in clinical settings.
The lack of federal funding for behavioral health may raise questions about the business viability for many of these startups. The shortage of trained mental health professionals, especially in rural areas, can be a barrier to scale as well. The recent announcement by the U.S. Department of Health and Human Services (HHS) that $44.5 million will be allocated to grow the pool of behavioral health professionals is very timely.
At the same time, behavioral health is one of those fields with a double bottom line — in other words, the intended benefits are financial and social. As support for funding for behavioral health programs gathers momentum through legislation, and as behavioral health solutions mature with data, predictive models that accurately identify early onset of dementia and other conditions can have a significant impact on reducing treatment costs. As John Dow of SFBHN says, everyone will then be able to reap the benefits, however you define them.
This blog was orginally published on CIOonline