A $280 billion healthcare problem ripe for technology innovation and predictive analytics

A $280 billion healthcare problem ripe for technology innovation and predictive analytics

A $280 billion healthcare problem ripe for technology innovation and predictive analytics

Mental health and substance abuse treatment are on track to be a $280 billion problem 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.

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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 Solutions; the other involves Quest Diagnostics and UC San Francisco (UCSF). Let's take a look at both of them.

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.

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To bring technology innovation to address the problem, SFBHN has partnered with ODH Solutions, 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.

 



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