RxDataScience Blog


Mental Health and Big Data: A Step in the Right Direction

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Kate Spade – depression and anxiety

Robin Williams – severe depression

Pete Davidson – Borderline Personality Disorder

Demi Lovato – Bipolar disorder

Two gone, two battling a lifelong battle, like many Americans. With the stigma and bias surrounding the topic, the mental health community struggles to move forward. The research and treatment is at least a decade behind common chronic conditions, mainly because no one wants to talk about mental health due to the complexity and lack of understanding. 

Approximately one in five adults in the U.S. – 43.8 million – experience mental illness in any given year. One in 25 adults in the U.S. – 9.8 million –  experience a serious mental illness that interferes or limits their ability to function in activities in their daily life. As for the youth, one in five, ages 13-18, experience a severe mental disorder at some point in their lifetime. 

“Mental illness is nothing to be ashamed of, but stigma and bias shame us all,” Bill Clinton said in 1999 on his June 5 radio address when he discussed the future of mental health policy. 

Whether we know it or not, mental health plagues the American culture, but it is not often talked about freely. Because of various societal norms, most of these individuals suffer in silence or cannot find the treatment that suits their case. Patients get lost in the system, misdiagnosed, or the treatment is ill timed for the wrong patient.  

While these illnesses have taken over the U.S., most individuals still lack access to care in the 21st century. 56 percent of American adults with a mental illness do not receive treatment while one in five adults report an unmet need. 

Mental illnesses are difficult on all fronts, from understanding and communicating to even categorizing the symptoms. Patients suffer in silence, waiting months to receive a diagnosis and plan of action. Different medications are prescribed, utilizing a trial system just to find the perfect treatment for the patient. Often, there are several misses before a correct treatment or patients walk away from the treatment, assuming they can handle it on their own.

The mental health community faces some unique challenges: lack of a central organization, inconsistent quality of information, and in some cases, denial of illness. As the medical profession has struggled for decades to think of effective ways to help their patients, data analytic companies have shown different ways that big data can be utilized for mental health treatment. 

“We must mobilize our innovative minds to work alongside data scientists to create solutions to address one of mental health care’s biggest issues — delivering good, evidence-based care to the masses who would benefit most,” Kari Stephens, Ph.D, said in an article for Psychiatric News on May 1, 2017. “Mental health care is best understood not just through individual patient data, but through a comprehensive lens of health care delivery.”

By integrating and analyzing large sets of data, the scientists and doctors can identify patterns within the data that otherwise would’ve been harder to detect. Machine learning can then be used to identify biological causes, different symptoms, and medical causes and connect them to form a more accurate diagnosis and treatment plan. 

While it seems simple when it’s put plainly, there are difficult challenges that data scientists must overcome to achieve the end goal. One of the challenges is linking and combining multiple data sources together that range from genetic information , doctors’ notes, and MRI scans to pharmacy sales, test results, and information gathered from health apps and monitoring tools. Another is lack of data sharing.

“It is the lack of data sharing due to the commercial interests of the data providers and health systems that are the biggest obstacle,” Larry Pickett, CEO and co-founder of RxDataScience, said. “There is a serious lack of leadership and collaboration in the mental health community as a whole. Organizations need to look outside their commercial self-interests and develop collaborative models that benefit patients.”

Through private-public collaboration and data sharing, data analytic companies can work alongside the medical community to find a more effective way to reach and help the mental health community.

“Today, data is poorly utilized due to being fragmented across the healthcare industry and reliance on manual and older analytical methods,” Pickett said. “It is used to test and get FDA approval for new chemical entities and product extensions via clinical trials. You have individual psychiatrists and health systems with limited access to data making decisions based on small populations.” 

By combining clinical trials from multiple pharmaceutical companies, real world data providers, health system electronic records, and patient survey data, the ideal analytical program can be formed in a physician/psychiatrist friendly manner. It will be readily available for data exploration and visualization; however, the program will be missing the ability to add notes and insights based on clinical observations. By taking the notes from each session and the data acquired over the years, a more exact treatment plan can be chosen for the given patient.

“The data would be combined and access via data exploration and visualization tools,” Pickett said. “It would also support more modern advanced analytics such as artificial intelligence and machine learning techniques such as deep learning, without needing data science expertise to access and analyze.”

Currently, clinical trial and real world data from medical and pharmacy claim data are scalable and available; however, symptoms data form electronic health records is the missing key component.

“The combination of all three sources will lead to a better understanding of the full patient journey which will yield insights for new treatment approaches and comparative effectiveness data,” Pickett said.

With pharmaceutical industry and the medical community working hand in hand with data scientists, there can be a positive change in how the mental health community is treated. The stigma has the chance to slowly become history as doctors can visualize the decades’ worth of data to form a better plan of action for treatment with the help from data scientists.

 

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