It’s Time for the Tech Revolution to Come to Mental Health Diagnoses

While breast cancer garners widespread attention, mental health awareness often lingers in the shadows when […]

While breast cancer garners widespread attention, mental health awareness often lingers in the shadows when compared to other medical conditions. The two diseases stand at opposite ends of the spectrum of diagnosis, treatment and scientific understanding.

It’s time to take a page from advances in breast cancer diagnosis and care and apply it to mental illness. What do I mean by that? Well, thanks to advances in precision medicine, people who receive breast cancer diagnoses today have far more information about the kind of cancer they are facing and — with the help of tumor typing, genetic analysis and more — what treatments are likely to be most effective. Advances in diagnostics and therapeutics have improved outcomes for millions of people living with and fighting breast cancer.

Contrast this with how we diagnose mental illness today. Patients are often told they have “depression” or display symptoms consistent with “anxiety.” But these are broad and imprecise categories — and using such broad and vague terms would be unthinkable in other areas of medicine. More troublingly, prescribing effective medicines to treat these conditions is more art than science, and it often takes years of trial and error to find the right combination and dosage. This too is untenable. We need to take inspiration from the progress in oncology over the last few decades and challenge ourselves to adapt its successful playbook to mental illness. It’s time for precision psychiatry.

The National Institutes of Health estimates that more than 1 in 5 Americans live with mental illness, but awareness, understanding, and treatments have yet to catch up with diseases that affect far fewer people. Instead, people with mental illness face inconsistent care and low treatment success rates, in large part due to the subjectivity and vagueness of available diagnostic tools.

Treating mental illness is notoriously difficult, and the American healthcare ecosystem is extremely complex – and while there may never be a world without mental illness, we need to avail ourselves of every potential solution, including tech. Unlike cancer, where there are tumor cells that can be identified and analyzed, most mental illnesses lack known biomarkers that can be tested and typed. But we must do better than broad interviews, outdated questionnaires and personal patient histories. Until we get past subjective diagnoses, we can’t begin to fix the problems that plague treatment for mental illness.

To date, mental health tech is almost exclusively focused on addressing downstream effects rather than root causes. Think mindfulness apps and telehealth accessibility. While these are positive innovations, they do little to further our pursuit of precision psychiatry. We need to tap into the mountain of data out there to drive toward better diagnosis and treatment.

Here’s the old way: You decide to seek help. Then you turn to Google to find a provider that is accepting new patients and takes your health insurance. Weeks or even months later, you show up for a 45-minute initial patient evaluation, file redundant paperwork, and meet your clinician – finally. You have about 30 minutes to share every relevant aspect of your entire life story. Good luck remembering everything. If you are seeing a psychiatrist or NP, they’ll likely use the last few minutes of the appointment to make an initial diagnosis based entirely on your 30 minute conversation, suggest a medication they’d like for you to try, write the script, and schedule the follow-up. Chances are, the first medication you are prescribed won’t make your condition any better. You cycle through a few more medications but you still do not improve. With no solution in sight, you decide it’s not worth it, and you’d be better off trying to tough it out on your own.

Imagine instead: In lieu of arriving at the first appointment empty-handed, you’ve been given access to all of your health records aggregated across current and past providers and been able to digitally annotate them and fill in any missing gaps. You’ve used embedded  tools to assess your personality features, your behaviors, and how features of your life history may be relevant to the manifestation of your condition. You come to that first session armed with your complete, handcrafted blueprint – and your clinician has a copy too, so together you can map out a path forward. As you progress in treatment, you’re digitally visualizing  changes in moods and behaviors of interest, and get AI generated insights back on what’s working, what’s not, and what to do about it.

Now picture this same process playing out over hundreds of thousands of clinical sessions. The more data we input, the better we will be able to stratify mental health conditions to bring greater precision to how we diagnose and treat. Mapping patient histories, following the nuanced features of their condition over time, and – ultimately – achieving remission improves ROI for all parties. Insurers will benefit because they’re more precisely and efficiently determining coverage and maximizing patient outcomes. Pharma and diagnostics will benefit because the influx of segmentation data will ignite diagnostic, treatment, and biomarker R&D. And clinicians will benefit because they’re no longer handcuffed by incomplete, subjective information.

We have made major strides in destigmatizing mental illness, but the field is decades behind similar movements. Every year we celebrate Breast Cancer Awareness Month in October. It was first celebrated in 1985 and in the nearly four decades since the annual celebration, it has helped evolve our understanding of the disease. By tapping into the power of data, AI, and tech, we can do the same for mental illness.

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