Behavioral health providers are hungry for meaningful innovations in treatment modalities.
A cutting-edge technique known as precision psychiatry could be an answer to fostering more timely and improved outcomes, experts told Behavioral Health Business. This practice, an application of the more general term precision medicine, requires significant data and technology investments, however, which could hamper the adoption process.
Precision psychiatry tailors treatment plans and prescriptions to a patient’s specific presentation, symptoms, medical history, and diagnosis, using algorithms applied to patient-submitted data. Machine learning can provide clinicians with recommendations for the drug most likely to be effective for a particular patient.
“You might think that that happens in traditional practice, but in fact, many, many practitioners take a much more of a one size fits all to care,” Dr. Mimi Winsberg, chief medical officer and co-founder of mental health provider Brightside Health, told BHB. “If you look … at prescribing practices across the country, most practitioners are using one to three different psychiatric meds and not going farther afield than that.”
San Francisco-based Brightside provides psychiatry, therapy and crisis care for adults and teens aged 13 to 17. The provider’s precision algorithms allow its clinicians to be “armed with clinical decision support.” This means that machine learning algorithms evaluate a patient’s “unique signature” of symptoms and suggest the best course of treatment.
A precise approach may even rid the behavioral health industry of a controversial term: treatment-resistant depression. This condition has multiple definitions but is generally recognized as a failure to respond to at least two different types of antidepressants.
The term implies that patients can’t be treated, Winsberg said. Instead, she claims these patients simply require a more unique approach.
“One of the academic questions that arise out of this is: Were these patients just difficult to treat to begin with, or did giving them the wrong agents actually turn them into difficult-to-treat patients?” Winsberg said. “Just putting them on the most common antidepressant is not likely to work.”
Precision care is distinct from measurement-based care, which has become more common across the behavioral health industry, so much so that providers have suggested that the term is “lip service.”
Providers practicing measurement-based care use data accumulated across patients’ course of care to inform clinician decisions about treatment paths.
Measurement-based care is the opposite end of the treatment cycle from precision, according to Winsberg, since measurements can only provide information based on outcomes from initial treatment attempts. While measurement-based care is “an important aspect of closing the loop,” precision care can give patients a better shot at improving from the get-go.
The current state of precision psychiatry
Precision medicine has only been practicable recently, due to the availability of what Dr. Jordan Smoller, professor of psychiatry at Massachusetts General Hospital and Harvard Medical School, called “big data.” For Smoller, “big data” includes the use of machine learning, artificial intelligence and billions of data items acquired from electronic health records (EHRs).
Smoller is also the director of the Center for Precision Psychiatry at Mass General Hospital.
While new technology makes precision psychiatry possible, the concept has not yet caught on to any large degree in the behavioral health industry.
“We’re just at the beginning of seeing these kinds of efforts moving towards clinical practice,” Smoller said. “The concept of what’s made precision psychiatry a viable aspiration has in part been the advent of very large data sources. Resources and understandings of the underlying biology, the underlying psychosocial contributors to illness, things that we didn’t really have, and we still don’t have the full picture until relatively recently.”
Brightside’s approach to precision psychiatry starts at intake, asking patients a set of questions with branch logic, which involves patients getting different follow-up questions based on their answers to previous questions. These answers then allow Brightside’s algorithms to offer clinical suggestions on psychopharmaceuticals, program selection and program type.
Setting up the technology necessary to make these recommendations is easier said than done. Brightside grew with machine learning algorithms as its backbone from its founding, Winsberg said, giving the provider a serious backlog of data. Data collection, storage and management would all be potential roadblocks for providers building out precision capabilities.
Once implemented, precision psychiatry can set a provider worlds apart from its peers while improving outcomes.
“Is a typical practice even taking into account this notion of precision psychiatry? I would say no,” Winsberg said. “When you look at the CMS data of how prescribers are practicing across the country, they’re typically using one to three medications. They’re using the same treatments over and over and over again, regardless of how patients are presenting.”
One example of precision care in practice is pharmacogenetics, in which genetic tests help determine if patients carry genetic variants associated with drug responses. These tests have become an industry in itself, with multiple options commercially available.
The evidence for these tests thus far is “modest,” according to Smoller, and they have some limitations. Additionally, these tests are mostly limited to a few genetic variations that researchers have long known about, including genes that encode drug-metabolizing enzymes like the P450 enzymes.
Many professional organizations have recommended against making these tests part of routine care, Smoller said, but the tests can still be useful in certain circumstances.
There is also progress in using a precision approach to drug discoveries, in which genomics is used to identify which genes, proteins and compounds are involved in a condition and then developing drugs to target that specific biology.
“That’s not how psychiatric drug development has been in the past,” Smoller said. “It’s been serendipity and based on people’s limited understanding of the biology of, say, depression.”
Even transcranial magnetic stimulation (TMS) is becoming more precise using improved knowledge of brain circuitry, Smoller said.
The future
Precision psychiatry could be a “real leap forward” for the behavioral health industry, Smoller said, and dramatically enhance outcomes.
Moving beyond trial and error approaches to precision techniques also has benefits beyond the clinical.
“We could see cost-effectiveness for the industry and for society at large, in the sense that we are now being much more efficient at providing treatments that are going to work faster because we’re not going through this trial and error cycle,” he said.
For drug developers, precision psychiatry could be a “double-edged sword,” however. Without a precise approach, effective drugs can be applied to large swaths of patients. With precision psychiatry, drugs would be stratified to smaller groups of people, but have much greater efficacy.
Clinicians, meanwhile, are hungry for these types of innovations, according to Smoller.
Winsberg said she is optimistic that precision psychiatry will become more widely implemented within the next five to 10 years.
“I’d love to see this notion of treatment resistance going by the wayside and instead thinking about a patient as requiring complex treatment off the bat,” she said. “So getting patients into the right treatment arms in a more timely manner will drive outcomes.”
Precision medicine is likely to grow in the psychiatric field and is set to expand across other behavioral health specialties as well. Dori Steinberg, vice president of research at eating disorder provider Equip, previously told BHB that precision care could be the key to improving the efficacy of eating disorder treatments.
San Diego-based virtual eating disorder provider Equip treats patients using family-based treatment, enhanced cognitive behavioral therapy (CBT-E) and dialectical behavioral therapy, among other modalities. In September 2023, the provider netted a $20 million investment from General Catalyst.
While precision care is one of the most exciting opportunities for eating disorder treatment to evolve, according to Steinberg, the modality is still in the research phase for eating disorder treatment.
“An individual provider can provide very one-on-one individualized care, but how do you do it when you’re trying to reach the millions of people with eating disorders,” Steinberg said. “At Equip we have it on our roadmap and thinking about how we’re gonna get there.”
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