We are in the middle of a mental health crisis. Demand for care is growing, outcomes are falling short, and clinicians are burning out. Even with effective treatments available, most people aren’t getting care that truly fits their needs. Providers are often left making high-stakes decisions in brief appointments, without the information they need to see the full picture. Too much of mental healthcare still relies on broad protocols and surface-level checklists, missing the root causes that shape each person’s experience.
The Case for Precision in Mental Health
That’s where precision mental health comes in, offering a new approach that helps clinicians deliver care tailored to each individual. Instead of relying on broad labels like “depression” or “anxiety,” it considers factors such as sleep patterns, trauma history, biology, and environment to guide care decisions.“Depression is very heterogeneous, yet we start with the same treatments for everyone,” says Laura Hack, MD, PhD, director of the Stanford Translational Precision Mental Health Clinic. By continuously measuring and analyzing what changes over time, clinicians can move beyond trial-and-error treatment and provide more effective, tailored support.
In this way, precision mental health acts as a force multiplier, helping clinicians do more with the skills they already have. With predictive models and data-driven insights, providers can make faster, more confident decisions, offering patients the right care sooner.“There is such a sense of urgency with these conditions,” says Leanne Williams, PhD, director of the Stanford Center for Precision Mental Health and Wellness. “If we could get this into practice, we could be changing lives.”
Jordan Smoller, MD, ScD, director of the Center for Precision Psychiatry at Massachusetts General Hospital, further adds: “The merger of big data and artificial intelligence is helping to advance the promise of precision medicine in psychiatry, that is, tailoring treatments more efficiently to the specific needs of individual patients.”
Why Measurement Is Foundational
Personalized care depends on having the right information, but today’s mental health tools often rely on quick checklists or static snapshots that miss key details. A patient’s symptoms, biology, behavior, and environment aren’t fixed, they change over time. Yet most clinicians don’t have a way to track that in real-world settings.
To move beyond guesswork, mental health care needs measurement systems that are dynamic and multi-dimensional, capturing patterns like sleep, stress, or treatment response as they evolve. As Amie Leighton, CEO at Allia Health, puts it: “Even the best doctors can’t keep all this in their head; that’s where technology can help.”
Without that kind of ongoing measurement, it’s impossible to predict what will work for whom and to adjust care as people’s needs shift in real time. “Clinicians can’t manage what they can’t measure,” says Saroosh Khan, CTO at Allia Health.
The Bigger Picture: From Fragmentation to Integration
Today’s mental healthcare is fragmented, and this disjointed approach drives up costs, creates inefficiencies, and leaves both patients and payers without clear outcomes.
For payers, employers, and health systems, fragmented mental health care means rising costs and uneven outcomes. Therapy, medication, and lifestyle factors like sleep and nutrition are too often handled in silos, leading to inefficiencies and gaps in care.Precision mental health offers a more integrated path forward by combining clinical insights, real-world data, and predictive tools to deliver proactive, personalized care at scale. This not only improves patient outcomes but also reduces unnecessary appointments, ineffective treatments, and downstream healthcare costs.
“Payers need predictable outcomes,” adds Khan. “They need to understand what a treatment costs, who it works for, and how it reduces long-term risk. Without data that maps those patterns, insurers won’t move.”
That said, precision doesn’t equal perfection. These tools carry real risks: from data privacy concerns to over-reliance on AI without human oversight. For patients, providers and payers to trust precision mental health, clear ethical guardrails are essential. That means transparency, human-centered design, and clinical validation, ensuring technology supports better care without creating new risks.
By Colleen Reilly
