Sometime soon, a patient is going to look at their therapist and ask a question that should make all of us a little uncomfortable: "I can track my sleep, my heart rate, and my steps in real time. Why is my mental health the one thing nobody's watching between appointments?"
The practices that already have a good answer to that question will help define the next decade of behavioral health. The ones that don't will spend it catching up.
We've covered a lot of ground in this series. We've explored what RTM is, how it differs from RPM, the specific CPT codes that make it billable, the clinical science of measurement-based care, the business case, the implementation playbook, and the emerging roles that make it all work.
Now let's look forward.
RTM, as it exists today, is version 1.0. The infrastructure is in place, but the potential is still largely unrealized. Here's where I believe this is headed, and what forward-thinking behavioral health leaders should be preparing for.
Trend 1: AI-Enhanced Clinical Intelligence
The most obvious evolution is the integration of artificial intelligence into RTM workflows. Today, clinicians review patient data manually, scrolling through mood logs, assessment scores, and engagement metrics. That's manageable with 20 patients. At 100 patients, it's unsustainable.
AI has the potential to turn RTM data from a stream into a signal. Pattern-detection algorithms can identify concerning trends (sustained mood decline, sleep disruption, disengagement) and surface them to clinicians as actionable alerts. Natural language processing can analyze patient journal entries or messaging patterns for early warning signals. Predictive models can flag patients at elevated risk of dropout, crisis, or treatment non-response before those outcomes manifest.
This isn't speculative. Research is already demonstrating that passive smartphone sensing (data collected without active patient input, such as movement patterns, screen time, and social interaction frequency) can detect behavioral changes associated with psychiatric symptom worsening. The field of digital phenotyping, advanced by researchers like John Torous and colleagues at the Division of Digital Psychiatry, is progressing rapidly, and its integration with RTM frameworks is a natural next step.
But, and this is a critical "but," AI in mental health must remain a decision-support tool, not a decision-making tool. The clinician has to retain interpretive authority, and the therapeutic relationship has to stay human. Technology should surface insights, not make diagnoses or prescribe interventions. The practices that get this balance right will lead the field. The ones that prioritize automation over clinical judgment will lose both their patients and their credibility.
Trend 2: Expanded Payer Coverage
CMS has been the primary driver of RTM reimbursement, but commercial payers are increasingly following suit. Major commercial insurers have begun publishing coverage policies that recognize RTM services, and as more claims data accumulates and the evidence for RTM's impact on outcomes and costs grows, I expect payer adoption to accelerate.
We may also see the emergence of value-based arrangements that incorporate RTM data. Imagine a contract where a behavioral health practice is rewarded for demonstrating measurable improvement in patient-reported outcomes: depression scores trending downward, anxiety scores stabilizing, or treatment completion rates rising. RTM provides exactly the data infrastructure needed to support those arrangements. Measurement-based care has long been recognized as a way for organizations to align with value-based payment models, precisely because it generates the care-quality and outcomes data those contracts depend on.
Trend 3: Between-Session Care Becomes Standard of Care
This is the biggest shift. For decades, mental health treatment has been defined by sessions: 50 minutes, once a week, in an office (or on a screen). What happens between sessions has been largely invisible to the healthcare system.
RTM is beginning to change that. As monitoring tools become more sophisticated, reimbursement pathways mature, and the evidence for between-session engagement grows, I believe we'll reach a point where continuous, structured support between therapy sessions is considered a basic component of quality mental health care, not an optional add-on.
This doesn't mean therapy becomes 24/7. It means the therapeutic ecosystem extends beyond scheduled appointments to include structured check-ins, skill practice, self-monitoring, and data-informed outreach. It transforms the patient's experience of care from episodic to continuous.
Trend 4: The Workforce Will Evolve
As RTM scales, the behavioral health workforce will need new roles and new competencies. Digital navigators, as we discussed earlier in this series, will become standard team members. Clinicians will need training in data interpretation, digital tool integration, and hybrid care delivery. Practice leaders will need expertise in RTM billing compliance, platform evaluation, and outcome-based program design.
Graduate training programs will eventually build these competencies into their curricula, but for the current workforce, continuing education and practice-based learning will be the primary pathways. And the encouraging part is that even short, focused training can meaningfully improve clinicians' comfort and competence with digital tools.
Trend 5: Patients Will Expect It
This may be the most powerful trend of all. As digital health tools become ubiquitous in every other domain of healthcare (cardiology, endocrinology, oncology), patients will begin to expect the same from their mental health providers. They'll ask: "Why can't I track my mood between sessions? Why doesn't my therapist see how I'm doing between appointments? Why am I only getting help once a week?"
The practices already offering this experience will have a significant competitive advantage. The ones that aren't will face growing pressure from patients, payers, and regulators to evolve.
The Real Takeaway
Here's my final takeaway from this series: RTM is not a story about technology. It's a story about transformative care delivery. The technology is simply the enabler of an evolution that is clinical, operational, and cultural, rooted in the belief that patients deserve continuous support.
The future is about building systems that make that support sustainable and reimbursable while keeping the human connection at the center of care, even as the tools around it evolve.
It's been encouraging to see the level of interest and engagement throughout this series. If you're a practice leader, clinician, or administrator who's ready to take the next step, start with what we've covered here: understand the codes, do the math, choose a platform, pilot with a small cohort, and iterate.
The future of mental health care is being written right now. It's up to you to decide how you become part of that story.
Thank you for reading. I'd love to hear your vision for where behavioral health is headed. What excites you? What concerns you? Let's keep the conversation going.
#FutureOfMentalHealth #RTM #AI #BehavioralHealth #DigitalHealth #MeasurementBasedCare #HealthcareInnovation #TherapeuticAlliance #MentalHealthLeadership
References & Sources
Torous, J., et al. (2021). The Growing Field of Digital Psychiatry: Current Evidence and the Future of Apps, Social Media, Chatbots, and Virtual Reality. World Psychiatry, 20(3), 318-335. https://pmc.ncbi.nlm.nih.gov/articles/PMC8429349/
Torous, J., et al. (2025). The Evolving Field of Digital Mental Health: Current Evidence and Implementation Issues for Smartphone Apps, Generative Artificial Intelligence, and Virtual Reality. World Psychiatry, 24(2), 156-174. https://pmc.ncbi.nlm.nih.gov/articles/PMC12079407/
Bond, R.R., et al. (2023). Digital Transformation of Mental Health Services. npj Mental Health Research, 2(1), 13. https://www.nature.com/articles/s44184-023-00033-y