Measurement-Based Care in Behavioral Health—and Where SessionGlance Fits In

Measurement-based care (MBC) has become one of the most consistently supported ways to improve outcomes in behavioral health, yet it remains surprisingly underused in everyday practice. A major narrative review in JAMA Psychiatry describes MBC as the routine use of symptom and outcome measures to guide treatment decisions in real time—not just every 90 days or at discharge, but before or during most sessions (Lewis et al., 2019).

Despite decades of research showing that MBC can accelerate improvement, reduce deterioration, and support more precise clinical decisions, fewer than 20% of behavioral health clinicians use it regularly (Lewis et al., 2019). That gap between what works in the research literature and what happens in routine care is exactly where SessionGlance aims to help: by making measurement-based care feel less like an add-on and more like a natural extension of what clinicians already do.

In many ways, MBC formalizes what good therapists are already trying to do—track progress, notice who is not improving as expected, and adjust treatment accordingly. What changes with MBC is that this process becomes visible, structured, and sharable with both clients and care teams, rather than remaining implicit or intuitive.

What the Research Says About Measurement-Based Care

Lewis and colleagues (2019) describe MBC as having four core components: administering brief, standardized measures routinely; clinicians reviewing data; patients reviewing data; and collaboratively using those data to adjust treatment. When all four pieces are present, MBC becomes a feedback loop that can detect non-response early and guide timely course corrections.

Across more than 20 randomized and quasi-experimental studies, MBC has been associated with:

• Faster improvement in symptoms for many clients.
• Reduced likelihood that patients deteriorate during treatment.
• Particularly strong benefits for clients who are “off track” or at risk for poor outcomes (Lambert et al., 2003; Lewis et al., 2019; Shimokawa et al., 2010).

In one meta-analysis, routinely feeding back outcome information to clinicians significantly decreased the proportion of patients who worsened in treatment (Lambert et al., 2003). Other work has shown that MBC can be especially powerful for clients who might otherwise drop out or remain stuck without targeted changes to the treatment plan (Shimokawa et al., 2010).

The review also highlights that MBC is transdiagnostic and transtheoretical—it can be integrated into cognitive-behavioral therapy, psychodynamic therapy, ACT, family therapy, and more, without requiring allegiance to a specific school of intervention (Lewis et al., 2019). In other words, MBC does not replace your preferred model; it supports it with structured feedback.

Why MBC Isn’t Used as Often as It Should Be

If MBC works so well, why isn’t everyone doing it? The review points to barriers at multiple levels (Lewis et al., 2019), many of which will feel familiar to practicing clinicians:

• Patient-level: concerns about confidentiality, measure burden, or whether questions feel relevant to their lived experience. Some clients disengage from rating scales if they never see how the scores are used.
• Clinician-level: time pressure, skepticism that standardized scales add value beyond clinical judgment, and fear that outcome data might be used punitively—to rate performance, inform bonuses, or justify staffing cuts.
• Organizational-level: lack of EHR integration, limited staff time for training, and minimal ongoing support. Even highly motivated clinicians struggle when there is no clear workflow or technological support.
• System-level: misaligned incentives and limited reimbursement structures that do not reward outcome monitoring or continuous quality improvement.

Implementation science suggests that technology—specifically measurement feedback systems—can reduce some of these burdens by automating data collection, scoring, and visualization (Lewis et al., 2019). However, these systems only help when they are intuitive, integrated, and sensitive to the realities of clinical work.

Where SessionGlance Fits: A Practical Pathway to MBC

SessionGlance was designed to help clinicians practice measurement-based care in a way that is clinically meaningful and financially sustainable. It does this by handling the logistics of data collection and documentation while keeping the clinician’s judgment and voice at the center.

Rather than asking therapists to log into one system for outcome measures, another for notes, and a third for reports, SessionGlance pulls these elements together. The goal is to make MBC feel like a natural part of therapy, not a separate task that competes with the therapeutic relationship.

SessionGlance aligns closely with the core components of MBC described by Lewis et al. (2019):

1. Routine Symptom Measurement

After each recorded session, SessionGlance can prompt completion of brief, standardized rating scales (e.g., mood, anxiety, functioning, resilience). These measures are tied to each encounter rather than only periodic reviews, supporting the “every or most sessions” standard emphasized in MBC research.

Because these measures are integrated into the SessionGlance workflow, clinicians don’t have to juggle separate survey links, clipboards, or spreadsheets. Over time, the platform builds a clear visual record of how symptoms and functioning change across weeks and months of treatment.

2. Clinician Review of Data

In the online clinician portal, scores and trajectories are displayed over time, making it easy to see who is improving, who is stuck, and who might be worsening. Draft psychological assessments and session summaries embed these data directly into the narrative, reducing the friction of “going to find the numbers” elsewhere.

This makes it more realistic to do what the research recommends: use data not just for reporting, but to guide clinical decision-making. For example, a plateau in anxiety scores may prompt a shift in intervention focus, while a sudden spike may trigger additional risk assessment or consultation.

3. Patient Review of Data

Client-facing feedback reports summarize recent sessions and highlight key symptom trends, reinforcing insight and helping clients see their own progress (or areas needing focus). This is consistent with evidence that MBC is most powerful when both practitioner and patient understand and use the data together (Lewis et al., 2019; Scott & Lewis, 2015).

Seeing a graph of improvement—or lack of change—can open up conversations that might otherwise feel difficult to start. Clients can ask, “Why do you think my scores went up this month?” and “What might help us get back on track?” This kind of shared inquiry is at the heart of collaborative, feedback-informed care.

4. Data-Informed Treatment Adjustment

Because SessionGlance organizes session themes, interventions, and symptom change in one place, it becomes easier to:

• Revisit and update the case formulation when the data suggest a new pattern.
• Shift session focus based on what is or isn’t changing.
• Adjust frequency or intensity of care when needed.
• Justify adjunctive services, referrals, or continued treatment in documentation.

These kinds of data-informed shifts are central to how MBC improves outcomes over usual care (Lewis et al., 2019; Scott & Lewis, 2015). Instead of waiting until the end of treatment to discover that therapy “didn’t work,” clinicians and clients can make earlier, smaller course corrections.

SessionGlance and MBC as a Financially Sustainable Practice

One of the key insights from the MBC literature is that implementation is far more likely to succeed when reimbursement structures and incentives align with the work required (Fortney et al., 2017; Lewis et al., 2019). SessionGlance helps support this alignment by linking measurement and documentation to existing CPT structures.

• Draft documentation for CPT 96130: By turning session material and outcome data into draft psychological evaluations, SessionGlance helps clinicians more efficiently document evaluative work that supports billing under CPT 96130 (first hour of psychological testing evaluation and integration of data).
• Embedded measures, not extra work: Because rating scales launch automatically after uploads, clinicians aren’t juggling separate survey links or paper forms. Measurement becomes part of the workflow, not an additional task that competes with client care.
• Practice-level insight: Aggregated, de-identified data across clinicians can help practices understand their own outcomes, identify training needs, and demonstrate quality to payers and partners, echoing the quality improvement goals described in the MBC literature (Fortney et al., 2017; Lewis et al., 2019).

When measurement, documentation, and reimbursement are aligned, clinicians are less likely to experience measurement-based care as “one more unfunded mandate” and more likely to see it as a way to sustainably support high-quality practice.

Why This Matters for Everyday Clinical Work

The Lewis et al. (2019) review makes a clear case: when implemented with fidelity, MBC can improve outcomes, reduce deterioration, and help clinicians make more informed, timely decisions. At the same time, doing MBC well requires infrastructure, training, and sustained support.

SessionGlance is one response to that challenge. It aims to:

• Bring MBC into private practices and smaller clinics that may not have large IT teams.
• Embed rating scales and visual feedback into the natural flow of therapy rather than bolting them on at the edges.
• Translate the “invisible labor” of synthesis and evaluation into structured, billable documentation that supports both care quality and reimbursement.
• Preserve clinician expertise and voice while reducing documentation burden, so time and energy can be re-invested in the therapeutic relationship.

In practice, this might look like a therapist and client reviewing a short graph together once a month, noticing that anxiety scores have leveled off, and collaboratively deciding to focus more directly on avoidance patterns. Or it might involve using a longitudinal summary from SessionGlance to support a consultation with a prescriber or to document the rationale for continued care.