From collection to action: how MTSS data tracking improves interventions

Most schools collect large amounts of MTSS data, but too often, that data doesn’t lead to timely action. When information is scattered across academics, behavior, and mental health systems, teams are left reacting instead of intervening early. 

https://ies.ed.gov/rel-northeast-islands/2025/01/multi-tiered-systems-support-and-importance-promoting-student-well-being

Common MTSS challenges include:

• Data living in silos across academic, behavioral, and mental health supports
• Delays between identifying concerns and providing intervention
• Behavioral and mental health data are being inconsistently included in MTSS decision-making

When early warning signs are missed, students may move unnecessarily into Tier 2 or Tier 3 supports. Over time, this can contribute to staff frustration, burnout, and increased student disengagement.

This guide explores how intentional MTSS data tracking helps teams transition from collection to action, utilizing timely, coordinated insights to enhance interventions and better support students before challenges escalate.

Collecting MTSS data with purpose, not paperwork

Collecting MTSS data is only effective when it supports clear decisions. Without defined decision points, teams can end up tracking large amounts of information without knowing how or when to act on it. The result is often delayed intervention and unnecessary data overload.

To keep MTSS data actionable, collection should be guided by three core questions:

1. What decisions are we trying to make? MTSS teams should first identify the decisions they need data to support—such as whether a student needs additional support, if an intervention is working, or when it’s appropriate to adjust services. Starting with decisions helps prevent data collection from becoming unfocused or excessive.

2. What information helps inform those decisions? Effective MTSS data reflects the entire student experience. Academic data alone rarely tells the whole story. When teams consider academic, behavioral, attendance, and mental health indicators together, they’re more likely to identify early warning signs and respond before challenges escalate.

3. When will we review and act on the data? Clear timelines are essential. Establishing regular data review cycles helps teams move away from “wait-and-see” approaches and toward timely, proactive intervention. Consistent review makes it easier to spot patterns, evaluate progress, and make adjustments across tiers.

When MTSS data collection is organized around these questions, it becomes easier to move from insight to action. Rather than serving as mere paperwork, data becomes a practical tool for guiding timely and coordinated support. MTSS teams are also more effective when data is centralized, allowing patterns to surface quickly and next steps to be identified without delay.

What “actionable” MTSS data actually looks like

More data doesn’t always mean better results. For tiered supports, quality, clarity and timing are as important as volume. MTSS data should be actionable, available, and linked to interventions.

Universal screening data (Tier 1)

Universal screening is crucial for establishing a solid Tier 1 foundation. Rather than waiting for a student to fail a class or receive multiple disciplinary concerns, proactively checking in helps you identify patterns that should be addressed before students are labeled. As previously noted, it’s essential to monitor a student's academic, behavioral, and social-emotional progress.

Universal screeners can also be used to identify problematic schoolwide patterns. By treating your screening data as a starting point, you can use it to strengthen Tier 1 supports, often before a student’s academic and behavioral needs escalate.

Academic indicators that commonly inform Tier 1 decisions include:

• Benchmarks in reading and math
• Course grades
• Performance on common assessments
• Growth scores from universal screeners
• Rates of missing assignments
• Standards-based report card performance indicators

Behavioral and social-emotional indicators that often signal emerging support needs include:

• Teacher ratings of cooperation, self-regulation, or engagement
• Observable behavior changes, like withdrawal, increased worry, or difficulty managing setbacks
• Attendance patterns
• Tardiness rates
• Frequency of discipline referrals
• Student self-reports on stress or belonging during school hours

Progress monitoring data (tiers 2 & 3)

If a student needs targeted or intensive support at the Tier 2 or 3 levels, it’s important to monitor the data directly tied to specific interventions being used. Effective MTSS data tracking at higher tiers demands frequent and consistent assessment of the skills or behaviors you’re trying to improve or change. By collecting data consistently, you can avoid the “wait-and-see” decision-making that can allow months to pass without adjustments to support.

For example, Tier 2 reading interventions often rely on progress monitoring data such as:

• Weekly curriculum-based measures (CBM) for reading fluency
• Accuracy in specific phonics skills
• Correct words per minute on grade-level reading passages
• Brief comprehension checks after intervention sessions

For interventions targeting anxiety or behavior, progress monitoring may include:

• Student- or teacher-rated anxiety symptoms tracked weekly or biweekly
• Weekly target behaviors, including classroom disruptions or nurse visits
• Ability to use effective coping strategies, tracked daily or weekly with a checklist
• Self-rating by the student using a simple scale (for example, 1 to 5), at the beginning and end of each school day

Fidelity & implementation data

If they’re not used as intended, even well-designed intervention planning won’t offer optimal outcomes. Fidelity and implementation data can help you track whether supports are being used consistently, effectively, and appropriately.

Without effective MTSS implementation data, outcomes are more likely to be misunderstood or misinterpreted. For example, you might assume that a Tier 2 intervention isn’t working for a student, but not realize they didn’t have access to the full intervention. By tracking fidelity, it’s easier to determine whether an intervention for students wasn’t the right fit or if it simply wasn’t implemented properly.

Implementation data helps teams determine whether outcomes reflect the effectiveness of an intervention or issues with its delivery. 

Questions to consider include:

• Were sessions provided as often as planned?
• Were all major components of a curriculum or SEL lesson delivered as intended?
• Were self-ratings or teacher observations used with fidelity checklists to inform data analysis?
• Was the duration of each session as intended?
• Were group sizes and student-to-staff ratios appropriate (especially when interventions were designed for small group delivery)?
• Were missed or rescheduled sessions documented accurately (including reasons why)?

Utilizing MTSS data to drive tiered intervention decisions

As your MTSS data tracking becomes more consistent and focused, you’ll see how the information can help you make informed decisions.

Tier 1: Strengthening universal supports

At the Tier 1 level, the goal is to identify trending data so your universal environment is as supportive as possible. According to research on MTSS, data-informed improvements made at the Tier 1 level can enhance academic outcomes and improve social-emotional functioning for most students.

Trending MTSS data can help teams make informed adjustments to:

• Instructional practices: If benchmark data identifies reading difficulty patterns across multiple grades, you might decide to adopt evidence-based literacy strategies as a school-wide initiative.
• SEL programming: If your universal screening shows increased rates of anxiety or lower resilience scores among students, you can implement SEL lessons focusing on skills for coping and emotional regulation.
• School-wide climate strategies: Attendance or behavior trends can help you make informed decisions about aspects such as hallway routines, transitions, and other strategies that reinforce positive behaviors.

Having a plan in place ensures your Tier 1 level is responsive and updated regularly, which can help prevent unnecessary Tier 2 referrals. This not only benefits students but can help reduce resource overload and staff burnout for educators.  

Tier 2: Refining targeted interventions

MTSS data at the Tier 2 level should provide clear entry and exit criteria. Utilizing data also helps you match interventions to the actual needs of the student, not what’s available.

Decisions to move a student in or out of Tier 2 should be definable, not solely subjective. For example, a student may require reading support based on universal screener data and teacher concerns. When possible, there should be clear goals to exit Tier 2 support upon meeting defined growth targets over a specified time period.

Tier 3: Individualized, high-needs support

At Tier 3, MTSS data helps you justify intensive or resource-heavy interventions. It ensures you can coordinate services between school and community partners. 

Tier 3 data supports high-stakes decisions by helping teams:

• Document needs that indicate intensive Tier 3 interventions are beneficial
• Coordinate internal and external services to align goals and avoid duplicated efforts
• Reduce or prevent delays for students with urgent mental health needs by identifying red flags such as more frequent nurse visits, an increase in counseling requests, or drops in participation or completion of work

Common MTSS data tracking mistakes to avoid

Even well-designed systems can fall short without clear MTSS best practices for data collection and tracking. Common pitfalls to watch for include:

• Tracking data without defined decision points: Without clear decision rules, collecting multiple measures risks turning meaningful data into mere documentation rather than actionable insights. 
• Over-reliance on academic indicators alone: Don’t make the mistake of relying only on academic indicators, but overlooking behavioral and mental health concerns. If you only focus on grades and test scores, it becomes easy to miss potential underlying social-emotional needs. This can be especially true in cases where a student might not act out, but rather internalizes their stress.
• Inconsistent progress monitoring: Ensure everyone uses the same planning tools and collects data at the same intervals. Inconsistency makes it difficult to compare interventions or assess if adjustments are needed.
• Failing to close the loop after interventions are implemented: It’s essential to have a follow-up procedure in place. Schedule data reviews and identify a clear plan for next steps. Otherwise, students can remain in accelerated tiers indefinitely, even when their data indicates they’re ready for a change.

Turning MTSS data into better outcomes for students

MTSS data is most valuable when it drives action. When teams can make real-time decisions, systems shift from reactive to proactive, supporting students before challenges escalate. Used effectively, MTSS data can lead to stronger social-emotional skills, reduced symptoms, and improved overall functioning in and out of the classroom.

This is especially true when mental health data is fully integrated into MTSS decision-making. When schools know what to track, how often to review it, and how it informs next steps, they can build scalable systems of support that extend beyond academics alone.

Telehealth can play a meaningful role in this framework by expanding access to mental health support and allowing teams to monitor progress consistently across tiers. When paired with purposeful MTSS data tracking, these services help create faster, more coordinated pathways to care.

Learn how Talkspace can support your MTSS framework by integrating mental health services into your tiered system of support. Request a demo today to see how data-driven interventions can improve student outcomes.

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Sources:

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1. “Multi-Tiered Systems of Support and the Importance of Promoting Student Well-being.” 2024. Institute of Education Sciences. February 2024. https://ies.ed.gov/rel-northeast-islands/2025/01/multi-tiered-systems-support-and-importance-promoting-student-well-being. Accessed December 30, 2025.
2. Nitz, Jannik, Fabienne Brack, Sophia Hertel, Johanna Krull, Helen Stephan, Thomas Hennemann, and Charlotte Hanisch. 2023. “Multi-tiered Systems of Support With Focus on Behavioral Modification in Elementary Schools: A Systematic Review.” Heliyon 9 (6): e17506. https://doi.org/10.1016/j.heliyon.2023.e17506. Accessed December 30, 2025.