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Early Warning Indicators Can Flag At-Risk Students Quickly. Why Does Support Take Weeks?

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For superintendents, special education directors, MTSS and student services leads, and school health directors.

Why does support take weeks? Here’s the short answer: Districts have largely solved detection. Early warning indicators reliably identify at-risk students, but research finds that relatively few flagged students receive a matched intervention, and it’s not always clear how long those students wait. The hard part is coordination: educators across the district often have only partial views, and after the student support team meets, no one is assigned to make sure the referral actually leads to support.

Early warning indicator (EWI) system: uses attendance, behavior, and course performance data to flag students at risk of not graduating.

Coordination gap: the space between a flag and a delivered support, where partial views sit in separate systems and follow-up has no owner.

Do early warning indicators identify at-risk students?

Yes, and the evidence for it isn’t new. In a 2007 study, Balfanz and colleagues found that four indicators measured in sixth grade identified 60% of the students who later didn’t graduate. More recently, the UChicago Consortium on School Research looked at Chicago Public Schools students in grades 3 through 8 and found that those with good grades and attendance graduated at 93%, while students off track on both graduated at 39%.

Other districts are seeing the same thing. In Frontline’s K-12 Lens 2026 report, which surveyed 1,058 district leaders across the country, 99% said their district tracks student data, and correlationally, districts that track early warning indicators reported 14% chronic absenteeism compared with 21% for districts that don’t. 

The story gets a bit muddier when we look at what happens in the weeks after a student is flagged.

Grouped bar chart: districts that track early warning indicators report 15% (2025) and 14% (2026) chronic absenteeism; districts that don't report 19% and 21%.
Bar chart: 99% of districts track any student data, 75% track chronic absenteeism, 63% track course failure, and 51% monitor whether interventions work.

What happens to students after they are flagged?

Spotting a student isn’t the same as supporting one. One place to see it is EWIMS, a randomized trial of the Early Warning Intervention and Monitoring System run by REL Midwest and AIR. In participating schools, the system’s early warning tool flagged 9,559 students on at least one indicator, such as chronic absence or course failure. Set next to Frontline’s own district survey data, the numbers look like this.

The EWIMS authors note that some interventions may have occurred without being recorded in the tool, so these figures show a gap between flagging students and recording support. “Same category” also means the intervention fit the type of flag, not that it was built around the individual student.

It also helps to read these figures against MTSS, which commonly expects about 10-15% of students to need targeted (Tier 2) support and 1-5% to need intensive (Tier 3) support. Because about half of students were flagged, 27% of students works out to roughly 13% of all students, which isn’t necessarily low. The open question is how long those students waited.

47% of districts that track warning signs are unsure how many flagged students received support.

EWIMS isn’t just a data tool. It’s a seven-step cycle: set up a team, load the data, review it, work out why students are flagged, assign interventions, monitor whether they work, and then evaluate and adjust the process itself.

In the first year, most of the 37 schools got through the setup steps, and about half used the data tool at a high level. Far fewer carried the middle steps through. Only 11–22% reached a high level on reviewing the data, interpreting it, assigning interventions, and monitoring students. Step 7, reflecting on the process, rebounded to 49%.

Dot chart: 51% of EWIMS schools used the data tool well, but only 11–22% reached a high level on steps 3–6.

Districts may be creating data that can help surface at-risk students, but it’s less often that they review that data, interpret it, and assign students to interventions based on what it tells them. This work requires clear ownership of each step in the intervention process and timely handoffs of student information.

Case example: one student’s first 14 weeks

We often talk about a student named Jayden. He’s a composite, but the details could apply to any number of students.

Here’s how the first 14 weeks can go — even though every adult in the building is attentive and working hard.

In week 2, the school nurse logs Jayden’s third stomachache visit, and then his sixth, in a health record that only the health office sees. A week later, the attendance clerk notices that Jayden has frequently been late and logs it in the SIS. His teacher sees the missing homework and the way he’s become more withdrawn and mentions it to a colleague over lunch, but they lack an obvious place to write it down. In week 6, the assistant principal has a behavior referral on her desk, but it doesn’t mention the stomachaches. 

In week 7, Jayden’s early warning signals (or rather, one of them) are noticed when his attendance crosses a threshold, but it’s an attendance flag and nothing more. It takes two weeks before the support team meets — the first time all the pieces are put together. The counselor gets a referral in week 10, but she has a full caseload and there is no one assigned to follow up. By the time Jayden’s report card is sent home, support still hasn’t started, even though every adult was acting on what they could see.

imeline: nurse visits begin in week 2, behavior referral in week 6, warning flag in week 7, team connects the pieces in week 9, referral in week 10, report card in week 14 with support still pending.

You probably recognize the pattern. Angela Watson, Director of Health Services at the School District of Pickens County, described a team that found one student with 20 health room visits, 15 tardies, and four write-ups, and the work of “putting all that together.”

“When we’re able to pull that and see that Johnny has, in the first nine weeks, been to the health room 20 times, and you’re sitting in a room with a team and the assistant principal says, ‘Wait a minute, Johnny has also come in late 15 times,’ and then another person says, ‘He’s also been written up four times,’ all of a sudden you start putting all that together and you realize there’s more going on with that student than just asking to go to the health room.”

Angela Watson Director of Health Services, School District of Pickens County, SC

This doesn’t only impact students; teachers and staff feel it, too. In the K-12 Lens 2026 report, 37% of special education leaders named student behavior and support demands as the top threat to staff retention.

Why do flagged students still have to wait for support?

Everyone saw part of Jayden’s story, but no one had the whole picture — at least not until too much time had passed. There are (at least) two problems that contribute to this: 

Four school staff stand in a circle, each holding a different puzzle piece that would fit together, with an empty outlined space in the middle.

Multiple vantage points. The nurse, the clerk, the teacher, the assistant principal, and the counselor each hold a true but partial picture, and each works in a different system. Nothing is wrong with any individual view, but since each adult only has their own view, the pattern goes unnoticed until people begin comparing notes.

A school staff member holds out a folder like a relay baton toward an empty lane while colleagues nearby point to someone else.

Who owns the next step. Even after the pieces come together, the distance between “we should do something” and “someone did it” often has no name attached to it. The meeting ends, everyone nods, and the referral… sits in a queue.

The research points the same way. A 2022 review by Zabek and colleagues of school counselors, psychologists, social workers, and nurses found that their skills are often underused in day-to-day practice, and pointed to service fragmentation as one barrier to care. A 2026 qualitative study of Coordination of Services Teams found that well-functioning teams relied on a universal referral system for identifying student concerns and a coordinated system for centralizing student support services. As is so often the case, if everyone is responsible to move the ball forward, no one is responsible.

In practice, this is the work of student support coordination, the daily job behind MTSS, student intervention tracking, referral follow-up, school health, and special education case management. Districts do each of these already, usually in separate places, and the connections between them tend to get made through memory, email, and hallway conversation.

What does delay cost, and can it be shortened?

In a 2025 study of 520 K–12 students referred for school-based mental health services, 60% had started services by the following year, which means four in ten hadn’t. A 2025 RAND survey of 1,019 principals found that about 40% say it is hard or very hard to get care for students who are identified through a mental health screening.

Stacked bar: of 520 referred K–12 students, 314 (60%) started mental health services and 206 (40%) had not a year later.
Donut chart: about 40% of principals say getting care for students who screen positive is hard or very hard.

But delayed care isn’t how it always is or has to be. One school-based psychiatry program got more than 300 students to a first appointment within 10 days, against a historical wait of eight weeks.

Three questions for district leaders

Here are three questions to take to your own team:

  1. How many weeks pass between the first signal and the first support in your district?
  2. Who owns a referral after the meeting ends?
  3. How many people would you need to ask to assemble the full picture of one flagged student?

In the EWIMS randomized study, a structured process that assigned owners to follow up reduced chronic absence from 14% to 10% and course failure from 26% to 21% in one year. (Note: this didn’t improve every single outcome, and a 2025 replication didn’t repeat those results, so take this evidence with that in mind.) 

Paul Lucero, Director of Assessment in Colton Joint USD described the shift districts are trying to make: “We’re moving from information to knowledge. When we treat the people in the room as experts and combine their context with clean data, the actions actually change outcomes.”

The student from the opening image sits with a counselor and smiles slightly while the nurse, teacher, office staff, and assistant principal stand together behind them.

We are elevating Frontline into a System of Intelligent Action, built to surface what needs attention, propose the next step, and help people act, so a student who is flagged in week 7 receives support in days, not weeks, and remains visible to everyone involved, from the first nurse visit to confirming the services have been delivered.

FAQs

What is an early warning system?

Do early warning systems improve student outcomes?

Why don’t more flagged students receive interventions?

Who should own a student referral after a support team meeting?

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