Ilana Borkenstein

We Built M7 for Nurses, It Turns Out the Rest of Healthcare Needed It Too

M7 Health CEO and RN Ilana Borkenstein shares why software built to solve nurse scheduling is now expanding across clinics and other care settings, and what that reveals about workforce design in healthcare.

When we started M7 Health, our focus was intentional. We built for nurses first.

Not because nursing was the only workforce that mattered, but because nursing is the hardest workforce to schedule well. Nurse staffing sits at the intersection of clinical risk, regulatory complexity, human sustainability, and constant change. Skill mix requirements, union rules, charge coverage, rest periods, fairness expectations, and unpredictable patient volume all collide in one place.

Anyone who has built a nurse schedule knows it is not a simple optimization problem. It is layered decision making under pressure. When it breaks, the consequences show up immediately in patient safety, staff morale, and cost.

Our belief was simple. If we could build a system that nurse leaders actually trusted, one that reflected how units truly operate, we would be solving the most complex version of workforce scheduling in healthcare.

What Surprised Us After Go Live

Within two years of launching, M7 was live across inpatient nursing units at health systems nationwide — from large academic medical centers to rural community hospitals. We grew faster than we expected, and the results were consistent: better schedules, less manual work, fewer last-minute gaps.

What we didn't anticipate was what happened next.

After nurse managers and house supervisors began using M7, other parts of the organization started asking the same question. Could this work for us too? The first requests came from other service lines within health systems, pharmacy teams, respiratory therapy, support staff, who saw what was happening on nursing units and wanted the same. Then came clinics and other care settings altogether.

We didn't go looking for this expansion. Leaders pulled us there. They saw fewer last-minute scrambles, more predictability, and staffing decisions that were both equitable and cost conscious, and they wanted it for their teams. So we built for it.

At Ochsner Health, that's what this looks like at scale. M7 went live across 40+ inpatient hospital campuses in under four months and the results were immediate: over 2,000 shifts filled automatically every week, nurse leaders saving approximately 10 hours per pay period previously spent on manual scheduling, and average staff usage above 90% month over month. Those results are what drove the decision to expand. Ochsner is now rolling M7 out to surgical, procedural, and other frontline shift-based teams across the system. As their CIO put it, expanding beyond inpatient nursing was "a natural next step in our enterprise-wide commitment to operational excellence." Read the full announcement.

The demand never came from a product roadmap. It came from leaders watching something finally work, and from an implementation approach designed to make that happen.

What Clinics Were Struggling With

In many ways, the challenges clinics face mirror hospitals, just in a different shape.

At Diana Health, a multi state women's health network operating across Tennessee, Florida, and Texas, leaders were trying to manage a high cost care model with printed calendars and email attachments. The challenges they faced mirror what many multi-site organizations experience. It's the same dynamics that make central staffing so difficult to get right. Providers floated frequently between clinics. Call coverage had to meet strict contractual requirements, the kind that are only becoming more consequential as The Joint Commission now requires hospitals to demonstrate staffing adequacy as a National Performance Goal. Once schedules were printed, they were outdated almost immediately. There was no reliable way to see coverage across states or track whether providers were meeting call and clinic minimums .

At Oula Health, a modern women's health provider with clinics in New York and deliveries at partner hospitals, the operational reality was far more complex than their tools suggested. Providers rotated across locations. On call coverage spanned clinics and hospitals. Techs and per diem staff floated wherever demand spiked. Leadership lacked a clean view of labor by role, location, or shift type, making overtime and incentive spend difficult to control.

These were not edge cases. They were examples of organizations trying to deliver high quality care with workforce infrastructure that could not keep up.

Why M7 Translates Beyond Nursing

The reason M7 works so well in clinics and other care settings is structural, not accidental.

Nurse scheduling represents the upper bound of workforce complexity in healthcare. It requires systems that can handle dense constraints, constant change, and high stakes decisions without sacrificing fairness or trust. Any platform that can do that already contains the logic needed for environments with fewer regulatory layers and less volatility. The same trust that makes AI-driven tools actually work for nurse leaders applies equally in clinic settings. That trust is also what unlocks ROI.

In clinics, staffing patterns are more predictable. In ambulatory care, patient flow is different. But the core needs are the same. Leaders need visibility. Staff need fairness. Organizations need control over labor spend without burning out their teams.

At Diana Health, M7 provided centralized scheduling across states, real time visibility into provider deployment, and automated reporting to enforce contract compliance and catch cost drift early. At Oula, it created a true multi clinic float pool, reliable on call visibility, and reporting that finance teams could finally trust.

Different settings. Same foundation.

The Common Thread Across Every Setting

Whether we are supporting an inpatient unit or a distributed clinic network, the same principles show up again and again.

Leaders want schedules that reflect reality, not just coverage math. Staff want predictability and transparency. Organizations want stability without relying on premium labor or constant manual intervention.

Poor scheduling creates human cost long before it shows up as financial cost. Burnout, dissatisfaction, and turnover follow patterns of unfairness and unpredictability, a dynamic the 2025 NSI National Health Care Retention & RN Staffing Report quantifies in detail. When schedules improve, retention improves. When retention improves, everything downstream becomes easier, a pattern backed by the data on what better scheduling actually does.

Nursing simply makes this visible faster. Clinics experience the same dynamics over a longer arc.

What This Means for Healthcare Leaders

Healthcare is complex, and change is hard. But in this case, the complexity is exactly why the change is needed. Fragmented tools for different roles, scheduling treated as a commodity, complexity handled manually when systems fall short. That approach creates the instability it was meant to solve.

Our experience suggests the opposite approach works better.

When workforce infrastructure is built to withstand the hardest environment first, everything else benefits. Leaders reduce fragmentation. Teams work from a shared source of truth. Staff experience consistency instead of patchwork solutions.

The question is not whether a system can technically schedule a clinic or other type of healthcare organization. The real question is whether it can dynamically handle complex environments and surface the visibility that leaders actually need, in real time, across roles, before problems escalate. If it can do that for nursing, it can do it everywhere.

Looking Ahead

We will always be deeply committed to nursing. That is where M7 started, and it is where our bar for safety, fairness, and trust was set.

At the same time, we are excited by what we are seeing as M7 expands into clinics and other care settings. Not because it validates our technology, but because it validates a philosophy.

Build for the hardest problem. Respect the people doing the work. Design systems leaders can trust under pressure.

When you do that, the impact does not stay contained. It spreads.

FAQ

Why did M7 start with nurses instead of clinics or other roles?

Because nurse scheduling is the most complex workforce planning problem in healthcare. Solving it required the highest level of rigor and trust.

Why does M7 work well in clinics and ambulatory settings?

Those environments retain important constraints but face less volatility than inpatient nursing. A system designed for nursing already contains what those teams need.

Is M7 moving away from nursing?

No. M7 remains nurse led and grounded in clinical reality. Expansion happens because the same principles hold across settings, not because the focus has changed.