The Nurse Staffing Spreadsheet That Told a Hospital It Needed 9.6 More Nurses

The first version of Parity Healthcare Analytics did not begin with a pitch deck, a hospital procurement committee or a clever piece of artificial intelligence. It began with a disagreement. Heidi Morin, then a nurse director, was being pressed to reduce her workforce. The financial reports pointed one way; what she saw in obstetrics and neonatal care pointed the other. So she built her own staffing calculator and tried it on the units she managed.

Six weeks later, the calculator produced an awkward answer: measured against industry staffing standards, the department was short by 9.6 full-time equivalents. Morin translated the workload into the financial vocabulary her hospital could use. According to her account, the analysis supported additional positions while reducing labor costs, improving morale and decreasing turnover. The important move was not simply asking for more nurses. It was converting patient volume and acuity into a case that clinical and finance leaders could inspect together.

A calculator born in the messy middle

Women’s and children’s services are a rude place to trust a tidy average. Labor and delivery can include triage, surgery, recovery and inpatient care in the same department. A neonatal intensive care unit may have a stable census and a suddenly different workload. Scheduled procedures, admissions and patient acuity do not respect the clean boundaries of a payroll report. A retrospective metric can say what happened last month without helping the charge nurse decide what to do at 2 p.m.

Morin had already spent years looking for a better answer. Her early electronic staffing activity tool was selected for a national poster presentation by the Association of Women’s Health, Obstetric and Neonatal Nurses in 2017. She later joined Maine Medical Center’s Innovation Cohort and developed the prototype that became Parity. A podium presentation followed in 2020. Morin says peers urged her to make the approach available beyond her own hospital. Grant support funded development, then two years of pilots in hospitals in the United States and Canada gave the team a wider test bed. She eventually left her nurse director role to run the company full time.

“Start with the frontline problem.”Heidi Morin’s advice to healthcare innovators

That history explains Parity’s useful specificity. This is not a general dashboard looking for a hospital problem. It is a decision tool built around a recurring question: given the patients here now, the work they require and the people available, how should the unit flex its nursing resources? The software captures real-time census, acuity and unit activity; compares actual staffing with a patient-centered target; and rolls the observations into trends for scheduling, demand forecasting, productivity and budgeting.

Not another schedule

Hospitals already buy scheduling platforms, timekeeping systems, external benchmarks and productivity reports. Parity’s position is deliberately adjacent: it says it does not replace those systems. It supplies the missing decision layer underneath them. Scheduling records who is expected. Timekeeping records who worked. The electronic health record documents care. Parity tries to connect what patients need to what the staffing team should do while there is still time to act.

The company now packages that loop as a workforce performance partnership, not a software license left on the loading dock. Its model has three pieces: experts who analyze performance and recommend changes; a decision-intelligence platform that measures and monitors; and recurring reviews intended to turn findings into an operating habit. Chuck Alsdurf, Parity’s co-founder and chief operating officer, supplies the finance side of the bridge. The public team also includes nursing customer-success expertise and software engineering leadership.

That hybrid model matters because a chart cannot negotiate a staffing change. Nurse leaders need to trust the definitions. Finance needs to understand how the measure relates to cost. Charge nurses need a workflow that does not become another clerical burden. Executives need proof that the change persists. Parity is selling the interpretation and follow-through along with the screen.

The 11-to-11 clue

A 2025 customer story gives the clearest picture of what a hospital can do with the product. Michelle Wafer, executive director of maternal child health at the University of New Mexico Hospital, had been using fixed core staffing for day and night shifts. Parity’s reports surfaced different peaks by day and time, including demand that did not line up neatly with traditional shift changes. The team identified selected days when extra coverage from 11 a.m. to 11 p.m. made more sense.

Wafer did not impose the change across the board. She piloted the new shift with interested nurses. Parity reports that staff felt better supported, nurse availability improved and the operation reduced unnecessary overtime and burnout. The claims come from the company’s own client account, not a controlled study, but the intervention is refreshingly concrete. Instead of declaring a workforce transformation, the unit put people where its own pattern suggested they were needed.

The same logic sits behind Parity’s 2024 pilot with the Maine Rural Maternity & Obstetrics Management Strategies Network. Rural obstetrical units face a harsh mix of low volume, reimbursement pressure and expensive labor. Parity supplied software and data-analysis consulting meant to help participating birthing centers align workforce plans with their patient population, volume and acuity. Later that year, the company became a Premium Industry Partner of Synova Associates, which educates perinatal and neonatal nurse leaders.

What a builder can steal

Parity’s playbook is more portable than its clinical formulas. First, find a consequential decision being made with a proxy that everyone privately distrusts. Second, build the smallest instrument that captures the missing reality at the moment of decision. Third, translate the finding into the buyer’s language. Morin did not stop at patient acuity; she converted workload into FTEs and a financial framework. Fourth, let users pilot a narrow operational change. The 11-to-11 shift is stronger evidence than another colored dashboard.

The company also chose a sensible market wedge. Women’s and children’s services have complex, fast-changing workload and established staffing guidance. That makes the mismatch between a generic productivity formula and frontline reality easier to demonstrate. A narrow wedge can produce credible evidence, language and champions before the product moves across more of the hospital. Parity’s current website describes that broader ambition, while its best-documented deployments remain rooted in perinatal care.

Where the model can stall

Good information does not create nurses who are not available, reopen a closed maternity ward or change an insurer’s reimbursement. An acuity-based recommendation is only useful when a hospital has some flexibility to move, add or reschedule staff. It also depends on consistent frontline input. If capturing acuity is slow, disputed or treated as surveillance, the data layer becomes a new source of friction.

Hospital buying cycles add another brake. Morin identifies timing, budget approvals and resistance to changing familiar productivity models as recurring obstacles. Public pricing is not disclosed, and the economic case will vary by unit and implementation. A prospective customer should ask what data must be entered, how recommendations are validated against its own policies, which integrations are included, how adoption is measured and when labor savings are expected to appear.

Parity is a small private company in Rockville, Maryland. Public company records supplied for this profile list four employees and $100,000 in debt financing in 2023; LinkedIn places the team in the two-to-ten range. Revenue, valuation, pricing and a complete customer list are not public. Those limits make the company easier to understand, not less interesting. Parity is not winning with a giant dataset or a sprawling suite. Its argument is that a carefully designed measure, placed inside the right decision, can expose both understaffing and wasted labor.

The founding result remains the cleanest summary. Morin was asked to accept an external productivity answer. She measured the unit differently, found a 9.6-FTE deficit and made the finding legible to finance. The spreadsheet did not settle every question. It changed which questions the hospital could ask. Parity’s business is turning that change of mind into a repeatable operating system.