Common questions
When we work with finance teams, these are the questions that come up most
Doesn't a vacancy reduce payroll costs and improve the P&L?
In the short run it does reduce payroll, and the calculator accounts for that directly. Open Show the math and you'll see a net-of-payroll line: revenue protected minus the loaded salary that would have been paid during the days saved (base × 1.31 for benefits, per BLS employer-cost data3). Because hospital labor runs ~45-55% of revenue,5 each clinical payroll dollar supports roughly $2-3 of revenue, so the net impact of filling faster remains strongly positive even after adding the payroll back.
Don't other staff absorb the workload during a vacancy?
Partially, yes, which is why no formula here assumes 100% loss. Every revenue line is multiplied by a capture rate (75% conservative, 90% expected for capacity roles). Bedside nursing is one of the truest capacity constraints in any industry: staffing ratios are often regulatory, so an unstaffed position frequently means a bed that cannot be filled. Coverage that does happen, overtime, floating, travel staff, is counted as cost in the hard-dollar line instead. The two lines never double-count.
Can travel nurses cover the gap?
They can maintain capacity, at a documented premium, and that premium is exactly what the hard-cost line measures. The all-in travel RN rate runs about $91/hour versus $59/hour for employed staff,1 roughly a $66K annual premium per covered seat. There is also a second-order effect NSI documents: sustained reliance on premium labor correlates with higher staff turnover (17.6% nationally, costing the average hospital $5.19M/year1), which in turn creates the next vacancy. Faster permanent fills reduce both the premium and the cycle.
How is the 3× salary multiplier derived?
It's derived, not asserted, two independent ways that agree. Top-down: hospital labor cost runs ~45-55% of revenue,5 so each loaded payroll dollar must support ~$2+ of revenue by arithmetic; clinical roles run above that average because administrative payroll dilutes it. Bottom-up: large-system revenue per employee (~$275K from public filings) against the BLS mean RN base wage (~$86K3) gives ~3.2×. We default to 3× and make it fully overridable. Your finance team can reproduce both derivations from your own cost reports, and we encourage exactly that.
Does revenue per employee overstate the value of a single role?
For support roles, it can, which is why this calculator only models revenue-critical clinical positions, never administrative headcount. For bedside roles we set the average aside entirely and use direct capacity math (bed-days × net revenue per bed-day4). The multiplier path exists only for clinical roles without a clean bed-revenue line, and it's deliberately set below what the top-down derivation would justify.
How does new-hire ramp time affect these estimates?
Ramp time strengthens the case rather than weakening it. The days a faster process saves come off the fully-productive end of the timeline, not the orientation period: orientation costs the same whether it starts in March or May, but every week of hiring delay is a week of fully-ramped capacity lost at the back end. Because effective vacancy equals days open plus ramp drag, a model that ignores ramp, as this one conservatively does, understates the true cost of slow hiring.
How reliable is the 30-50% time-to-fill improvement?
The estimate is designed not to depend on taking it on faith. The default is 30%, below hireEZ's measured customer benchmark of 50% time-to-fill reduction6, so the output is built on a discounted figure from the start. Set it to whatever your team believes is achievable; even a 15% improvement produces a seven-figure result for most systems carrying the national-average vacancy load. And when you're ready, the platform's analytics layer computes this from your actual ATS data instead of benchmarks, removing the assumption entirely.
