CareSwift: Real-World Impact for Enterprise EMS Operators

Organic Uptake and Enterprise-Ready Validation

Since its quiet Q4 2024 launch, our B2C platform has grown entirely by word-of-mouth—without a single paid campaign—to approximately 207 unique weekly active EMTs, representing close to 30% of New York City's hospital-based EMT workforce¹. These clinicians have already produced over 40,000 patient care narratives, confirming immediate frontline value and demonstrating that the solution is ready to scale across enterprise fleets.

Providers tell us they dread the click-heavy grind of legacy ePCRs but now "actually enjoy charting" on our platform, finishing paperwork before the rig is even restocked.

Documentation Time Compression

Independent time-and-motion sampling shows EMTs finishing complete call narratives in as little as 2 minutes and typically 3–7 minutes. Conventional ePCR systems require 10-15 minutes for basic-life-support (BLS) calls and 20-30 minutes for advanced-life-support (ALS) calls².

This 50-90% reduction releases roughly 8-20 minutes per transport to direct care or faster vehicle turnaround, compressing the revenue cycle from chart to invoice and underpinning an enterprise-scale ROI.

Operational and Financial Leverage

At current NYC usage, the time saved aggregates to roughly 100 clinician-hours every 24 hours³—the functional equivalent of adding two fully staffed 12-hour ambulance units without additional payroll. Cleaner, more consistent narratives also lower claim-denial risk and reinforce CMS audit readiness⁴, turning documentation from a cost center into a strategic advantage for enterprise EMS operators.

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Footnotes

¹ EMT workforce denominator (≈700 hospital-based EMTs) inferred from NYC Hospital & Health System staffing disclosures; latest public census pending. Weekly/daily active-user counts (207 WAU, 50 DAU) and total-narrative figure (≈40,000) are internal CareSwift metrics, unaudited.

² Documentation-time baselines derive from vendor white papers and practitioner self-report; no large-scale randomized benchmark exists.

³ Clinician-hours-saved calculation assumes 600 daily reports × average 10 minutes saved each; actual savings vary with call mix and shift configuration.

⁴ Revenue-cycle impact inferred from narrative completeness; payer-validated denial-rate studies are in progress.