Flow Trace
See what's blocking patient flow, and what's next.
Patient flow through a hospital depends on dozens of handoffs across departments: bed assignment, diagnostics, specialists, discharge planning, and more. When one of those dependencies stalls, the delay is rarely visible until it has already cascaded into a backed-up ED, a held OR block, or a patient waiting far longer than they should.
Flow Trace maps those dependencies across departments in real time, identifying what is actually preventing a patient from moving through care, why the delay is occurring, and what needs to happen next to resolve it. Bottlenecks get flagged before they cascade into the rest of the hospital, not after.
In practice, that means hospital operations and care teams get a clear, current view of where flow is breaking down and why, instead of piecing it together after the fact. It's built to help hospitals reduce delays, recover capacity, and make better use of already-stretched critical resources.
The Problem
Patient flow depends on dependencies across departments that are rarely visible until a delay has already cascaded into backed-up beds, held procedures, or longer waits.
The Approach
Flow Trace maps those dependencies across departments in real time, identifying what's blocking flow, why, and what needs to happen next, so hospitals can catch bottlenecks before they cascade.
U.S. hospitals, more than 35 million annual admissions, and over 907,000 staffed beds - the scale of the underlying operational system
Verified· American Hospital Association, 2026health systems and 600 hospitals reported in LeanTaaS's published deployment materials for inpatient flow
Verified· LeanTaaS, 2026U.S. hospitals
Verified· American Hospital Association, 2026U.S. community hospitals (initial addressable segment)
Verified· American Hospital Association, 2026Qventus
AI inpatient-capacity platform
- discharge-barrier identification
- care-gap orchestration
- ancillary-service prioritization
- discharge prediction
- EHR integration
Overlap: AI-driven capacity intelligence and discharge prediction - probably the closest direct benchmark
Differentiation: Qventus already answers "what is happening" well; Flow Trace's angle is the causal chain underneath it - which specific dependency is blocking this patient and who owns resolving it.
LeanTaaS (iQueue for Inpatient Flow)
Predictive/prescriptive capacity analytics
- admissions/transfers/discharges forecasting
- capacity analytics
- bottleneck forecasting
- workflow coordination
Overlap: Predictive capacity and bottleneck forecasting at meaningful scale
Differentiation: LeanTaaS forecasts capacity trends; Flow Trace is oriented around the individual patient's specific blocker and next action.
TeleTracking
Enterprise patient-flow & bed management
- bed management
- patient flow
- transfer-center workflows
- capacity intelligence
Overlap: Enterprise-wide operational coordination
Differentiation: TeleTracking is an established enterprise system of record for bed/transfer operations; Flow Trace is a lighter dependency-reasoning layer, not a bed-management replacement.
Why This Can Still Win
Patient-flow optimization is a proven, competitive category (Qventus, LeanTaaS, and TeleTracking all have real deployments), so Flow Trace needs a narrower thesis than generic flow optimization. That thesis is explicit causal/dependency mapping across departments: a patient-level dependency graph with blocker ownership and a recommended next action, rather than only a dashboard of what's currently happening.
Illustrative Cascadia model based on adjustable assumptions. This is not a forecast of future performance.
Downside
- MRR
- $37,500
- ARR
- $450,000
- Gross Profit
- $337,500
Base
- MRR
- $187,500
- ARR
- $2,250,000
- Gross Profit
- $1,687,500
Upside
- MRR
- $750,000
- ARR
- $9,000,000
- Gross Profit
- $6,750,000
Existing Cascadia Asset
- An existing, working codebase rather than a blank repository
- Product architecture and data model already designed
- UX/UI already designed and tested against a real workflow
- Product workflows already established, not hypothetical
- Market and competitive research already completed
- A defined brand and product identity
Start Internally
- Discovery and product strategy
- Architecture and data-model design
- UX/UI design
- Engineering across the full product surface
- Infrastructure and integrations
- Testing, security review, and deployment
- Iteration against real usage
- Market validation
Illustrative internal-build labor model
Using Cascadia’s illustrative internal development-team model (2 developers, 0.5 QA, 0.5 UX/interface design, 0.5 product/project management, U.S. Bureau of Labor Statistics national mean compensation benchmarks, plus a 30% Cascadia assumption for employer burden and overhead), a build over this venture’s typical timeline represents the following in modeled direct and burdened labor — before infrastructure, integrations, compliance, implementation, training, or support.
9-month build
~$450,000
12-month build
~$600,000
18-month build
~$900,000
Sources
- American Hospital Association, “Fast Facts on U.S. Hospitals” (2026)
- LeanTaaS, “Publicly reported deployment figures” (2026)
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Interested in Flow Trace?
Cascadia Venture Works is open to conversations regarding strategic partnerships, licensing, pilots, investment, and acquisition opportunities where appropriate.