The I/T/O Model and Four Eras of ED Innovation

Emergency department patient flow optimization addresses the full continuum from patient arrival through triage, treatment, disposition, and discharge or admission. The field is organized around three principal intervention layers — input management (controlling who enters and when), throughput management (accelerating in-department processes), and output management (expediting admission or discharge) — a framework known as the Input/Throughput/Output (I/T/O) model and described in a 2024 umbrella review of solutions and challenges across the health system.

Within the dataset of 70+ retrieved records, four distinguishable eras of innovation emerge between 2005 and 2026. The foundational era (2005–2011) established the core concept of a real-time quantitative crowding index through the earliest patent in this dataset — filed by Steven L. Bernstein in the US in 2005 — and produced the first systematic reviews of triage interventions and early crowdinforming simulation experiments. The development cluster (2012–2018) saw rapid proliferation of discrete event simulation and agent-based modeling studies across Denmark, Portugal, Iran, Australia, the UK, and North America, alongside the first interactive ED dashboard patent from Cerner Innovation (2015) and the first predictive bottleneck remediation patent from Jeffrey Randall Dreyer (2018).

The applied integration era (2019–2022) shifted innovation toward hybrid methods combining simulation with machine learning, real-time data stream integration, and COVID-19-driven process redesign. The frontier era (2024–2026) is defined by a qualitative leap: the arrival of LLM multi-agent architectures for full patient flow management, represented by two filings from Sheba Impact Ltd. (WO, 2025; US, 2026), and by the incorporation of external contextual data — environmental conditions, seasonal trends, and public events — into ML-based congestion forecasting, as in SR University’s pending Indian patent (2026).

Simulation Methodologies: From Discrete Event Models to Digital Twins

Discrete Event Simulation (DES) is the dominant quantitative methodology for ED patient flow analysis in this dataset, appearing across studies from Portugal, Jordan, Italy, Iran, Denmark, Australia, and Switzerland. DES models patient pathways as sequences of probabilistic events — arrivals, triage, diagnostics, treatment, discharge — enabling “what-if” scenario testing without real-world disruption.

The methodological richness of DES applications in this dataset is notable. Studies have combined DES with Artificial Neural Networks (ANN) and Genetic Algorithms (GA) to minimize waiting time and unit engagement; with Six Sigma’s DMAIC methodology to achieve documented cycle time reductions; with RFID-based real-time tracking; and with agent and room archetypes validated against Smart Crowding data during COVID-19 pandemic conditions. According to WHO health systems research standards, such multi-method validation is a hallmark of mature operational research.

Agent-Based Modeling (ABM) complements DES by simulating the individual-level behaviors of patients, nurses, physicians, and equipment as autonomous agents, capturing emergent system behaviors that DES cannot represent. A 2017 study demonstrated staff agents participating in dynamic resource reallocation decisions, modeling cooperative behavior. The most significant ABM development in the dataset is the 2023 three-mode digital twin architecture: Digital Shadow (real-time monitoring), Synchronised DT (predictive simulation), and Exploratory DT (Monte Carlo scenario exploration). This convergence of ABM, real-time data synchronization, and scenario analysis represents a direction expected to accelerate as EHR integration matures.

“Digital twin architectures operate in three modes — real-time monitoring, predictive simulation, and Monte Carlo scenario exploration — converging ABM, data synchronization, and prospective planning in a single operational framework.”

A methodologically distinct signal in the dataset is the application of time-varying graphs (TVG) stored in Neo4j graph databases to reveal temporal congestion patterns and periodic resource constraints invisible to traditional relational database analysis. This graph network approach (2022) represents a meaningful potential advance for real-time operational intelligence systems.

AI, Predictive Analytics, and the LLM Multi-Agent Frontier

The AI and machine learning cluster in this dataset encompasses patented and published systems that apply predictive analytics, neural networks, and — most recently — large language models to anticipate congestion, score acuity, allocate resources, and dynamically manage workflow. This cluster has the steepest innovation gradient in the dataset, with the most disruptive entries appearing in 2025–2026.

The trajectory begins with UBQ, Inc.’s 2019 US patent, which introduced an ML module that generates calculated acuity scores and workload predictions, then assigns predicted tasks to work queues. Koninklijke Philips N.V.’s 2024 US filing advanced this approach with a trained workflow delay prediction algorithm that analyses patient, resource, and flow data to surface predicted delays via a graphical user interface. Both of these filings are categorised as inactive in the dataset, underscoring the pace of obsolescence in this space.

SR University’s 2026 pending Indian patent introduces a dimension absent from earlier filings: the incorporation of environmental conditions, seasonal trends, and public events into ML-based congestion forecasting via time-series methods. This extends the input variable set well beyond traditional clinical parameters, moving toward a systems-of-systems perspective aligned with standards being discussed at organisations such as IEEE for health informatics interoperability.

The defining frontier entries are the two filings from Sheba Impact Ltd. — a WO (PCT) filing in 2025 and a US pending patent in 2026 — both describing multi-agent LLM architectures for full patient flow management. The US 2026 patent explicitly claims real-time clinical history collection, triage support, and end-to-end ED process management under stressful real-world conditions. The PCT counterpart signals international protection intent across jurisdictions beyond the US. This is a category absent from the 2018–2023 patent record, representing a qualitative discontinuity in the IP landscape that IP strategists should monitor for continuation filings, claim scope, and licensing activity in 2026–2027.

Automatic push notification systems represent a patient-facing AI application distinct from clinician-directed tools. A 2021 prospective cohort study from Israel demonstrated that automated SMS-based notifications improved patient navigation and reduced length of stay — pointing toward patient-facing digital engagement as an underexplored optimization lever that complements clinician-directed AI systems.

Real-Time Dashboards and Clinical Decision Support: Evidence and IP

Real-time dashboard and clinical decision support systems present ED status, bottlenecks, and performance metrics to clinical staff, enabling immediate operational decisions. This cluster spans both patented software platforms and literature-documented digital tools, and is the segment with the strongest documented IP concentration in this dataset.

The evidence base for dashboard interventions includes a 2016 simulation study showing a 34–44% LOS reduction potential with an operational BI dashboard, and a physician-in-triage (PIT) simulation from Canada showing a 34% LOS reduction and a 49% reduction in wait-to-be-seen time. Telemedicine-enabled approaches, including telehealth dashboards for high-acuity patient awareness across an enterprise practice (documented in a 2019 paper) and drive-through pandemic care systems (2021), have further expanded the application scope of real-time clinical support tools, as tracked by health systems bodies including WHO.

On the IP side, Cerner Innovation, Inc. holds 4 active US patents in this cluster — filed in 2015, 2020, 2020, and 2023 — covering centralized interactive ED display systems showing patient summaries, performance metrics, and segmentable patient views. This consistent continuation strategy from 2015 to 2023 creates a meaningful barrier for new entrants seeking to commercialize centralized ED display and performance monitoring systems in the US market. Jeffrey Randall Dreyer holds 2 active US patents (2018 and 2020) covering a graphical interface with triage region, bed status region, and patient arrival/acuity surge regions integrated with prescriptive alerts.

Patent Assignees, Jurisdictions, and Geographic White Space

Among the 12 patents with identified assignees in this dataset, the distribution reveals a highly concentrated IP landscape dominated by US-based entities, with a single emerging entrant from Israel and one from India representing the frontier of international expansion.

The jurisdiction analysis within this dataset reveals that 10 of 12 patent filings are in the US, with 1 PCT filing from Sheba Impact Ltd. (WO, 2025) and 1 pending filing from SR University (India, 2026). The literature geography is substantially broader: studies span Canada, the UK, Netherlands, Switzerland, Denmark, Portugal, Iran, Israel, Australia, Jordan, Germany, Japan, and the US, indicating a globally distributed research effort with no single dominant country. UK NHS-context studies are notably prolific, reflecting the sustained pressure of the 4-hour performance target mandated by national policy.

A strategically significant observation is the absence of patent activity from jurisdictions with active research communities. Iran, Jordan, Australia, and Scandinavia have each produced multiple published simulation and process improvement studies in this dataset, yet none have generated corresponding patent filings. This gap between research output and IP protection suggests potential first-mover opportunities for organisations willing to file in these geographies, consistent with patent strategy guidance from bodies such as WIPO on emerging market IP positioning.

Strategic Implications for R&D and IP Teams in 2026

Six strategic implications emerge from this technology landscape for R&D leaders, IP strategists, and clinical technology teams working in the ED patient flow domain.

1. LLM and generative AI integration is the defining frontier of ED flow IP

The Sheba Impact Ltd. patent family (WO 2025, US 2026) is the first credible commercial-grade attempt to operationalize multi-agent LLM systems for end-to-end ED management. R&D teams should monitor this assignee and PCT family for claim scope, continuation filings, and licensing activity through 2026–2027.

2. Cerner Innovation holds the dominant active patent position in real-time dashboards

With 4 active US patents and a consistent continuation strategy from 2015 to 2023, Cerner’s IP creates a meaningful barrier for new entrants seeking to commercialize centralized ED display and performance monitoring systems. Product developers should conduct a freedom-to-operate analysis against this family before entering the US market.

3. DES and hybrid simulation are approaching saturation

DES-based publications span 2009–2023 across dozens of countries in this dataset. The methodological diversity — DES+ANN+GA, DES+DMAIC, DES+RFID, hybrid ABM+DES+SD — signals methodological maturity. Value creation has shifted from modeling methodology to real-time deployment and AI-driven automation.

4. Geographic white space exists outside the US and Europe

Only one patent filing in this dataset originates outside the US or Israel. The extensive literature from Iran, Jordan, Australia, and Scandinavia has not generated corresponding patent activity, suggesting potential first-mover IP opportunities in these geographies.

5. Pandemic resilience has permanently expanded the application scope

COVID-19 research (2020–2022) established telemedicine-enabled alternative care areas, dynamic patient flow countermeasures, and big data pandemic operations modeling — validated across 238,152 patients in one study — as durable ED optimization methods. Future ED flow systems should incorporate surge scenario planning and external contextual data as baseline requirements.

6. Patient-facing digital engagement is an underexplored lever

The 2021 prospective cohort study from Israel on automated SMS-based push notifications demonstrated measurable improvements in patient navigation and LOS reduction. This patient-facing dimension remains underrepresented in the patent record, representing an accessible area for innovation that does not conflict with existing IP concentration in clinician-directed dashboards.

“Geographic white space is the most actionable near-term IP opportunity in ED flow optimization: Australia, Scandinavia, Iran, and Jordan have produced significant published research with no corresponding patent activity.”