HealthcareTime-SeriesEmerging Standard

Decision IQ – AI-Powered Patient Throughput Solution

This is like an air-traffic control tower for hospitals that uses AI to watch every bed, patient movement, and bottleneck in real time, then recommends what to do next so patients don’t sit waiting in hallways or ERs.

9.0
Quality
Score

Executive Brief

Business Problem Solved

Hospitals struggle with clogged patient flow—long ER wait times, slow admissions from the ED, delayed discharges, and poor bed utilization—because staff have to manually coordinate complex logistics across departments.

Value Drivers

Reduced length of stay by improving bed assignment and discharge coordinationLower ED boarding and diversion through better capacity forecastingImproved staff productivity by automating situational awareness and recommendationsHigher revenue capture via increased patient throughput and reduced avoidable idle capacityBetter patient experience and quality metrics (e.g., LWBS, time-to-bed)

Strategic Moat

Tight embedding into hospital operations and TeleTracking’s existing bed management and capacity management workflows, combined with proprietary operational and throughput data from client hospitals.

Technical Analysis

Model Strategy

Hybrid

Data Strategy

Time-Series DB

Implementation Complexity

High (Custom Models/Infra)

Scalability Bottleneck

Data integration and data quality across EHRs and hospital operational systems; real-time ingestion and latency constraints for large hospital networks.

Market Signal

Adoption Stage

Early Majority

Differentiation Factor

Positions AI specifically around patient throughput and operational decision support rather than generic analytics, with a focus on real-time bed management, capacity visibility, and prescriptive recommendations for hospital flow teams.