Revolutionized patient discharge flow with Gen AI-powered task monitoring

Introduction

A leading healthcare system partnered with CitiusTech to tackle delays in patient discharge from ICUs and Step-down units. The goal was to use Gen AI to evaluate sparse clinical notes and identify missed tasks, each of which could delay discharge by 8 hours. The solution significantly boosted care team efficiency and paved the way for automated discharge summaries.

The Challenges
Every missed task costs time and capacity

Delayed discharges: Missed or undocumented tasks in discharge flows led to a median delay of 8 hours per patient.
Sparse clinical notes: The lack of structured task indicators in documentation made automated tracking difficult.
Reliability requirement: The solution needed high precision (F1 > 0.8) to ensure clinical trust.
Workflow integration: It had to blend seamlessly into existing systems without disrupting clinician routines.

The Solution
Gen AI-driven task detection, built to scale and explain

Developed a lightweight, explainable multi-agent system powered by Gen AI to evaluate clinical documentation and detect missed tasks. Key innovations included:

Light multi-agent algorithm: Custom-built agents for documentation evaluation with reliable output control and explainability.
Synthetic data generation: Created to overcome the lack of labeled datasets for training and validation.
Parallelized processing: Allowed for high patient volumes without escalating costs.
Explainability layer: Built-in transparency to improve clinical adoption and confidence.
Foundation for discharge summary automation: Structured data output enabled the next phase of smart discharge planning.

Business Outcomes
From fragmented flows to frictionless discharges

8 Hours saved per caught task	Helped clinicians proactively manage and accelerate discharges.
0.92 F1 score achieved	Surpassed performance targets, ensuring reliable decision support.
12x Increase in labeled data output	Synthetic data generation significantly expanded training data, enhancing model accuracy and robustness.
1,000 Tasks analyzed per million tokens	Delivered highly efficient, cost-effective throughput.
Clinician feedback	“The AI-generated notes were too clean” proof of strong language modeling and documentation clarity.

Precision matters, but so does clinical trust

Combining synthetic data generation with a human-in-the-loop feedback loop ensures accuracy without losing context.
Transparent outputs and explainability build clinician trust even when automation “writes too well.”
Embedding Gen AI into discharge workflows requires balance between automation and user control.

Reimagine Discharge Management with Gen AI

Explore how leading hospitals are saving hours per patient using Gen AI-enabled task evaluation.

Power intelligent care journeys