Background

Accurate urine output monitoring remains one of the fundamental parameters in assessing renal function and fluid balance in critically ill patients.

In many ICUs, however, the process still relies on manual measurement and documentation, which introduces variability and potential inaccuracy.

At our 6-bed cardiac intensive care unit, this routine task consumed substantial nursing time and occasionally resulted in double-counted or missed values, particularly during high workload periods.

To address these challenges, we implemented HTG Urogram, an automated urine output monitoring system that measures diuresis continuously in five-minute intervals and transmits data wirelessly to a central web interface.

Implementation

A three-week evaluation period was conducted across all six beds.

Device installation required no modification of existing urinary drainage systems, and staff training was completed in under 60 minutes.

Continuous data collection was achieved without workflow disruption or additional infrastructure demands.

Findings

• Data accuracy: measurement error reduced from an estimated 20 % to below 3 %, with complete elimination of duplicate hourly recordings.

• Clinical responsiveness: real-time visualization of diuresis allowed earlier assessment of therapeutic effects of diuretics and vasoactive drugs, without waiting for manual datapoints.

• Operational benefit: average nursing time savings of ~25 minutes per 12-hour shift and reduced cognitive load in fluid balance monitoring.

• Adoption: rapid staff acceptance, no reported interference with patient care or device-related complications.

Conclusion

The introduction of HTG Urogram demonstrated that automated urine output monitoring can be safely integrated into intensive care workflows, improving both data fidelity and the timeliness of clinical decisions.

The system enhances nursing efficiency, reduces human error, and provides physicians with more reliable datasets for assessing renal perfusion and fluid therapy outcomes.

From a clinical leadership perspective, it represents a pragmatic, evidence-based advance toward digitalized critical care monitoring.