a tertiary hospital intensive care unit in Taiwan
A Tertiary Hospital ICU in Taiwan Cuts Nurse Logistics Time 81.6%
A tertiary hospital ICU in Taiwan moved nurse transport runs to delivery robots. Daily active logistics time fell 81.6%, from 111.34 to 20.43 minutes.
Deployment at a glance
- 81.6%
- Cut in nurses' daily active logistics time
- 20.43 min
- Daily active logistics time afterward, from 111.34
- 1,505 m
- Less daily walking distance for nurses
- 553 hrs
- Nursing hours released per year, annualized
Based on a documented real-world deployment. Figures are from public reporting; the organization is not named.
Nursing minutes lost to corridor runs
In a tertiary hospital intensive care unit in Taiwan, transport work ran through the whole shift. Each trip pulled a nurse away from the bedside, and each walk added up across a day of tightly timed clinical care.
The hard part was measurement. Transport tends to sit in the gaps between bedside tasks, so it rarely shows up in staffing plans built around patient hours. Until the minutes were counted, the cost of that walking stayed largely invisible.
That invisibility is what made the case worth studying. A unit that cannot see how much nursing time goes to logistics cannot judge whether a delivery robot would return that time to patients.
Routing transport to a robot delivery program
The hospital moved a share of routine ICU transport from nurses to a robot-assisted logistics model. The robot maker is left unnamed here, since the lessons sit in how the workflow changed rather than in the hardware.
Two measurement tools tracked the change. Time-and-motion observation recorded how nurses spent their active logistics minutes, and robot task logs supplied timings from the robot side. Pairing a human view with machine records gave a before and after picture that did not rely on memory.
Deployments like this tend to go well when the team fixes the run types before go-live, checks routes against real corridors and elevators, and briefs staff on how to request and receive a robot delivery. Those steps are general practice, and they are the ones a US hospital team would plan for first.
- Map the transport runs that take the most nursing minutes
- Define which items and destinations the robot will serve
- Observe nurses before go-live to set a clear baseline
- Log every robot task so each delivery has a timestamp
- Repeat the same observation after go-live on the same measures
Active logistics time and walking fell
Nurses' daily active logistics time fell from 111.34 minutes to 20.43 minutes, an 81.6% reduction. That leaves about 91 minutes a day that had been spent on transport and went back to nursing work.
Daily walking distance fell by 1,505 meters. Annualized, the program released about 553 nursing hours per year. Against that gain, the program cost was annualized at NT$1.65 million from the hospital's perspective.
Expressed per unit of time, the cost came to NT$2,984 per nursing hour saved. That figure exceeded prevailing wage levels, and the team behind the evaluation argues the value lies in moving nursing time back to direct patient care rather than in a wage comparison. The cost estimates were annualized over a 7-year equipment life at a 3% discount rate and tested with one-way and probabilistic sensitivity analyses.
What this means for US hospital teams
The clinical lesson is about where nursing minutes go, and that question applies on any floor. Service Robot Co. is an OEM-neutral commercial robot integrator for US businesses. We select the right robots across manufacturers, then lease, deploy, integrate, train and service every unit through a nationwide US engineer network, a turnkey robot deployment with one partner for the whole lifecycle.
Our offer is a 3-year lease with one fixed lease payment quoted after a site assessment. Teams that want to test the workflow can begin with one leased unit as a robot pilot program, and widen the fleet only after their own timing data shows the change. That is where most robot leasing for business conversations start: which routes, which items and which floor.
Treat any outcome from another site as a question to test, not a promise for your floor. Measure your baseline first, because routes, elevators and run types vary from floor to floor.
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