COST-EFFECTIVENESS OF AN AUTOMATED DELIVERY ROBOT PROGRAM TO REDUCE NURSING TRANSPORT BURDEN IN AN INTENSIVE CARE UNIT: A HOSPITAL-PROVIDER PERSPECTIVE
Author(s)
Ting-Yi Lu, M.S.1, Hui-Chu Lang, MPH, PhD1, Shu-Ling Eng2;
1National Yang Ming Chiao Tung University, Taipei, Taiwan, 2Taipei Veterans General Hospital, Taiwan
1National Yang Ming Chiao Tung University, Taipei, Taiwan, 2Taipei Veterans General Hospital, Taiwan
OBJECTIVES: Nursing workload related to intra-hospital logistics (e.g., transporting linens, medications, and consumables) contributes to inefficiency and staff burden in intensive care units (ICUs). Although automated delivery robots have been introduced to reduce non-value-added transport activities, their economic value in Taiwanese hospitals remains unclear. This study evaluated the cost-effectiveness of implementing an automated delivery robot program for routine supply transport in an ICU from a hospital perspective.
METHODS: A cost-effectiveness analysis was conducted in the ICU of a tertiary medical center in Taiwan comparing usual care (manual transport by nurses) with a robot-assisted logistics model. Time-and-motion observations and robot task logs were used to estimate daily transport time and task volume. Costs included capital acquisition and system integration, training, maintenance and software, and electricity. The primary outcome was nursing hours saved, and cost-effectiveness was expressed as the incremental cost per nursing hour saved. Annualized costs were calculated assuming a seven-year equipment lifespan and a 3% discount rate. One-way and probabilistic sensitivity analyses were performed.
RESULTS: Compared to usual care, the implementation of the automated delivery robot under a zone-based deployment model reduced nurses’ active logistics time from 111.34 to 20.43 minutes per day (81.6% reduction), corresponding to approximately 553 nursing hours released annually. Daily walking distance decreased by 1,505 meters. From the hospital perspective, the annualized program cost was NT$ 1.65 million. The resulting incremental cost-effectiveness ratio (ICER) was NT$ 2,984 per nursing hour saved.
CONCLUSIONS: In a real-world ICU setting, the automated delivery robot program substantially reduced nursing transport workload and physical burden. Although the cost per nursing hour saved exceeded prevailing wage rates, the intervention may support more efficient allocation of nursing time toward direct patient care and improve workforce sustainability.
METHODS: A cost-effectiveness analysis was conducted in the ICU of a tertiary medical center in Taiwan comparing usual care (manual transport by nurses) with a robot-assisted logistics model. Time-and-motion observations and robot task logs were used to estimate daily transport time and task volume. Costs included capital acquisition and system integration, training, maintenance and software, and electricity. The primary outcome was nursing hours saved, and cost-effectiveness was expressed as the incremental cost per nursing hour saved. Annualized costs were calculated assuming a seven-year equipment lifespan and a 3% discount rate. One-way and probabilistic sensitivity analyses were performed.
RESULTS: Compared to usual care, the implementation of the automated delivery robot under a zone-based deployment model reduced nurses’ active logistics time from 111.34 to 20.43 minutes per day (81.6% reduction), corresponding to approximately 553 nursing hours released annually. Daily walking distance decreased by 1,505 meters. From the hospital perspective, the annualized program cost was NT$ 1.65 million. The resulting incremental cost-effectiveness ratio (ICER) was NT$ 2,984 per nursing hour saved.
CONCLUSIONS: In a real-world ICU setting, the automated delivery robot program substantially reduced nursing transport workload and physical burden. Although the cost per nursing hour saved exceeded prevailing wage rates, the intervention may support more efficient allocation of nursing time toward direct patient care and improve workforce sustainability.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
EE102
Topic
Economic Evaluation
Disease
No Additional Disease & Conditions/Specialized Treatment Areas