Impact of postoperative in-hospital continuous vital sign monitoring on healthcare costs, resource utilization and labor market outcomes

Continuous vital signs monitoring (CVSM) is increasingly being used for early complication detection in general wards, potentially reducing prolonged medical care and healthcare utilization. However, its impact on health economic outcomes, including post-discharge trajectories, remains largely unexplored. This study aimed to estimate the impact on healthcare costs, resource utilization and labor market outcomes of patients included in a postoperative randomized clinical trial (RCT) of an artificial intelligence (AI)-assisted CVSM. The WARD Surgical RCT (Clinicaltrials.gov Identifier: NCT04640415) randomized participants to monitoring by AI-assisted CVSM with real-time alerts or blinded monitoring. In this study, Generalized Linear Models and Two-part models were used to estimate the impact on healthcare costs and resource utilization across primary and secondary care, including home care, home nursing and prescription medication. Additionally, the impact on employment status, full-time employment duration and sickness leave duration were examined. The study included 382 trial participants traceable in the Danish national registries. No differences in total healthcare costs were found between the groups (EUR 21,184 vs EUR 20,621, p = 0.58 at 30 days and EUR 40,505 vs EUR 40,870, p = 0.81 at 1 year). After adjustment, the intervention group had a reduction of 2.4 weeks (95%CI (-4.5;-0.3)) on sickness leave within 3 months. No other statistically significant differences were observed. There was no statistically significant impact of AI-assisted CVSM on total healthcare costs, resource utilization, employment status or duration of full-time employment compared to blinded monitoring. Monitoring was associated with shorter duration of sickness leave within 3 months. This reduction, even if modest, may yield broader societal benefits by supporting workforce participation and reducing productivity loss.