Estimation of the maximum potential cost saving from reducing serious adverse events in hospitalized patients.

Purpose: The increasing use of advanced medical technologies to detect adverse events, for instance, artificial intelligence-assisted technologies, has shown promise in improving various aspects within health care but may also come with substantial expenses. Therefore, understanding the potential economic benefits can guide decision-making processes regarding implementation. We aimed to estimate the potential cost savings associated with reducing length of stay and avoiding readmissions within the framework of an artificial intelligence-assisted vital signs monitoring system.

Methods: We used data from Danish national registries and coarsened exact matching to estimate the difference in length of stay and probability of readmission among adult in-hospital patients exposed to and not exposed to serious adverse events. We used these estimates to calculate the maximum potential savings that could be achieved by early detection of adverse events to reduce length of stay and avoid readmissions.

Results: Patients exposed to serious adverse events during admission had 2.4 (95% CI: 2.4-2.5) additional hospital bed days and had 14% (95% CI 11%-17%) higher odds of readmissions compared with patients not exposed to such events. A base case scenario yielded maximum potential savings if one patient avoided a serious adverse event of EUR 2040 due to reduced length of stay and EUR 43 due to avoidance of readmissions caused by serious adverse events.

Conclusion: Reductions in serious adverse events are associated with decreased healthcare costs due to reduced length of stay and avoided readmissions. Artificial intelligence-assisted vital signs monitoring systems are one potential approach to reduce serious adverse events, however, the ability of this technology to reduce adverse events remains unclear. Comprehensive prospective analyses of such systems including the intervention and implementation costs are necessary to understand their full economic impact.