Background and aims: Treating patients in psychiatric intensive care units (PICUs) is costly for the English National Health Service (NHS), requiring significant staff time. Oxevision, a non-contact system, providing vision-based patient monitoring and management (VBPMM) has been introduced in some NHS mental health trusts which aims to help clinicians to deliver safer and more efficient care. The objective of this early economic evaluation was to explore the impact of introducing VBPMM with standard care, versus standard care alone on health and economic outcomes in PICUs across England.
Methods: The model uses a cost calculator approach to evaluate the potential benefits of introducing VBPMM, capturing differences in observation hours and critical events such as assaults. Effectiveness data were primarily based on a 24-month observational before and after study undertaken in an NHS mental health trust using VBPMM. Outcomes reported in this study are incremental costs and reduction in clinical events presented as per occupied bed days, per patient, per average ward, and for the English NHS overall. Scenario analysis was conducted to test the uncertainty of results using statistical significance of key inputs.
Results and conclusions: The analysis indicates that introducing VBPMM may be cost saving compared with standard care alone. The biggest driver of estimated cost savings was from the potential reduction in one to one observation hours, which may have significant impact in PICUs. Limitations of the analysis include the single center data underpinning the analysis and assumptions made about transferability of clinical data to different sized wards. Scenario analysis was conducted, and the results were robust to statistically significant changes in input parameters. This study suggests that introducing VBPMM on PICUs has the potential to reduce costs and improve efficiency of resource allocation, but results should be confirmed with additional clinical study evidence.
Keywords: I; I1; I10; I13; NHS; PICU; digital health; economic analysis; health economics; mental health.