The role of digital technology in surgical home hospital programs

Abstract

Home hospital (HH), a care delivery model of providing hospital-grade care to patients in their homes, has become increasingly common in medical settings, though surgical uptake has been limited. HH programs have been shown to be safe and effective in a variety of medical contexts, with increased usage of this care pathway during the COVID-19 pandemic. Though surgical patients have unique clinical considerations, surgical Home Hospital (SHH) programs may have important benefits for this population. Various technologies exist for the delivery of hospital care in the home, such as clinical risk prediction models and remote patient monitoring platforms. Here, we use institutional experiences at Brigham and Women’s Hospital (BWH) to discuss the utility of technology in enabling SHH programs and highlight current limitations. Additionally, we comment on the importance of data interoperability, access for all patients, and clinical workflow design in successfully implementing SHH programs.

The digital transformation of surgery

“…Another study shows that the use of a non-contact video camera to monitor vital signs can be used to track early signs of physiological deterioration, to function as a less disruptive, more efficient, early warning system 20 . These new capabilities may enable an eventual shift in the nucleus of post-surgical care from the hospital back to the home; some large academic medical centers have already established successful digital technology-enabled surgical home hospital programs that allow patients to be safely recover from surgery in their own home 21 .…”

“…For example, few studies have shown any improvement in care when AI-enabled decision support tools are used 29 . Some important barriers to clinical impact include translating ML model outputs into clinically actionable insights and incorporating them into existing workflows and clinical decision making processes 15 , 21 , 30 . Additionally, these new technologies must be built and rigorously evaluated in a way that is reproducible, transparent, and interpretable to users to earn their trust 30 , 31 .…”