A Cost Evaluation of COVID-19 Remote Home Monitoring Services in England

Remote home monitoring services emerged as critical components of health care delivery from NHS England during the COVID-19 pandemic, aiming to provide timely interventions and reduce health care system burden. Two types of service were offered: referral by community health services to home-based care to ensure the right people were admitted to the hospital at the right time (called COVID Oximetry@home, CO@h); and referral by hospital to support patients’ transition from hospital to home (called COVID-19 Virtual Ward, CVW). The information collected for the oxygen levels and other symptoms was provided via digital means (technology-enabled) or over the phone (analogue-only submission mode). This study aimed to evaluate the costs of implementing remote home monitoring for COVID-19 patients across 26 sites in England during wave 2 of the pandemic. Understanding the operational and financial implications of these services from the NHS perspective is essential for effective resource allocation and service planning. We used a bottom-up costing approach at the intervention level to describe the costs of setting up and running the services. Twenty-six implementation sites reported the numbers of patients and staff involved in the service and other resources used. Descriptive statistics and multivariable regression analysis were used to assess cost variations and quantify the relationship between the number of users and costs while adjusting for other service characteristics. The mean cost per patient monitored was lower in the CO@h service compared with the CVW service (£527 vs £599). The mean cost per patient was lower for implementation sites using technology-enabled and analogue data submission modes compared with implementation sites using analogue-only modes for both CO@h (£515 vs £561) and CVW (£584 vs £612) services. The number of patients enrolled in the services and the service type significantly affected the mean cost per patient. Our analysis provides a framework for evaluating the costs of similar services in the future and shows that the implementation of these services benefit from the employment of tech-enabled data submission modes.