A Digital Respiratory Ward in Leicester, Leicestershire, and Rutland, England, for Patients With COVID-19: Economic Evaluation of the Impact on Acute Capacity and Wider National Health Service Resource Use

Abstract

Background: The COVID-19 pandemic stressed global health care systems' acute capacity and caused a diversion of resources from elective care to the treatment of acute respiratory disease. In preparing for a second wave of COVID-19 infections, England's National Health Service (NHS) in Leicester, Leicestershire, and Rutland sought to protect acute capacity in the winter of 2020-2021. Their plans included the introduction of a digital ward where patients were discharged home early and supported remotely by community-based respiratory specialists, who were informed about patient health status by a digital patient monitoring system.

Objective: The objective of the digital ward was to maintain acute capacity through safe, early discharge of patients with COVID-19 respiratory disease. The study objective was to establish what impact this digital ward had on overall NHS resource use.

Methods: There were no expected differences in patient outcomes. A cost minimization was performed to demonstrate the impact on the NHS resource use from discharging patients into a digital COVID-19 respiratory ward, compared to acute care length of stay (LOS). This evaluation included all 310 patients enrolled in the service from November 2020 (service commencement) to November 2021. Two primary methods, along with sensitivity analyses, were used to help overcome the uncertainty associated with the estimated comparators for the observational data on COVID-19 respiratory acute LOS, compared with the actual LOS of the 279 (90%) patients who were not discharged on oxygen nor were in critical care. Historic comparative LOS and an ordinary least squares model based on local monthly COVID-19 respiratory median LOS were used as comparators. Actual comparator data were sourced for the 31 (10%) patients who were discharged home and into the digital ward for oxygen weaning. Resource use associated with delivering care in the digital ward was sourced from the digital system and respiratory specialists.

Results: In the base case, the digital ward delivered estimated health care system savings of 846.5 bed-days and US $504,197 in net financial savings across the 2 key groups of patients-those on oxygen and those not on oxygen at acute discharge (both P<.001). The mean gross and net savings per patient were US $1850 and US $1626 in the base case, respectively, without including any savings associated with a potential reduction in readmissions. The 30-day readmission rate was 2.9%, which was below comparative data. The mean cost of the intervention was US $223.53 per patient, 12.1% of the estimated gross savings. It was not until the costs were increased and the effect reduced simultaneously by 78.4% in the sensitivity analysis that the intervention was no longer cost saving.

Conclusions: The digital ward delivered increased capacity and substantial financial savings and did so with a high degree of confidence, at a very low absolute and relative cost.

Keywords: Covid-19; SARS-CoV-2; cost; cost-effectiveness analysis; costs; delivery; digital technology; economic; economics; finance; finances; financial; home transition; hospital; hospital stay; hospitalization; hospitalizations; hospitals; length of stay; lung; lungs; pulmonary; remote; remote care; resource; resources; respiratory; service; services; telehealth; telemedicine; virtual care; ward; wards.

Figure 1

The relationship between median acute LOS and number of acute discharges in COVID-19 patients in UHL, March 2020-November 2021 ordinary least square model. LOS: length of stay; UHL: University Hospitals Leicester.

Figure 2

UHL and England monthly mean and median length of stay for patients with COVID-19: September 2020 to November 2021. UHL: University Hospitals Leicester.

Figure 3

Digital ward admissions and supply stressors in University Hospitals Leicester between November 2020 and November 2021: acute beds, mechanically ventilated (MV) beds, and staff absences.