Background During the SARS-CoV-2 (COVID-19) pandemic, routine antenatal care was disrupted, and pregnant women positive for COVID-19 were at increased risk of caesarean section, intensive care admission or neonatal unit admission for their baby. Virtual care and telehealth can reduce barriers to care and improve maternity outcomes, and adoption has been encouraged by health authorities in the United Kingdom. Methods Norfolk and Norwich University Hospitals Trust deployed a flexible maternity virtual ward (MVW) service using the Current Health platform to care for pregnant women during the pandemic. Patients were monitored either intermittently with finger pulse oximetry or continuously with a wearable device. We outline the MVW technology, intervention and staffing model, triage criteria and patient feedback, as an example of an operational model for other institutions. Results Between October 2021 and February 2022, 429 patients were referred, of which 228 were admitted to the MVW. Total bed-days was 1,182, mean length of stay was 6 days (SD 2.3, range 1–14 days). Fifteen (6.6%) required hospital admission and one (0.4%) critical care. There were no deaths. Feedback alluded to feelings of increased safety, comfort, and ease with the technology. Conclusions The MVW offered a safety net to pregnant women positive for COVID-19. It provided reassurance for staff, while relieving pressures on infrastructure. When setting up similar services in future, attention should be given to identifying clinical champions, triage criteria, technology and alarm selection, and establishing flexible escalation pathways that can adapt to changing patterns of disease.

Background The SARS-CoV-2 (COVID-19) pandemic may accelerate the adoption of digital, decentralized clinical trials. Conceptual recommendations for digitalized and remote clinical studies and technology are available to enable digitalization. Fully remote studies may break down some of the participation barriers in traditional trials. However, they add logistical complexity and offer fewer opportunities to intervene following a technical failure or adverse event. Objective Our group designed an end-to-end digitalized clinical study protocol, using the Food and Drug Administration (FDA)–cleared Current Health (CH) remote monitoring platform to collect symptoms and continuous physiological data of individuals recently infected with COVID-19 in the community. The purpose of this work is to provide a detailed example of an end-to-end digitalized protocol implementation based on conceptual recommendations by describing the study setup in detail, evaluating its performance, and identifying points of success and failure. Methods Primary recruitment was via social media and word of mouth. Informed consent was obtained during a virtual appointment, and the CH-monitoring kit was shipped directly to the participants. The wearable continuously recorded pulse rate (PR), respiratory rate (RR), oxygen saturation (SpO2), skin temperature, and step count, while a tablet administered symptom surveys. Data were transmitted in real time to the CH cloud-based platform and displayed in the web-based dashboard, with alerts to the study team if the wearable was not charged or worn. The study duration was up to 30 days. The time to recruit, screen, consent, set up equipment, and collect data was quantified, and advertising engagement was tracked with a web analytics service. Results Of 13 different study advertisements, 5 (38.5%) were live on social media at any one time. In total, 38 eligibility forms were completed, and 19 (50%) respondents met the eligibility criteria. Of these, 9 (47.4%) were contactable and 8 (88.9%) provided informed consent. Deployment times ranged from 22 to 110 hours, and participants set up the equipment and started transmitting vital signs within 7.6 (IQR 6.3-10) hours of delivery. The mean wearable adherence was 70% (SD 19%), and the mean daily survey adherence was 88% (SD 21%) for the 8 participants. Vital signs were in normal ranges during study participation, and symptoms decreased over time. Conclusions Evaluation of clinical study implementation is important to capture what works and what might need to be modified. A well-calibrated approach to online advertising and enrollment can remove barriers to recruitment and lower costs but remains the most challenging part of research. Equipment was effectively and promptly shipped to participants and removed the risk of illness transmission associated with in-person encounters during a pandemic. Wearable technology incorporating continuous, clinical-grade monitoring offered an unprecedented level of detail and ecological validity. However, study planning, relationship building, and troubleshooting are more complex in the remote setting. The relevance of a study to potential participants remains key to its success.

Background Virtual care (VC) and remote patient monitoring programs were deployed widely during the COVID-19 pandemic. Deployments were heterogeneous and evolved as the pandemic progressed, complicating subsequent attempts to quantify their impact. The unique arrangement of the US Military Health System (MHS) enabled direct comparison between facilities that did and did not implement a standardized VC program. The VC program enrolled patients symptomatic for COVID-19 or at risk for severe disease. Patients’ vital signs were continuously monitored at home with a wearable device (Current Health). A central team monitored vital signs and conducted daily or twice-daily reviews (the nurse-to-patient ratio was 1:30). Objective Our goal was to describe the operational model of a VC program for COVID-19, evaluate its financial impact, and detail its clinical outcomes. Methods This was a retrospective difference-in-differences (DiD) evaluation that compared 8 military treatment facilities (MTFs) with and 39 MTFs without a VC program. Tricare Prime beneficiaries diagnosed with COVID-19 (Medicare Severity Diagnosis Related Group 177 or International Classification of Diseases–10 codes U07.1/07.2) who were eligible for care within the MHS and aged 21 years and or older between December 2020 and December 2021 were included. Primary outcomes were length of stay and associated cost savings; secondary outcomes were escalation to physical care from home, 30-day readmissions after VC discharge, adherence to the wearable, and alarms per patient-day. Results A total of 1838 patients with COVID-19 were admitted to an MTF with a VC program of 3988 admitted to the MHS. Of these patients, 237 (13%) were enrolled in the VC program. The DiD analysis indicated that centers with the program had a 12% lower length of stay averaged across all COVID-19 patients, saving US $2047 per patient. The total cost of equipping, establishing, and staffing the VC program was estimated at US $3816 per day. Total net savings were estimated at US $2.3 million in the first year of the program across the MHS. The wearables were activated by 231 patients (97.5%) and were monitored through the Current Health platform for a total of 3474 (median 7.9, range 3.2-16.5) days. Wearable adherence was 85% (IQR 63%-94%). Patients triggered a median of 1.6 (IQR 0.7-5.2) vital sign alarms per patient per day; 203 (85.7%) were monitored at home and then directly discharged from VC; 27 (11.4%) were escalated to a physical hospital bed as part of their initial admission. There were no increases in 30-day readmissions or emergency department visits. Conclusions Monitored patients were adherent to the wearable device and triggered a manageable number of alarms/day for the monitoring–team-to-patient ratio. Despite only enrolling 13% of COVID-19 patients at centers where it was available, the program offered substantial savings averaged across all patients in those centers without adversely affecting clinical outcomes.

Background During the COVID-19 pandemic, individuals with a positive viral test were enrolled in a study, within 48 hours, to remotely monitor their vital signs to characterize disease progression and recovery. A virtual trial design was adopted to reduce risks to participants and the research community in a study titled Risk Stratification and Early Alerting Regarding COVID-19 Hospitalization (RiskSEARCH). The Food and Drug Administration–cleared Current Health platform with a wearable device is a continuous remote patient monitoring technology that supports hospital-at-home care and is used as a data collection tool. Enrolled participants wore the Current Health wearable device continuously for up to 30 days and took a daily symptom survey via a tablet that was provided. A qualitative substudy was conducted in parallel to better understand virtual trial implementation, including barriers and facilitators for participants. Objective This study aimed to understand the barriers and facilitators of the user experience of interacting with a virtual care platform and research team, while participating in a fully virtual study using qualitative and quantitative data. Methods Semistructured interviews were conducted to understand participants’ experience of participating in a virtual study during a global pandemic. The schedule included their experience of enrollment and their interactions with equipment and study staff. A total of 3 RiskSEARCH participants were interviewed over telephone, and transcriptions were inductively coded and analyzed using thematic analysis. Themes were mapped onto the Theoretical Domains Framework (TDF) to identify and describe the factors that influenced study adherence. Quantitative metrics, including adherence to wearable and scheduled tasks collected as part of the RiskSEARCH main study, were paired with the interviews to present an overall picture of participation. Results All participants exceeded our definition of a fully adherent participant and reported that participation was feasible and had a low burden. The symptoms progressively resolved during the trial. Inductive thematic analysis identified 13 main themes from the interview data, which were deductively mapped onto 11 of the 14 TDF domains, highlighting barriers and facilitators for each. Conclusions Participants in the RiskSEARCH substudy showed high levels of adherence and engagement throughout participation. Although participants experienced some challenges in setting up and maintaining the Current Health kit (eg, charging devices), they reported feeling that the requirements of participation were both reasonable and realistic. We demonstrated that the TDF can be used for inductive thematic analysis. We anticipate expanding this work in future virtual studies and trials to identify barriers and enabling factors for implementation.

The importance of vital sign monitoring to detect deterioration increases during healthcare at home. Continuous monitoring with wearables increases assessment frequency but may create information overload for clinicians. The goal of this work was to demonstrate the impact of vital sign observation frequency and alarm settings on alarms in a real-world dataset. Vital signs were collected from 76 patients admitted to healthcare at home programs using the Current Health (CH) platform; its wearable continuously measured respiratory rate (RR), pulse rate (PR), and oxygen saturation (SpO2). Total alarms, alarm rate, patient rate, and detection time were calculated for three alarm rulesets to detect changes in SpO2, PR, and RR under four vital sign observation frequencies and four window sizes for the alarm algorithms’ median filter. Total alarms ranged from 65 to 3113. The alarm rate and early detection increased with the observation frequency for all alarm rulesets. Median filter windows reduced alarms triggered by normal fluctuations in vital signs without compromising the granularity of time between assessments. Frequent assessments enabled with continuous monitoring support early intervention but need to pair with settings that balance sensitivity, specificity, clinical risk, and provider capacity to respond when a patient is home to minimize clinician burden.