key: cord-0783546-ud1j80j2 authors: Gorbenko, Ksenia; Mohammed, Afrah; Ezenwafor, Edward; Phlegar, Sydney; Healy, Patrick; Solly, Tamara; Nembhard, Ingrid; Xenophon, Lucy; Smith, Cardinale; Freeman, Robert; Reich, David; Mazumdar, Madhu title: Innovating in a Crisis: A Qualitative Evaluation of a Hospital and Google Partnership to Implement a COVID-19 Inpatient Video Monitoring Program date: 2022-05-20 journal: J Am Med Inform Assoc DOI: 10.1093/jamia/ocac081 sha: 6288f60badc8e4ec08918effb6bf7c2b5e4d772c doc_id: 783546 cord_uid: ud1j80j2 OBJECTIVE: To describe adaptations necessary for effective use of direct-to-consumer (DTC) cameras in an inpatient setting, from the perspective of health care workers. METHODS: Our qualitative study included semi-structured interviews and focus groups with clinicians, information technology (IT) personnel, and health system leaders affiliated with the Mount Sinai Health System. All participants either worked in a COVID-19 unit with DTC cameras or participated in the camera implementation. Three researchers coded the transcripts independently and met weekly to discuss and resolve discrepancies. Abiding by inductive thematic analysis, coders revised the codebook until they reached saturation. All transcripts were coded in Dedoose using the final codebook. RESULTS: Frontline clinical staff, IT personnel, and health system leaders (N = 39) participated in individual interviews and focus groups in November 2020–April 2021. Our analysis identified five areas for effective DTC camera use: technology, patient monitoring, workflows, interpersonal relationships, and infrastructure. Participants described adaptations created to optimize camera use and opportunities for improvement necessary for sustained use. NOn-COVID-19 patients tended to decline participation. DISCUSSION: Deploying DTC cameras on inpatient units required adaptations in many routine processes. Addressing consent, two-way communication issues, patient privacy, and messaging about video monitoring could help facilitate a nimble rollout. Implementation and dissemination of inpatient video monitoring using DTC cameras requires input from patients and frontline staff. CONCLUSIONS: Given the resources and time it takes to implement a usable camera solution, other health systems might benefit from creating task forces to investigate their use before the next crisis. The COVID-19 crisis emerged abruptly and has strained the health care systems around the globe. The rapidly increasing numbers of patients with COVID-19 needing hospitalization, staff shortages, and lack of sufficient personal protective equipment (PPE) generated many challenges, including the difficulty of providing enhanced monitoring of patients under isolation. Moreover, hospitals faced an urgent need to protect health care workers from the highly infectious and deadly virus while providing optimal care to patients. Access to appropriate PPE and fear of infecting self and loved ones has been among the top sources of anxiety for health care workers and leaders during the pandemic. [1] To address these concerns, many hospitals increased their use of telemedicine tools that do not require physical proximity for medical screening and evaluations, and tools now referred to as electronic PPE, or ePPE. [2, 3] One of the innovative responses that allowed adequate patient monitoring and helped to preserve traditional PPE (e.g., N95 face masks) by minimizing non-critical contact with patients was using direct-to-consumer (DTC) cameras on COVID-19 floors. DTC cameras have been familiar in non-health care settings for decades. For example, homeowners have used them in closed circuit television systems for security purposes; educators have used them in distant learning to reach remote learners; parents have used them in baby monitoring systems to see and hear their infants from another room in the house. in the greater New York City area and other hospital systems took this innovative approach to facilitate patient monitoring. [4] [5] [6] This study examines the use of DTC cameras at a 3,815-bed academic medical center where the daily census of patients with COVID-19 reached almost two thousand in early April 2020, including over 400 patients in intensive care units (ICUs). Many of these patients were suffering from respiratory distress and were connected to advanced respiratory devices that required enhanced monitoring. MSHS leadership needed cost-effective cameras with simple installation that could be used by staff easily with minimal training. Minimum requirements included sufficient video image resolution to discern patient discomfort and clear views of the digital readouts of vital monitors. Originally designed as home monitoring systems, Google Nest cameras met these criteria and were leased by MSHS free of charge as an ePPE solution for inpatient monitoring. The health systems received and installed 170 Google Nest cameras and implemented them within two weeks at four hospitals. The scale and speed of implementation of this intervention was unprecedented due to the pressures of the pandemic. The few prior studies of inpatient video monitoring that exist have described the use of other forms including telecare phone calls, telemonitoring app, [7] centralized video monitoring with in-room webcams, [8] tele-intensive care units (tele-ICUs), [9, 10] and tele-critical care for family visitation during the COVID-19 pandemic. [11] These studies show the promise of each of these technologies specifically. Our study offers insight specific to the use of DTC cameras, contributes to understanding whether the adaptations for other forms of ePPE generalize to DTC cameras, and thus informs future implementations of ePPE in hospitals. Adaptation, a key concept in implementation, is a process of thoughtful and deliberate alteration to the design or delivery of an intervention, with the goal of improving its fit and effectiveness in a given context. [12, 13] The objective of our study was to describe the adaptations needed to increase effective use of the cameras from the perspective of frontline clinical staff, IT personnel, and hospital leaders. The early surge in the number of patients with COVID-19 in MSHS created the need to have continuous "eyes on the patient" from a distance. Within the first days of the pandemic, Mount Sinai Hospital added 60 ICU beds and converted two non-ICU units to accept patients with COVID-19. Unlike ICU floors, these floors had solid doors and walls, preventing needed external visualization of patient rooms. Being able to see patients was critical for timely detection of the need for intervention but the highly infectious and aerosolized nature of COVID-19 transmission required patients to be in isolation. Healthcare workers had to minimize in-person contact for their own and other patients' safety. Recognizing the visual need and building barrier, MSHS leaders reached out to tech companies about cameras. A contact at Google proposed the use of their DTC solution (Google Nest security cameras for home), which could be customized for hospitals. Partnership between clinicians, Google, IT and engineering departments aided a quick rollout, given the urgency of the situation. Google loaned these cameras to MSHS temporarily free of charge. A team of engineers from Google and a multidisciplinary team from Mount Sinai that consisted of frontline clinicians, IT and leadership met daily to design the patient monitoring console. A working prototype was ready to be deployed after two weeks of design and development and then a few dozen of Google Nest cameras arrived and were quickly installed. This was the first of many deliveries as the program scaled across MSHS hospitals. MSHS received 170 cameras in total and had about 100 patients being monitored using these cameras at once during peak usage. Cameras were deployed on inpatient units at four hospitals and other care settings (e.g., dialysis). We employed a qualitative design using semi-structured in-depth interviews and focus group discussions, to assess the experiences and perceptions of MSHS staff about the use of Google Nest DTC cameras on COVID-19 floors. [14, 15] Our study was guided conceptually by the Non-7 adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework which is pragmatic, evidence-based and theory informed. [16] The framework was developed to help predict and evaluate the success of technology-supported health programs, including remote patient monitoring. The framework guides evaluation of technology adoption, non-adoption, and abandonment by focusing evaluation efforts on implementation constructs (domains) that have critical impact on program success. The NASSS framework includes seven domains: condition, technology, value proposition, adopters, organization, wider system (i.e. policy environment), embedding and adaptation. We identified COVID-19 as the condition, DTC Google Nest cameras as technology. The value proposition was to improve patient safety, decrease staff anxiety about patients behind closed doors, and decrease staff exposure to COVID-19. Adopters (clinicians and IT personnel) and organization (organizational leaders) are key stakeholders involved in this early demonstration project within a single health system. We chose to conduct our study from their perspective because they were most knowledgeable about the adaptations needed for effective use of cameras. The interviews and focus groups took place between November 2020 and April 2021. During this period, New York City experienced a second wave of COVID-19 pandemic, [17] with schools switching to remote instruction by the end of November; COVID-19 vaccines receiving emergency authorization in December 2020; and schools reopening for in-person classes in February-March 2021. Interviews, which were conducted by a single researcher, occurred via phone or video conferencing, while focus groups were facilitated by two team members on site (initials removed for blinding) using video conferencing equipment to connect with interviewers (initials removed for blinding). We used focus groups with clinical staff to explore opinions, attitudes, and beliefs about camera implementation in a time-efficient manner. We added individual interviews with nurse managers, registered nurses, patient care associates (PCAs), and nursing assistants (NAs) to clarify emerging themes, gather detailed descriptions of processes, and capture any divergent opinions that could be missed in a focus group setting. We interviewed some physicians in leadership positions, and report them as "health system leaders" rather than physicians here. We interviewed no physicians working on the COVID-19 units. This was an intentional decision based on whose workflows were affected by the DTC cameras the most: nurses and patient care associates. While aware of the cameras, physicians continued to round on patients in person and did not use the cameras in their work or interaction with patients. We used the same interview guide for interviews and focus groups. The study team completed frontline personnel interviews early in the project. In seeking to understand the technical and administrative context, we recruited additional interviewees in IT and leadership roles in the spring. The study was deemed exempt by the Mount Sinai Program for Protection of Human Subjects. All participants voluntarily consented to be interviewed and recorded for anonymized transcription, and de-identified reporting of their comments. We recruited a variety of stakeholders, including frontline clinical staff, information technology (IT) personnel, and MSHS leaders (N=39) for individual interviews and focus groups. The clinical staff included PCAs, nurse managers, registered nurses, and nursing assistants (N=31 in 6 focus groups and 7 individual interviews). We also conducted individual interviews with project 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 management personnel, executive leaders, IT staff members, and a technical engineer from Google (N=8). The primary inclusion criterion was working on a COVID-19 floor with cameras installed or having direct experience with the project. The study team conducted 30-minute interviews and focus groups via internet-based video conferencing. Participants were assigned identification (ID) codes to identify data collected from them. Focus group participants were reported as a single group without participants' ID codes, because all focus groups were with clinical staff and the main focus was in documenting their experiences. The interviewer ensured that each participant answered questions in all domains of the interview guide (Table 1) including participants' roles in patient care, their experiences with the cameras, the impact on clinical workflows, patient safety, and staff morale, along with opportunities for improvement of camera use beyond the COVID-19 pandemic. Using an interview guide helped ensure consistency and reliability of collected data across participants. [18, 19] The interviewers used probes for clarification of concepts to ensure data credibility, or truth value to the participants and the context. [20] Using probes can also elicit different explanations/ details around certain constructs, thereby highlighting different facets of these phenomena. We reached saturation after we completed about two-thirds of the total number of interviews with clinical staff (4 out of 6 focus groups with clinical staff, N=2 individual interviews with nursing staff, and N=1 interview with a PCA). We followed accepted standards in qualitative research, which defines saturation as the point when new interviews yielded very little/ no new information. We continued to interview a few more people beyond 21 that point to make sure we have not missed anything. Then, we recruited IT personnel and executive leaders to add context and varying perspectives. Interviewers' personal preconceptions or biases regarding DTC camera use were discussed within the research team and documented prior to interviews to reduce bias in participant selection and data analysis. Is there anything we should have asked but didn't? A professional transcription service transcribed recorded interviews. The study team verified transcripts with interviewers' notes for consistency and accuracy and analyzed transcripts using the inductive technique, i.e. using individual observations in the data to derive codes and themes. [18] We used Dedoose qualitative analytic software [21] to extract broad themes (aspects within the data that reflected single concepts) and assigned codes to them. Subsequently, we identified sub-codes under these main codes for more specific themes. Thematic analysis provided a flexible approach to identifying, analyzing, and reporting patterns. [22] Three analysts (AM, KG, EE) coded a subset of transcripts (N=5) independently, one at a time, met to discuss discrepancies, and agreed on a set of codes and definitions (initial codebook). Then, the same coders used the initial codebook to code Transcript 2, met and 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 discussed discrepancies, updated the codebook with the changes introduced at Transcript 2. This process was repeated with 5 interview transcripts, until the coders were applying the latest version of the codebook and the codebook was stable, i.e. coders were no longer suggesting to add, change, split, or combine codes. At this point, one analyst (initials removed for blinding) applied the codebook to the complete data set. We organized similar and related codes into broader themes through visual examination and meticulous consideration of their meanings. Research team discussions helped further refine codes. An integrated narrative was discussed among team members and colleagues to verify coherence of the themes and in-between themes, alongside the original research questions. Analytical rigor was ensured through[18]: 1. Constant reference to participants' ID codes to ensure data was appropriately associated with participants' voices. 2. Consistency in data collection and monitoring of fidelity (use of interview guide, limited number of interviewers, mentorship and supervision of junior researchers). 3. Triangulation of methods (interviews and focus groups), participants (clinical staff, IT, leaders), and analysts (medical sociologist, two physicians). 4. Regular reference to source documentation, recordings and interviewers' notes to ensure data accuracy. Weekly team meetings during all stages of the analytic process, to ensure agreement and reliability of codes and results. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 6. Appropriate documentation, recording and secure storage of data with subsequent analysis for independent auditing for research integrity. 7. Discussions with various cadres of health care workers at MSHS during development of themes identified in this study. 8. Parallel data collection and analysis. Interviewees' comments revealed five areas for adaptation required for effective DTC camera use for inpatient monitoring: technology, patient monitoring, workflows, interpersonal relationships, and infrastructure. Within each theme, respondents discussed solutions to challenges that surfaced during the implementation, or adaptations ( Figure 1 and Table 2 ). Respondents also highlighted challenges that remained at the time of the interview (8-13 months after camera implementation), which we term opportunities for improvement ( Figure 2 and Table 3 ). Their comments indicated that these opportunities would need to be addressed for sustained DTC use. Participants noted that patients had declined to use DTC after the units reversed to their pre-pandemic designations and began to care for non-COVID-19 patients. We also explored differences in perceptions of camera implementation and use among clinicians on two units that participated in this study. In the end, we did not identify any striking differences in the perceptions of clinical staff from the two units. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 The Google Nest cameras needed technical adaptations for compliance with federal regulations concerning protections of patient data and privacy ( IT personnel added a function to switch between livestream video and a series of snapshots taken every five seconds on one unit to relieve network limitations in streaming multiple videos simultaneously. On that unit, critical patients were prioritized for full streaming, while others had a series of snapshots at 5-second intervals ( Table 2 , 1c). Other features included zoom-in and "privacy" enabling camera shut-off at patients' request (e.g., while changing), until a nurse approves further monitoring, a light on the camera indicated if monitoring was taking place. To preserve confidentiality, IT completely deactivated the recording feature (Table 2 , 1d-e). Our respondents described the cameras as "extra eyes" on the entire floor, for example, when there was a critical event with one patient, enabling the team to focus on the crisis, with one 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 staff deployed to monitor the floor through the feeds ( Patients were less receptive when they were not pre-informed (e.g., admitted in a confused state), or when the unit went from COVID to non-COVID (Table 2, 2d). 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 having PCAs and nurses prepared to handle the situation before they entered the room ( Table 2 , 3b). The cameras did not change the workload or nature of patient care, though they did help triage non-urgent requests ( Table 2 , 3c). Cameras also provided extended floor coverage when staff had assignments to patients in other parts of the unit ( Table 2 , 3d). The cameras affected staff processes in terms of length of stay in patient rooms, frequency of checking on patients, and reduced the number of times they needed to don and doff PPE. With the goal of reducing staff exposure to the virus in isolation rooms and in the context of staff shortages, cameras allowed clinical staff to check on patients remotely some of the time ( Table 2 , 3e-f) The implementation team and frontline clinicians designed a handoff sheet (Appendix A) to create an integrated team strategy and facilitate training of personnel ( Table 2 , 4a, c). It included patient information, assigned PCA's and nurse's names, patient oxygen modalities, fall risk, and phone number of the room. NAs on duty could use the phone to call the patient and ask them, for example, to put their oxygen device back on. Direct input of frontline staff was key to implementing the intervention because the need for cameras emerged organically from the units and was not imposed from above. This secured staff buy-in ( 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Engineering teams temporarily secured cameras on ceilings, which was useful in moving them around, especially for patients who could move around the room ( Table 2 , 5a, c). Flexibility in camera integration with existing technology was also useful. For example, one unit experimented with having patient video streams on iPads outside patient rooms, allowing nurses to be by the "bedside" monitoring their patients in the hallway (Table 2, 5b). The most frequently stated concern by participants was ability to communicate with patients via camera microphone and speaker (Table 3 , 1a). They stressed that the cameras were distant from the patient, located on the opposite wall to capture their full body and the noise of medical equipment and extractor fans in isolation rooms interfered with the audio quality. Bedside teams called the phone in the patient rooms and had patients use call bells. External microphones and speakers would be desirable enhancements in future applications (Table 3, 1a). Delays in data transmission also affected video and audio quality. Reducing lag from cloud transmission and routing feeds directly to the browser interface, might improve video and audio quality ( Table 3 , 1b). Respondents recommended considering newer camera models with higher capabilities (Table 3, 1c) , better picture quality and motion sensors for coverage of patients who could walk and improved quality to zoom-in on monitors (E.g., pulse oximeters) without entering the rooms. Quick and convenient deployment of cameras between rooms was critical during the pandemic, and participants mentioned the ease of deploying and using new cameras as essential (Table 3, 1e) . Increasing reliability of communication between patients and staff was among the most frequently suggested improvements ( incorporated in the consent process and parameters developed for assessing consent capacity (Table 3, 2b) . Standardized consent workflows may improve consent rates, thereby improving patient safety. Positive messaging about cameras (e.g., telling patients that "this is a tool that we offer for your safety"), and letting them opt out may also improve consent rates and decrease disconnection rates. Recording may be disabled by vendors prior to rollout due to privacy and liability risks. One respondent emphasized that a culture of failing fast should be encouraged outside of crisis or pandemic context (Table 3 , 3a). This hospital leader described their process of innovating in a crisis: "Once you have the problem, figure out who are the stakeholders, bring them together, and then just brainstorm. What are the gaps? What do we have? What can we try? What's our ideal state? What experiment can we do? How quickly can we do it? How quickly can we come back to debrief on it? Did it work? Did it not work? Do we have to modify?" Camera positioning is crucial for adequate coverage of the rooms and enhanced video quality. Some rooms had one camera per two patients as the number of patients rapidly increased, resulting in poor camera positioning, creating blind spots that compromised patient safety, and warranted regular walk-ins (Table 3, 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 bathrooms. More power outlets in the rooms will reduce the distance between cameras and enhance clearer visualization of the floors (Table 3, 4b) . Relevant internet upgrades suitable for high-quality video streams will aid visualization of readings from diagnostic equipment over the cameras (Table 3, 4c) . Upgrading all hospital rooms to have the potential for ICU-level visualization and hard-wired monitoring capability will help in a potential future surge ( This is the first study to our knowledge that describes the use of direct-to-consumer cameras as ePPE in a hospital setting, with the goals of improving patient and health care worker safety. Our study focused on the implementation process of deploying DTC cameras in the inpatient setting. The DTC cameras were deployed rapidly during the initial surge in New York. Several 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 leaders we interviewed spoke about the need to adapt these technologies to the unique contexts of their institutions, which varied even within the same health system. Table 4 summarizes general recommendations for implementing DTC cameras in an inpatient setting. Discussions around privacy and safety are ongoing and will require further clarifications. By contrast with studies of tele-ICUs, which reported some pushback from staff, we found that frontline clinicians at MSHS initiated and implemented many adaptations to make camera use more effective. [9] This finding is consistent with early reports about using telemedicine at ePPE during the COVID-19 pandemic. [2, 3] This may be explained by several 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 factors. First, video monitoring was conducted on the same floor, by nursing assistants who were part of the unit staff (rather than external staff in several tele-ICU studies), and at the request of the unit. Secondly, the camera intervention was implemented during a global pandemic, and promised to reduce the exposure to the virus and thus reduce their risk of falling ill with the novel pathogen. The fear of contagion and the risk of infecting self or loved ones was likely a strong impetus to embracing the project. With the scarcity of the PPE, anything that preserved PPE was well appreciated by the frontline staff. Third, cameras helped staff to feel more confident in their ability to perform their duties while someone else was watching their other patients. Prior to the implementation of DTC cameras, nursing staff reported feeling anxious about their ability to deliver quality care behind closed doors with no visibility. Research shows that feeling helpless was common among health care workers during the pandemic, and is in fact one of the indicators of professional burnout. [23] Designing a standardized workflow for identifying patients who can benefit from video monitoring, timeframes when they need to be monitored (e.g. 24/7 or only at night), developing patient-centric protocols to identify patients who should be offered to opt in rather than using the global opt-out strategy, and investing in health care specific plug-and-play cameras can protect patient lives, improve patient and family satisfaction, protect health care personnel from infection and burnout and reduce health care costs. While video monitoring has been used in health care in the past to enforce compliance to protocols such as hand hygiene [24] our study indicates that both patients and staff will likely accept being monitored if it is meant to protect them from harm. However, vendors need to develop products specifically tailored for health care and adhering to regulations regarding patient privacy. 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 With a number of adaptations to local context, DTC cameras are a promising tool and can be used in a variety of health care settings, such as inpatient units caring for patients with brain injury, delirium, dementia, or on certain medications. Further research is needed to evaluate how and to what extent inpatient video monitoring could improve patient safety and health care workforce psychological well-being. Our study has some limitations. This was a single case study that may not generalize to other hospitals and health systems. MSHS is a large health system located in New York City, with access to advanced monitoring technology and Google Nest cameras during the pandemic. In sum, our findings indicate that the effective use of ePPE and DTC cameras is contingent on adaptations, based on the observations of frontline staff and leaders. As our study shows, developing the workflows takes time, and discussions around patient privacy and everyone's safety are still ongoing. Using camera solutions during "normal" times may help improve patient safety and reduce staff anxiety on units caring for patients with limited physical and/or cognitive capacity, such as dementia, or on certain medications. We urge health care 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 DATA AVAILABILITY STATEMENT: The data underlying this article cannot be shared publicly due to the privacy of individuals that participated in the study. Anonymized data will be shared on reasonable request to the corresponding author . 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 This work was supported by the Office of Clinical Innovation, Mount Sinai Health System The authors have the following financial or personal conflicts to disclose: KG received salary support for conducting this study from the Office of Clinical Innovation, Mount Sinai Health System Acquisition of data: Ksenia Gorbenko Analysis and interpretation of data: Ksenia Gorbenko Critical revision of the manuscript for important intellectual content: Ksenia Gorbenko Understanding and Addressing Sources of Anxiety among Health Care Professionals during the COVID-19 Pandemic Electronic personal protective equipment: A strategy to protect emergency department providers in the age of COVID-19 Deployment of information technology to facilitate patient care in the isolation ward during COVID-19 pandemic Mount Sinai deploys Google Nest cameras for COVID-19 patient monitoring and communication | TechCrunch Real-Time Smart Patient Monitoring and Assessment Amid COVID-19 Pandemic -an Alternative Approach to Remote Monitoring Remote Patient Monitoring Program for COVID-19 Patients Following Hospital Discharge: A Cross-Sectional Study. 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