Tele-critical care was gaining momentum even before the wave of COVID-19 patients hit the US healthcare system. However, with the need to quickly extend the reach of intensive care unit (ICU) expertise around the country and, in some cases establish makeshift ICUs, tele-critical care represents the most rapidly scalable and readily available digital solution. In the vast landscape of the various technologies that constitute tele-critical care, it is important that digitally-enabled care leads to improved healthcare outcomes, optimal resource utilization, and cost efficiency. What is the evidence that tele-critical care tools accomplish these goals?
Tele-critical care tools enable ICUs to provide critically ill patients access to a remotely-stationed intensivist via an internet connection and a two-way audio-visual-electronic communication device fit with adjunctive diagnostic tools as needed. Critical care teams are able to manage ventilator mechanics, hemodynamics, critical care consultations, and end-of-life discussions remotely much as they would in-person. Decentralized models are based around a tele-intensivist that is highly engaged with the on-site multidisciplinary team and mimics standard “round and respond” ICU workflows, including multidisciplinary rounds, responding to code blues or emergencies, and managing ICU throughput. In the most sophisticated of platforms, a dashboard with real-time physiologic parameters is remotely monitored with AI-enabled triggers for early detection of patient decompensation. In the COVID pandemic, tele-critical care will be valuable as the census of patients may overwhelm the number of physicians and respiratory therapists who can monitor and manage patients physically in the ICU. Digital platforms for remote monitoring and management can help with this imbalance by digitally scaling workforce capacity to monitor and manage remotely.
Not all tele-critical care systems are created equally, with variability in cost, quality, and system functionality. The pre-COVID era suggested that tele-critical care could improve ICU mortality,(1) reduce length of ICU stay,(2) decrease the need for inter-hospital transfer,(3) and improve compliance with sepsis management protocols.(4) Importantly though, several studies (5,6) have reiterated the dramatic heterogeneity of tele-critical care practices and the varied downstream outcomes. The technology by itself will have limited impact, but the factors involved in implementation and use of the technology will affect its performance and return on investment (ROI). By analogy, a scalpel may be a perfectly manufactured tool, but in the wrong hands, or used in the wrong way, it may not have the desired effects on clinical outcomes.
In the high-cost environment of the ICU, tele-critical care needs to perform as an economical tool that can potentially reduce costs. The results of fiscal ROI reports have been mixed (7) since the profitability of a tele-ICU system is reliant on reducing adjacent ICU medical care costs.(8) In order to achieve this, the sum of revenue reimbursement and associated cost savings must exceed the upfront capital cost and ongoing operating cost of a tele-critical care system.(9) In the current market, the first year capital and operational cost of adopting a tele-critical care system can range from $7,200 per ICU bed in decentralized formats up to $100,000 per monitored bed in centralized formats.(10,11) Some studies have suggested the potential for break even and even positive ROI within 5 years.(12) As with most substantial purchases, hospitals must be prepared for a sustained implementation before realizing the fiscal and clinical benefits.(9)
With expansion of access to telehealth services by the Centers for Medicare and Medicaid Services (13) and relaxation of state regulations on medical licensing and credentialing during the COVID-19 pandemic, tele-critical care is poised to expand from rural or under-served areas to a broader penetration of the landscape to fill gaps in the workforce. GE and Microsoft, for example, have partnered in offering their Mural Virtual Care Solution on the Microsoft Azure cloud for the COVID-19 pandemic to help clinicians manage ventilated patients on a population basis to prioritize care, monitor dynamic changes of lung mechanics remotely, and wean patients off the ventilator appropriately.(14) Implementation in such a fluid environment is key. There are many makeshift tele-critical care platforms being rapidly set up in surge planning for COVID-19, however poor implementation can risk adding to the chaos of an already shifting environment, confusing roles and responsibility, and breaking down lines of communication. If tele-critical care is deployed systematically, it can promote adherence to best practices and improve ICU throughput, provider response times, and team communication.
Data from the University of Massachusetts Memorial Critical Care Operations Group (15) established an early model of a tele-critical care intervention: a remote monitoring center with audio-video capability that was responsible for real time audits of best practice adherence and patient monitoring that improved mortality and length of stay, and lowered rates of preventable complications. These improved outcomes were achieved by timely intensivists’ review of patients, timely use of performance data, adherence to best practices and quicker alert response times.(2) Tele-critical care models in war times or within resource-limited military hospitals have aimed for rapid deployment, and have been successful in managing sicker patients in community settings, albeit with limited information on outcomes.(16,17) During the COVID-19 pandemic, it may be reasonable that tele-critical care models around the country should be expected to perform in a manner similar to the triage and stabilization priorities of the military use of these tools.
In the post-COVID era, what will be the new normal of tele-critical care? Based on the evidence available, it will be important to stay true to the need for quick response, real-time patient monitoring, and adherence to best practices. Machine learning has already demonstrated value in critical care from early prediction of ventilator asynchrony and need for tracheostomy, pre-sepsis identification, false alarm reduction, predicting hospital acquired complications and in-hospital mortality.(18)
Consider the need for the following:
In summary, as tele-critical care evolves into a more technology-enabled environment, it will need to balance a population based approach with an emphasis on the individual experience. Utilization of the myriad of tele-critical care technologies will need to focus on patient centered outcomes, improved efficiencies, and reduced healthcare costs. Importantly, the changing landscape of tele-critical care will need to be data driven and evidence based.
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NODE.Health is pleased to cross post this article giving examples of tele-critical care. As more evidence comes out on the utilization of tele-critical care for COVID-19, NODE.Health will keep its readers informed. Interested in learning more about the Network of Digital Evidence (NODE.Health)? Click here