key: cord-0768798-7uvr6xcs
authors: Ahmed, Adnan; Charate, Rishi; Pothineni, Naga Venkata K.; Aedma, Surya Kiran; Gopinathannair, Rakesh; Lakkireddy, Dhanunjaya
title: Role of Digital Health During COVID-19 Pandemic and Future Perspectives
date: 2021-10-30
journal: Card Electrophysiol Clin
DOI: 10.1016/j.ccep.2021.10.013
sha: b1c6fb34f349a25ec574e7c1d168b5762384bd3b
doc_id: 768798
cord_uid: 7uvr6xcs

The Coronavirus disease (COVID-19) revolutionized the digital health care. This pandemic was the catalyst for not only a sudden but also widespread paradigm shift in patient care, with nearly 80% of the U.S. population indicating they have used one form of digital health. Cardiac electrophysiology took the initiative to enroll patients in device clinics for remote monitoring and triage patients accordingly. Tele-medicine was adapted to conserve PPE and ensure safety for patients and health care personnel. The concept of universal testing for emergent procedures was also adapted in institutions. Tele-AF project, smartphone ECG surveillance, heart logic(TM) and loading anti-arrhythmic drugs at home with smart phone tracings are leading examples of incorporating artificial intelligence tools in clinical electrophysiology practice. Though challenges remain making digital health available to masses, the future of digital health will be tested in the post-pandemic time, and we believe these changes will continue to be expansive and widely applicable to physicians and patients.

The Coronavirus disease pandemic has yielded an unparalleled global challenge in the delivery of healthcare. From nationally mandated quarantines and mass vaccination efforts to ushering in a new era of virtual communication, it has necessitated a new perspective on healthcare moving forward. Specifically, it has led to institutionalized changes to healthcare systems, hospitals, medical professionals, ancillary staff, training programs, and healthcare polices. Aims to both safely preserve the best qualities of face-to-face traditional patient care as well as integrate technology and virtual care have been at the forefront of each specialty. Digital health care has been a revolution in this effort in effective management of patients with complex conditions. This paradigm shift has called for our advocacy to improve upon and incorporate even newer emerging digital health solutions as well as alleviate previous barriers to digital healthcare. Cardiac electrophysiology has been uniquely poised as a specialty that has been accustomed to using digital health techniques such as remote monitoring and artificial intelligence (AI) supplementary tools even in the pre pandemic period [1] . In this current manuscript, we explain the obstacles encountered with in-person care during the pandemic, review currently available digital health platforms specifically in relation to cardiac electrophysiology and explore further avenues for advancing digital and in-person care delivery in the future.

The COVID-19 pandemic has abruptly ushered in a foundational change to the traditional practice of medicine. Despite clinical research and advancements continually evolving and reshaping the field of medicine, the practice of face-to-face patient encounters had previously remained stable.

While face to face care was accepted as the norm for centuries, the pandemic forced us to revisit this idea as a community. This pandemic was the catalyst for not only a sudden but also widespread paradigm shift in patient care, with nearly 80% of the U.S. population indicating they have used one form of digital health [2, 3] . The pandemic has also enabled healthcare providers and administrators to revisit the intricacies of in-person care delivery and improve overall efficiency.

In-person care is dependent on a variety of supporting frameworks that include providers, administrative personnel, patients, caregivers, family members and is very time and resource intensive. Testing for COVID-19 and limiting physical contact between personnel for in-person J o u r n a l P r e -p r o o f care made for a more complex, time consuming and inefficient process. One study advocated for creating a safe workplace by universal testing for COVID-19 in asymptomatic patients and healthcare workers. Out of 1670 subjects, 758 were patients and 912 were caregivers, EMS, and EP lab personnel. They study found 3.8%positivity rates in asymptomatic population. [4] While hospitals began cancellation of elective clinic and procedural visits in efforts to allocate health care resources towards tackling the pandemic, a steep decline in patient comfort levels in attending inperson visits was also noted. Several reports have indicated patient hesitancy to attend for inperson care even for concerning anginal symptoms. In fact, there was a reduction in patients presenting to the emergency room with acute myocardial infarction during the peak of the pandemic, and those that presented had higher mechanical complications due to late presentations [5] . These data highlight the hesitancy and overt concern that patients may have to seek medical care in this current global crisis, which can sometimes be life-threatening. Cardiac electrophysiology has also seen a decline in in-person visits across the globe during the pandemic.

However, electrophysiology has an advantage of decision-making being driven by abstract data such as rhythm monitors, electrocardiograms, and device interrogations, which enabled a smoother transition to virtual care.

Cardiac electrophysiology has been a leader in digital health care. Over the years multitude of devices has been developed and implemented in clinical practice, and these services were increasingly utilized during the pandemic in addition to development of some novel tools. Remote cardiac monitoring can be classified into three broad categories: [1]

 Medical grade wearable monitors such as Holter monitor and external and Internal loop recorder.

 Consumer grade wearable monitors such as smart watches.

 Cardiac implantable electronic devices (CIEDs) such as pacemakers and defibrillators.

J o u r n a l P r e -p r o o f These diverse range of devices generate different types of data. Whereas Holter and loop recorders only function as data collectors, CIEDs can recognize critical findings and intervene based on programing. As a result, remote monitoring bears a prognostic value and helps in reducing worse outcomes. CIEDs received a class I recommendation for remote monitoring in 2015. [6] However, in the pre pandemic times remote monitoring was underutilized due to patient and system-based issues. The pandemic made remote monitoring an important tool to help identify critical and noncritical issues and address them accordingly. [7] Enrollment of existing patients in device clinics in remote monitoring was an important initiative undertaken by various EP programs in response to the pandemic. [8] One Italian study reported an experience of 332 patients introduced to remote monitoring during the lock down. Patients were categorized based on modality, divided between remote monitoring at home vs office. Study findings reported high patient satisfaction and providers were better able to provide continuous healthcare coverage in eligible CIED patients. [9] Remote monitoring enables informed triage of patients needing urgent procedures, clinical decision making and diagnosis, and implementation of appropriate therapeutic interventions while bypassing an in-person visit. Similarly, patients adopting digital health tools like pulse oximeters, automated blood pressure equipment, glucose monitors, and single lead ECG recorders were able to provide their respective physicians with important data without risking exposure.

One important aspect of remote monitoring is the burden of data received and the challenge of trained personnel being available to accurately review and act upon the data. Development of novel Artificial intelligence (AI) tools that can incorporate machine learning can help stratify the findings, so that appropriate measure can be taken. 

The concept of tele-medicine existed in the pre-covid era but it was very limited and often complicated with re-imbursement issues for physicians. The COVID-19 crisis led to rapid adoptions of virtual medical care. At present tele-medicine is provided by telephones, secure messaging, and audio-video conference calls via commercial applications. The Office for Civil Right expressed willingness to forego penalties for Health Insurance Portability and Accountability Act noncompliance among providers enacting in good-faith measures for telemedicine during the pandemic. [11] In an attempt to conserve PPE, avoid exposure for patients and clinicians, and limit both hospitalizations for non-covid reasons and outpatient office visits, an array of tele health care was provided to patients in inpatient and outpatient settings. The Heart Rhythm Society (HRS) /American college of cardiology (ACC) /American Heart Association (AHA) provided an early guidance for electrophysiologists on how to practice during the pandemic. It advocated for virtual visits, emphasize social distancing, conservation of PPE, minimize face to face encounters when possible. It also clearly addressed non-urgent/emergent procedures, protocols for performing procedures on COVID-19 patients. [12] Berman et al shared their experience of managing 29 inpatient electrophysiology (EP) consultations at the heart of the pandemic in New York. They were able to manage 55% of patients remotely and were able to provide guideline and evidence-based recommendations. [13] Similar reports from other specialties like OB/GYN in which they were able to provide tele-health to 1352 patients for prenatal care, of which 61.5% were maternal fetal medicine (MFM) visits. [14] Another pilot study was reported by Renner et al from Helsinki University Hospital in Finland. They performed 25 tele-rounds in 15 patients in the pulmonary ward. They concluded that tele-rounding is feasible in select COVID-19 patients and can improve health care workers safety and conserve personal protective equipment (PPE). [15] J o u r n a l P r e -p r o o f Whether the current exponential growth in tele-medicine will continue to grow after the pandemic is over is yet to be seen. Though with mass scale vaccinations being delivered globally and humanity seeking a return to normalcy, we do believe the unexpected outcome of COVID-19 is reliance upon digital health, which can be seen in forms like physical fitness, adherence to therapies, ordering medications and disease screening tools as part of smart phone/tablet apps.

We hypothesize that these adoptions may improve patient satisfaction, avoid long wait times in offices, avoid travel and discuss medical care at the comfort of their homes. A study by Han et al Reported that 60% of patients and 70% of clinicians would prefer to continue with virtual telehealth visits in future. [3] This concept will also aid busy specialist physicians who tend to cover multiples hospitals to make recommendations via digital visits, improve recommendation times, and eventually improve hospital length of stay.

Artificial intelligence (AI) has been incorporated into medicine for some decades now but its incorporation to modern day clinical practice is reaching new horizons with the start of the COVID 19 pandemic. AI refers to machine-based processing of data that typically requires human cognitive function. Machine learning (ML) is a subgroup of AI that uses algorithms to learn patterns empirically from data, it identifies nonlinear relationships and high-order interactions between multiple variables which often difficult to obtain via traditional statistics. Deep Learning (DL) which is a powerful ML approach that analyzes large complex data sets and enables efficient decisions. AI tools have brought about significant change in cardiac electrophysiology and cardiovascular imaging as well. It has shown promise in assisting in diagnosis, disease prediction models, and response to treatment and prognosis. [16] The concept of AI is not new in cardiac electrophysiology with automated EKG interpretations existing since 1970s.

[17] However, interpretation of EKGs relies on expert opinion and requires training and expertise. Algorithms for the computerized automated diagnosis of 12 lead EKGs in pre-hospital setting can really aid emergency medical personnel or non-specialist physicians to identify a condition and timely start treatment in high-risk patients. But current automated EKG J o u r n a l P r e -p r o o f diagnosis algorithms lack accuracy and results in misdiagnosis if not reviewed carefully. There has been substantial progress in these areas where ECG based deep neural networks (DNNs) have been tested to identify arrythmias, classify supra ventricular tachycardias and predict left ventricular hypertrophy. A study by Attia et al. which included 180,922 patients, in which AIenabled EKG during normal sinus rhythm (NSR) was able to identify atrial fibrillation (AF) with almost 80% accuracy. [18] Another good example is the study by Ko et al. where they used a trained and validated convolutional neural network (CNN) using 12 lead EKG was able to detect hypertrophic cardiomyopathy with a sensitivity up to 95%. We do feel that these DNNs models requires more refinement and validation but in future are likely to aid specialist and non-specialist with improved EKG diagnosis and perhaps as screening tools. [19] [20] [21] [22] Other dimension related to EKGs are the use of implantable devices, smart watches, and smart phone-based apps which can generate large amounts of data sets that is not amenable for manual evaluation. Arrythmia detection algorithms on DNNs on large sets of ambulatory patients with single lead plethysmography have shown similar diagnostic performance as cardiologists and implantable loop recorders. Continuous monitoring provides the opportunity to pick up asymptomatic cardiac arrythmias and overcome serious adverse events in future. [21] Electro-anatomic mapping in complex invasive EP procedures provides another opportunity. By combining data from diagnostic tools like MRI, fluoroscopy, previous electro-anatomical mapping can help identify arrhythmogenic substrates and decrease the invasive catheter ablation times.

There has been development of integrating fluoroscopy and electro-anatomical mapping with MRI is possible with ML.[23, 24] The above-mentioned examples provide a framework of tools in AI, but their wide scale validation and translation into clinical practice may not be that far away.

Some examples of EP specific innovation are described below 

Another great example in this association is the use of smart phone for EKG surveillance. In order to preserve hospital capacity during the pandemic. The idea was to empower primary care physicians and patients with appropriate tools to identify patients with concerns for clinical deterioration with stable COVID-19 infection. The study involved 21 primary care physicians who enrolled 521 patients. They were equipped with 8/12 lead hospital grade smart phone operated EKG device (D-Heart). First EKG was done under the supervision of the physician, and they were instructed to record at least one EKG at day four of infection or whenever cardiac symptoms were J o u r n a l P r e -p r o o f present during the first ten days of infection. EKG was evaluated 24/7 within 15 minutes of arrival via telecardiology platform by cardiologists. This is reported to be the first study of its kind and enabled primary care physicians for early detection and avoiding a worse clinical outcome. Study did conclude that the smart phone-controlled EKG devices are ideal for simple arrythmia assessments but may not be adequate for complex EKG evaluation. [26] Certainly, this methodology lays a nice platform for multi-parametric tele-monitoring for patients in the future with improvement and acceptability of tele-health. Patients were seen in office for the first 3 days of initiation of medication. [27, 28] Though larger cohorts may be needed to validate these findings, these studies do lay a good foundation and direction for future studies. This outpatient initiative not only decreases the risk of nosocomial infections including COVID-19 but also helps to decrease the cost burden by avoiding hospitalization of three days.

Cardiac resynchronization therapy (CRT) devices have now been incorporated in multiple studies with ML to predict end points like heart failure or death after CRT by using multitude of baseline J o u r n a l P r e -p r o o f variables. Heartlogic™ is a good example which is a personalized, remote heart failure diagnostic and monitoring solution, and has been validated to provide weeks of advance notice for early signs of worsening heart failure. [29] The ML models have outperformed current guidelines in predicting response and improved event free survivals although these findings are modest as this time. In other reports ML has been able to predict mortality better than pre-existing clinical risk scores. [30, 31] 

Virtual care and digital health were instrumental in care delivery during the pandemic. While cancellation of elective procedures and visits was the immediate response, creation of alternative digital solutions such as virtual telemedicine visits and remote patient monitoring measures represented a long-term viable strategy. [7] . However, this transition was far from seamless, and posed significant difficulties during its immediate implementation. Firstly, the resource burden from the Covid-19 pandemic required a prioritization of essential procedures, and with this in mind a return to full force in the post pandemic period can place additional strain on digital health care delivery given that it continues to be evolving in terms of familiarity and efficiency [32] .

Furthermore, the sheer volume of data inflow that can be expected with CIEDs, both medical and consumer-grade wearable monitors, and incorporated artificial intelligence tools can be overwhelming. This burden of increased data can present challenges to incorporation into clinical practice and can be overwhelming once in-person care returns to full volumes. Additional quality control parameters as some of the accuracy of some of these devices are still precocious [1]. Along with this data influx, an efficient and accurate triaging system must be in place, and AI tools, though improving, still lack this ability reliably [1]. In a comparative pre-and peri-pandemic survey regarding the changes in the digital health landscape among cardiac EP professionals, the most common barrier cited was a lack of infrastructure, which despite showing in improvement between the two surveys still remained a prominent problem even after reassessment and highlights the lag of a supportive framework despite advancements in digital health [3] . This must be taken into consideration with the reintegration of face-to-face encounters, and with the progression of digital health moving forward. Our familiarity with digital health and its limits is still expanding, although more specifically this puts us as providers in the impactful role to ensure digital literacy to our patients [33] . Though smartphone applications, digital wearable devices and J o u r n a l P r e -p r o o f virtual telemedicine appointments have served to further patient care, this comes with a learning curve for the user itself and makes providers the fulcrum of digital literacy education and patient advocacy in this area. Furthermore, these digital health solutions also serve both themselves as social barriers to health and can further highlight already present healthcare disparities [3] . Digital health usually requires access to Wi-fi, Bluetooth, and/or smartphones, which may not be routinely available to all patients. Patients in underserved or underrepresented populations and with socioeconomic barriers are experiencing a compounded gap in care [34] . Specifically, a multivariate analysis consisting of 148,402 patients who had either completed or missed telemedicine appointments revealed that age older than 55, Asian ethnicity, Medicaid insurance care, and Non-English speaking patients were most vulnerable to the digital divergence in care [35] . African-American and Latinx communities with household incomes of less than $50,000 had lower rates of video telemedicine visits compared to telephone visits, which could limit some of the offered video conference benefits such as medication reconciliations or virtual physical exams [35] . The demand, therefore, for more applications of digital health must also met with equal support for digital health equity, an equally vital social disparity in the current state of medicine [34] . Finally, a virtual move to collective educational platforms such as national and global health conferences has remained a topic of discussion, with some claiming its potential to reach a wider audience yet others highlighting the inability to provide hands-on experience, and interdisciplinary learning [32] . As vaccination efforts continue to curb the impact of the pandemic, and in-person patient care has been slowly reintegrating, resurgences can halt this process, and the supplementary role of digital health must be continually reevaluated. Finding a steady state in which overreliance is not placed upon digital health, while still utilizing these resources to extract as much patient data to complement face-to-face interactions is paramount. Figure 1 summarizes the flow of digital health in clinical cardiac electrophysiology.

Two main overarching factors will outline the future of digital health: digital health infrastructure and government policies for reimbursement [3] . Economics remains a fundamental driver for impacting changes in medical care. Centers for Medicare and Medicaid have responded with base billing code implementation and addition for telemedicine to encompass a wide spectrum and J o u r n a l P r e -p r o o f acuity of patient encounters, and it remains to be seen if other insurance carriers will follow this pathway, as well as if this continues to be fostered and expanded in the future [1, 32] .

Other improvements have come in the form of applicability and accessibility. The utilization of learning models such as Project ECHO (Extension of Community Healthcare Outcomes) is a collaborative multispecialty video conferencing program that aims to promote peer to peer, multidisciplinary learning to healthcare providers, as well as make them comfortable as a technology provider in the digital health landscape [36] . Furthermore, the advocacy seen from organizations such as Telehealth for Seniors, Inc., a Florida base nonprofit aiding in provision of digital health devices and education for seniors have emerged during the pandemic, as well as increases in telehealth platform funding from the Coronavirus Aid, Relief, and Economic Security (CARES) Act [3, 37] . These have contributed to the rise in accessibility to digital health, although these gaps in digital health disparity have not been bridged and advocacy for digital health equity must remain pressured [34] . Successful continued advocacy and resultant expansion of digital health can hope to present new telemedicine models to more remote areas and reach a wider spectrum of patients.

A further application of digital health in the future post-pandemic period will hope to focus on the impact of digital health on clinical research and, namely, its recruitment. Predating the Covid-19

pandemic, efforts such as the MyHeart Counts Cardiovascular and Heart eHealth studies utilized app-based recruitment and wearable monitoring devices to create larger cohorts and easier, prolonged periods of study [38] . Pairing this with the advancements necessitated in digital health, there is an optimistic outlook on the contribution of digital health tools in patient recruitment and ease of monitoring to contribute to higher cohorts in clinical research.

Electrophysiology serves as a fertile foundation for the incorporation of AI, and the ideal role it plays in the future is still budding. The hope for AI to assist in triaging and risk stratification in various cardiac diseases provides for an enticing outlook, and we can be hopeful that these advancements will continue to be cultivated, as their application currently remains limited.

New digital health innovations and an accommodating digital health landscape have shown promise during this pandemic, and we find ourselves as a field faced with the challenge of J o u r n a l P r e -p r o o f continuing to cultivate and incorporate this aspect of medicine. Consumer grade wearable monitors, AI triaging and diagnostic supplementary tools, and improved accessibility to technology mark some of the foreseen changes to the field of cardiac electrophysiology. This knowledge will allow us to focus on restructuring the comprehensive and traditional albeit resource intensive in person model of patient care, and hope to transition to a more efficient, patient centered, and communicative framework incorporating both digital health and the reincorporation of in person care moving forward.

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