Abstract

Large-scale unexpected events, such as the COVID-19 pandemic, have accelerated the virtualization of processes across many industries, including healthcare (Ayabakan et al., 2024). Due to arrangements such as social distancing and remote work life changes, telehealth and telemedicine-based services became more ubiquitous after the pandemic. Telehealth is the use of electronic information and telecommunication technologies to support long-distance clinical health care, patient and professional health-related education, health administration and public health (Adler-Milstein et al., 2014). Additionally, geographic healthcare disparity has been a long-standing global social problem, and telehealth has bridged barriers to improve health resource disparity without requiring physical relocation of healthcare providers. Despite the many advantages of telehealth expansion, these clinical systems require prioritization of cybersecurity strategies to prevent cyber-attacks and safeguard employee health information. Telehealth poses unique security risks unlike conventional healthcare, with teams operating across varied security environments, non-specialists managing multiple devices, and real-time data exchange requirements. Some of these attacks include ransomware, phishing, denial of service (DoS), malware, and password attacks, among many others. Healthcare data is highly sensitive; cyber breaches cause unquantifiable reputational, legal and financial damages. As a result, we posit that cybersecurity compliance of telehealth teams alone is not enough - we seek to examine their resilience. We define cybersecurity resilience as a team's ability to anticipate, withstand, comply with, and recover from cyber threats, focusing on adaptability and continuity, such as restoring systems after a breach. We seek to examine the impact of human factors through the lens of cognitive load theory (Sweller et al., 2019) and the moderating role of security fatigue. We will use a survey approach to assess team cybersecurity resilience through intrinsic, extrinsic, and germane cognitive loads, moderated by security fatigue. For generalizability, we will include telehealth workers across all roles, including IT staff and clinicians. Data will be collected from telehealth teams across different regions to account for variability in cybersecurity practices. We will use structural equation modeling (SEM) to analyze the relationships between these factors. This research will contribute to the cybersecurity compliance, resilience, and telehealth adoption literature.

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