Evaluating the Influence of Healthcare Employee Behavior on Cybersecurity Vulnerabilities in Medical Systems
Praveen Priyaranjan Nayak, K. Jamuna, Swati Kemothi · Seminars in Medical Writing and Education · 2023
Healthcare organizations, in particular, are prime targets for cybercriminals due to the data’s sensitive nature of the data managed and the complex Information Technology(IT) infrastructure relied upon. Healthcare IT systems are particularly vulnerable because numerous employees interact with patient information daily, often without sufficient awareness of cybersecurity risks. Given the significant influence of human behavior on healthcare IT infrastructure, this research investigates how healthcare employee behaviors contribute to cybersecurity vulnerabilities in medical systems. A quantitative approach was employed, collecting data from 325 healthcare staff via an online survey. The research utilized several statistical techniques, including descriptive statistics, correlation analysis, and regression modeling, to observe various work-related factors. These techniques were applied to identify gaps in information security (IS) knowledge, attitudes, and behaviors among healthcare employees. The results revealed that work-related stress; Work emergency (WE), perceived workload, lack of training, and insufficient organizational support were positively correlated with risky security behaviors. Furthermore, personality traits such as conscientiousness and agreeableness significantly influenced employees’ security practices. Conscientiousness was found to be associated with higher cybersecurity risks, while agreeableness was linked to a lower risk of deficiencies in security knowledge and attitudes. Hypothesis were developed, with H1 and H2 being well supported by the findings. Based on these findings, the research suggests that addressing both intrinsic and extrinsic motivations, improving organizational support, and integrating advanced technological solutions could help mitigate cybersecurity vulnerabilities stemming from employee behaviors in medical systems.