Assessing Information Confidentiality in Telemedicine Platforms Using Public Web Data: A Case Study of Persian Televisit Websites.

Background: The shift from traditional office visits to internet-based care has accelerated during the COVID-19 pandemic, increasing reliance on telemedicine platforms. This growth has led to more health-related electronic data and heightened risks of unauthorized access, making it essential to prioritize information confidentiality issues. This study aims to reveal the disclosure of confidential information on a Persian televisit website. Methods: In this observational case study, we gathered public health-related electronic data from a Persian televisit website in 2022. SAS software was used to harvest messy data about patients and doctors and create a structured dataset. Meanwhile, Microsoft Excel and RStudio software programs were used for data visualization. A hashing algorithm was applied to encode personal information, preventing the identification of individuals. Results: Our study showed how public web data about 263 patients and 194 doctors, harvested from the target website, can be used to reveal patients' private information. Using such data, we explored the patient-doctor interaction patterns. With access to the patients' identifiable information, we recognized the identity of the clients who received internet-based care services and their possible diseases. Conclusion: This analysis revealed that exposure of patients' confidential information could compromise their identities and underlying medical conditions. This highlights the need for a national framework to ensure the security of health-related electronic data. Health authorities should enforce comprehensive laws, while the owners of televisit websites should implement privacy by design principles into the development of such platforms to prevent the disclosure of sensitive information.