{'fraction_non_alphanumeric': 0.010933557611438183, 'fraction_numerical': 0.0, 'mean_word_length': 5.2631578947368425, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Big data in healthcare research - how can we address public concerns of privacy

Big data is an emerging technological field that encompasses massive datasets. Its role in the healthcare field is currently being explored and has the potential to greatly improve healthcare and disease surveillance through pattern analysis of health data. Concerns had by the general public focus primarily on potential breaches of privacy and confidentiality of patient medical health records in the context of research. These concerns relate to the innate characteristics of big data, such as large size and fast data acquisition speed, which increases the risk of breaching confidentiality. Therefore, it is important for physicians to be mindful of privacy concerns and maintain trust as big data becomes more prominent. Doing so is a key factor in building public trust in the use. Understanding strategies and limitations of current practice standards will allow physicians to build on existing guidelines to incorporate the rise of big data. This means prioritizing privacy when handling big data through anonymization, creating safe havens and promoting dynamic informed consent practice standards.