Abstract:
Health information exchanges (HIEs) are an important part of the healthcare system. The
World Health Organization emphasizes the importance of security standards in managing
personal health data, as privacy concerns among healthcare consumers are increasing. HIPAA
prioritizes unauthorized disclosures, improper disposal, access, and other IT security and
privacy breaches of protected health information (PHI). The study demonstrates secure health
information sharing methods, ensuring trust and patient privacy through AES-128-CBC and
VSS-XOR, and integrating authentication, authorization, and access control with attributes for
user tracking. We perform further comparative analyses based on the visual cryptography in
LSB and DWT algorithms. PSNR results describe the similarity between the recovered secret
image and the original image. The novel health data sharing method using Named Entity
Recognition (NER), NER BiLSTM, provides 94% more accurate PII prediction than current
evidence on medical text prediction. The differential privacy application evaluates noise
levels to protect patients' privacy by removing or replacing patients and was compared using
word2vec and GloVe 300-dimensional embedding approaches. Word2vec performed better
semantically, while GloVe outperformed due to its support for a wide range of epsilon values,
ensuring patient privacy. The effectiveness and viability of the suggested scheme are
demonstrated by experiments and comparisons of the metrics. It is demonstrated that our
suggested scheme can withstand statistical analysis and counterattacks. By combining legal
agreements and technology to ensure meaningful information exchange, our developed
protocol complied with information security and HIPPA privacy basic rules
