Revolutionizing Regulatory Compliance in Healthcare with Artificial Intelligence (Published)
The healthcare industry faces a significant challenge in maintaining regulatory compliance due to the constant changes of state and federal mandates. On average, more than 40 new mandates are issued each month per state alongside approximately 1 to 7 federal mandates, creating significant challenges for healthcare providers, payers, and other stakeholders. Manually tracking, interpreting, and implementing these changes is a complex and resource-intensive process, making it difficult for organizations to maintain full compliance [1, 2]. In 2022 alone, healthcare providers faced over 600 new and updated regulations, with significant fines and penalties for non-compliance [3]. Non-compliance can result in huge penalties, operational disruptions, and reputational damage [8]. This article explores how Artificial Intelligence (AI) can automate the compliance process, ensuring 100% adherence to regulatory requirements. We discuss the challenges of manual compliance, evaluate various Large Language Models (LLMs) for their effectiveness in detecting policy changes, and outline the implementation process for AI-driven solutions.
Keywords: Artificial Intelligence, Healthcare, revolutionizing regulatory compliance
Towards Integration of Ontologies in Healthcare (Published)
Digital health is facing many challenges. Nowadays the use of ontologies in health care has increased and is covering wide range domains in healthcare. Using ontologies may improve the semantic interoperability and also offer the possibility to gain knowledge from them. It is significantly important not only to implement ontologies in healthcare but to integrate them in order to benefit from different ontologies. In this paper, we provide a comprehensive overview of the importance, advantages and challenges in integrating ontologies through a semantic mapping scenario between two ontologies. Integration of ontologies may support the decision-making process of healthcare providers by deriving relationships between different sets of conditions, findings, signs or symptoms.
Keywords: Healthcare, Integration, Mapping, Ontology