Automating Health Information Audits Using Artificial Intelligence: Implications for Risk Management and Regulatory Compliance
DOI:
https://doi.org/10.32628/CSEIT2511653Keywords:
Artificial Intelligence, Health Information Management, Automated Auditing, Risk Management, Regulatory Compliance, Data GovernanceAbstract
The growing healthcare system digitalization has added to the regulations on healthcare systems, cybersecurity threat and continuous need of assurance on health information practices. Paper and rule-based health information audits are becoming more and more insufficient to meet the magnitude, depth, and speed of electronic health records (EHRs), insurance claims and compliance requirement. This paper discusses the potential of using artificial intelligence (AI) to automatize health information audits and evaluates the role of artificial intelligence in the context of risk management and regulatory compliance in healthcare organizations. Based on the latest sources in the field of healthcare audit, risk management, data governance, and AI governance, the study summarizes the existing AI-based forms of audits, such as anomaly detection, robotic process automation, and continuous monitoring systems. The paper also assesses regulatory issues associated with data protection, algorithmic transparency, and accountability within the framework of such standards as HIPAA and the developing standards of AI regulation. The results indicate that AI-based audit systems can positively affect the efficiency of the audit, the effectiveness of risk detection, and the effectiveness of compliance monitoring, yet can cause additional governance, ethical, and cybersecurity issues. The article ends with a set of practical recommendations to HIM professionals, auditors, and regulators on adopting AI based audit systems, maintaining effective data governance, risk controls, and regulatory alignment.
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