Objective Ensuring the security and appropriate use of patient health information contained within electronic medical records systems is challenging. Observing these difficulties, we present an addition to the explanationbased auditing system (EBAS) that attempts to determine the clinical or operational reason why accesses occur to medical records based on patient diagnosis information. Accesses that can be explained with a reason are filtered so that the compliance officer has fewer suspicious accesses to review manually. Methods Our hypothesis is that specific hospital employees are responsible for treating a given diagnosis. For example, Dr Carl accessed Alice's medical record because Hem/Onc employees are responsible for chemotherapy patients. We present metrics to determine which employees are responsible for a diagnosis and quantify their confidence. The auditing system attempts to use this responsibility information to determine the reason why an access occurred. We evaluate the auditing system's classification quality using data from the University of Michigan Health System. Results The EBAS correctly determines which departments are responsible for a given diagnosis. Adding this responsibility information to the EBAS increases the number of first accesses explained by a factor of two over previous work and explains over 94% of all accesses with high precision. Conclusions The EBAS serves as a complementary security tool for personal health information. It filters a majority of accesses such that it is more feasible for a compliance officer to review the remaining suspicious accesses manually.
Considering the difficulties of ensuring the security and appropriate use of patient health information contained in medical records, an explanation-based auditing system (EBAS) REF was proposed to distinguish the clinical or operational reasons and present metrics to determine which hospital employees are responsible for treating a given diagnosis.
Explaining accesses to electronic medical records using diagnosis information
Journal of the American Medical Informatics Association : JAMIA
Journal of the American Medical Informatics Association : JAMIA
Computer Science Medicine