Detecting privacy-sensitive events in medical text

Prateek Jindal, Carl A. Gunter, Dan Roth
2014 Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14  
Recent US government initiatives have led to wide adoption of Electronic Health Records (EHRs). More and more health care institutions are storing patients' data in an electronic format. This emerging practice is posing several security-related risks because electronic data can easily be shared within and across institutions. So, it is important to design robust frameworks which will protect patients' privacy. In this report, we present a method to detect security-related (particularly drug
more » ... e) events in medical text. Several applications can use this information to make the hospital systems more secure. For example, portions of the clinical reports which contain description of critical events can be encrypted so that it can be viewed only by selected individuals. There are several types of sensitive data that are found in the clinical narratives. We categorize the sensitive data into 5 major types below:
doi:10.1145/2649387.2662451 dblp:conf/bcb/JindalGR14 fatcat:z2kos2333rgadnrk6h2zxsuinu