Title: Developing privacy solutions for sharing and analysing healthcare data

Authors: Luvai Motiwalla; Xiao-Bai Li

Addresses: Department of Operations and Information Systems, Manning School of Business, University of Massachusetts Lowell, Lowell, MA 01854, USA ' Department of Operations and Information Systems, Manning School of Business, University of Massachusetts Lowell, Lowell, MA 01854, USA

Abstract: The extensive use of electronic healthcare data has increased privacy concerns. While most healthcare organisations are conscientious in protecting their data in their databases, very few organisations take enough precautions to protect data that is shared with known third party organisations. Recently the regulatory environment has tightened the laws to enforce privacy protection. The goal of this research is to explore the application of data masking solutions for protecting patient privacy when data is shared with external organisations for research, analysis and other similar purposes. Specifically, this research project develops a system that protects data without removing sensitive attributes. Our application allows high quality data analysis with the masked data. Dataset-level properties and statistics remain approximately the same after data masking; however, individual record-level values are altered to prevent privacy disclosure. A pilot evaluation study on large real-world healthcare data shows the effectiveness of our solution in privacy protection.

Keywords: information privacy; data masking; data sharing; data mining; systems development; data analysis; healthcare data; electronic healthcare; e-healthcare; privacy protection; patient privacy.

DOI: 10.1504/IJBIS.2013.054335

International Journal of Business Information Systems, 2013 Vol.13 No.2, pp.199 - 216

Available online: 05 Jun 2013 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article