CHAPTER 13OPTIMIZATION OF ONTOLOGY-BASED CLINICAL PATHWAYS AND INCORPORATING DIFFERENTIAL PRIVACY IN THE HEALTHCARE SYSTEM
SOUMYA BANERJEE1, RACHID BENLAMRI2, SAMIA BOUZEFRANE3
1Birla Institute of Technology, Mesra, India
2Lakehead University, Thunder Bay, Ontario, Canada
3CEDRIC, Conservatoire National des Arts et Métiers, Paris, France
Abstract
The inception of ontology-based clinical pathways significantly enhanced the benefits of healthcare, especially for chronic diseases, by envisaging the dynamic attributes of medical care and standardize treatment behavior in order to control and finally reduce the cost of healthcare. The system is expected to be more personalized and thus the heterogeneous data sources of clinical pathways also demand decent risk classification of sensitive data of patients. This chapter introduces a holistic approach to ensure such data protection by incorporating differential privacy of sensitive data in the healthcare system. The chapter presents a relevant algorithm for the proposed model. The functional model is described and performance comparison is given with respect to conventional clinical pathway (CP) model with optimization of state chart (optimal cluster of CP), and data privacy measure through machine learning is also elaborated.
Keywords: Clinical pathways, optimization, health services, differential privacy, machine learning
13.1 Introduction
With the increase of chronic diseases and an aging population, ...
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