Discovery of Patterns to Improve Usability of Electronic Health Record Systems

Abstract

A majority of research efforts in the domain of Electronic Health Records concentrate on standardization and related issues. The earlier forms of medical records did not permit a high level of exchange, interoperability or extensive search and querying. Recent research has focused on the development of open standards for life-time long health record archives for individual patients. This facilitates the extensive use of data mining and querying techniques for the analysis. These efforts can increase the depth and the extent of the utilization of patient data. For example, association analysis can be used to identify common features among disparate patients to check whether diagnoses or procedures are effective. Pattern discovery techniques can also be used to create the census reports and generate a meaningful visualization of summary data at hospitals. For handling the large volume of data, there is a need to focus on improving the usability. The current study proposes a model for the development of EHR support systems. It aims to capture the health worker's needs in a scientific way, on a continuous basis. The proposal has been evaluated for the accuracy of knowledge discovery to improve the usability.