Can the theories of information and communication channels be used to explain the complexities associated with transformation of data into information, and information to knowledge?

Issue title: The Need for Innovations in Healthcare Systems Using Patient Experience and Advancing Information Technology

Guest editors: Varadraj P. Gurupur, Thomas T.H. Wan, Rama Raju Rudraraju and Shrirang A. Kulkarni

Article type: Research Article

Authors: Gurupur, Varadraj P.^{; *}

Affiliations: School of Global Health Management and Informatics, University of Central Florida, Orlando, FL, USA

Correspondence: [*] Corresponding author: Varadraj P. Gurupur, School of Global Health Management and Informatics, University of Central Florida, Orlando, FL, USA. E-mail: varadrajprabhu@gmail.com.

Abstract: In the world of health care in the last decade we have witnessed a continuous and exponential increase of electronic health data. This data has been harnessed by health informaticians to transform data into information and information is further transformed into knowledge. However, it is observed that all data does not get transformed into information. In this article the author attempts to discuss this concern from the perspective of a communication channel presented by the veteran computer scientist of the previous century Claude E. Shannon. A discussion on three different types of communications namely: a) human to human, b) human to machine, and c) machine to machine is provided. This discussion also includes the critical aspect of using different types of information entropy in estimating uncertainties associated with these communications. Additionally, the author also presents the identification of a particular communication channel and ascertaining its strength using conditional entropy. Overall, this perspective article makes a conscious attempt to initiate a discussion in the scientific community on this matter. The author believes that through this work we can bolster future innovations in this area of science and technology.

Keywords: Data, information, communication channel, information entropy, healthcare communication

DOI: 10.3233/JID-220010

Journal: Journal of Integrated Design and Process Science, vol. 27, no. 1, pp. 59-69, 2023