A Metaphoric Design of Electronic Medical Record (EMR) for Periodic Health Examination Reports: An Initiative to Cloud's Medical Data Analysis

Introduction

With the advent of cloud computing (Bhushan & Gupta, 2019), a rich collection of electronic medical data of patients is now readily available (Al Hamid et al., 2017). Although, a large amount of such data is publicly accessible (Ali, 2019; Dom, 1995; Olakanmi & Dada, 2019), the interpretation of medical records is quite challenging and cumbersome for the common people to have an explicit understanding of medical reports results (Jing et al., 2018; Liu et al., 2018). The medical terminologies are quite difficult for the non-medical people to understand. The machine intelligence has bestowed obvious benefits to people in many sectors of life including the medical areas (Rajkomar et al., 2018). Today, several intelligent and Cloud based solutions exist (Hogenboom et al., 2008; Meimaris et al., 2017; Yadav & Sohal, 2017). The diagnosis of different diseases can be prescribed with the medicines to patients based on disease symptoms. Despite the existence of such solutions, the automatic interpretation of medical records against the medical reports of patients has not been discovered at a satisfactory scale (Abd EL-Latif et al., 2020; Choi et al., 2016; Tou et al., 2018).

Periodic Health Examination (PHE) is a medical checkup of healthy individuals performed at variable intervals depending upon the age of the individual (Hughes et al., 2018; Yu-Hin Siu et al., 2016). The primary objectives of the PHE are to identify risk of diseases at an early stage, to detect diseases that have no apparent symptoms, to provide advice to individuals for primary prevention of diseases and to counsel them for promotion of a healthy lifestyle. Result of this checkup is shown as tables in a report with test names and result values in addition to the normal range that the result value should fall within (Ridley et al., 2016; Yu-Hin Siu et al., 2016). In order to free the individuals from the medical jargon and values, it is important to present these reports in a more human friendly way. One of the best ways to enhance the perception of such reports is to represent them graphically. Graphical representation makes it easier for the individuals to understand the medical information with no need to have a medical background (Asnicar et al., 2015; Choi et al., 2017).

Many graphical representations can be used to support the written material or to represent the information itself. One of these graphical representations is using metaphors; the fundamental concept by which information is easily recognized, understood and remembered (Lvovich, 2012). Most commonly, metaphors create connections between concepts that are already familiar to a person and new concepts, with the aim of helping the person understand something about the new concepts using their existing knowledge of the world. In user interfaces context, the system matches the real world in terms of association with familiar physical objects and following the human logic (F. Chen et al., 2016; Gurjar et al., 2016; Hensen, 2020). Metaphorical user interfaces are being widely adopted to enable people to take advantage of their experience in the real world when interacting with digital information (Cheong et al., 2020; Döring, 2016; Kratky, 2016; Torres-Cardona et al., 2019).