Pandemic tele-smart: a contactless tele-health system for efficient monitoring of remotely located COVID-19 quarantine wards in India using near-field communication and natural language processing system

Abstract

Efficient remote monitoring of the patient infected with coronavirus without spread to healthcare workers is the need of the hour. An effectual and faster communication system must be established wherein the healthcare workers at the remote quarantine ward can communicate with healthcare professionals present in specialty hospitals. Incidentally, there is a need to establish a contactless smart cloud-based connection between a specialty hospital and quarantine wards during pandemic situation. This paper proposes an initial contactless web-based tele-health clinical decision support system that integrates near-field communication (NFC) tags and a smart cloud-based structuring tool that enables the quick diagnosis of patients with COVID-19 symptoms and monitors the remotely located quarantine wards during the recent pandemic. The proposed framework consists of three-stages: (i) contactless health parameter extraction from the patient using an NFC tag; (ii) converting medical report into digital text using optical character recognition algorithm and extracting values of relevant medical-parameters using natural language processing; and (iii) smart visualization of key medical parameters. The accuracy of the proposed system from NFC reader until analysis using a novel structuring algorithm deployed in the cloud is more than 94%. Several capabilities of the proposed web-based system were compared with similar systems and tested in an authentic mock clinical setup, and the physicians found that the system is reliable and user friendly.

Keywords: Clinical decision support systems; Electronic medical records; Mobile health; Remote consultation; Telemedicine.

Fig. 1

The clinical workflow of the proposed pandemic tele-health system with comparison of conventional workflow

Fig. 2

The process flow of the proposed cloud-based pandemic tele-health system in which the patients are to be monitored at a mobile and a remote quarantine ward

Fig. 3

The process of uploading of medical records to the database by the healthcare worker at the mobile quarantine ward by reading the patient’s NFC tag

Fig. 4

Steps involved in “keywords” extraction from the medical report, which was converted into text files from image format using OCR

Fig. 5

Extraction of “parameter values” for each medical data through keyword detection and neighbor search algorithm

Fig. 6

Identification of various keywords from narrative text of the medical reports uploaded using POS tagging algorithm and represent as tabular data for ease of reading and adding them to the EMR database

Fig. 7

User interface design of the proposed application on the quarantine ward end to capture and upload clinical parameters and send to a specialty hospital

Fig. 8

User interface design of the proposed application on the specialty hospital end where medical data are structured and displayed in tabular form, whereas the images can be either viewed or downloaded

Fig. 9

Smart decision support feature in the application plots key health parameters. The plotting feature enables the doctor to track the variations in a particular medical parameter reading taken at different time intervals

Fig. 10

Visualization of structured data obtained by proposed smart structuring tool on the specialty hospital end

Fig. 11

Messaging applet built within the web application to empower communication between the quarantine ward and the specialty hospital. The applet has an inbuilt smart answer suggestion system enabling faster and easier communication on both the ends