Abstract
Abstract
Background: Multiple digital technologies were used during and after the COVID-19 pandemic with an intent to improve quality of patient care. It has been seen that the perception of patients toward the use of digital solutions in clinical care varies significantly. This has also been attributed to varying levels of digital literacy among the health care professionals (HCP) involved in patient care.
Objective: Our paper aims to study the impact of digital literacy levels of HCPs, including hospital attendants and support staff who were involved in a clinical care team of COVID-19 patients, so that barriers toward the implementation of digital health solutions could be identified.
Methods: A standardized survey using responses based on Likert scale was developed, which measured the confidence levels of HCPs and their attitudes toward digital technologies. The survey consisted of questions from the Technology Acceptance Model as well as the unified theory of acceptancy and use of technology to assess the attitude of HCPs. A total of 100 Hospital attendants directly employed in patient care were enrolled in the study. They were also asked to respond to feedback received from patients on the perceived quality of care.
Results: Around 60% of the HCPs showed high digital literacy levels. Most respondents showed confidence in the use of technology. Moreover, around 20% of HCPs showed apprehension toward using digital solutions for direct patient care. A significant difference was found between study population with high digital literacy and perceived quality of care.
Conclusions: Our study found that poor digital literacy in HCPs adversely affects the safety and quality of patient care. It is important that institutions provide targeted education and training to not only doctors and nursing staff but also other support staff with low digital literacy levels and to boost their confidence in providing clinical care.
doi:10.2196/41561
Keywords
Conflicts of Interest
None declared.
Edited by B Dinesen; This is a non–peer-reviewed article. submitted 30.07.22; accepted 19.08.22; published 23.08.22
Copyright©Amitesh Khare, Kanika Jain, Vijay Laxmi, Puneet Khanna. Originally published in Iproceedings (https://www.iproc.org), 23.08.2022.
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