Evaluating the Impact of Telemedicine Through Analytics: Lessons Learned from the COVID-19 Era

Abstract

The COVID-19 pandemic left a yet unseen paradigm shift in the international healthcare delivery and telemedicine has become its lifeline to guarantee the continuity of care under lockdowns, social distancing requirements, and the health systems overwhelmed. As the use of telehealth services became ramped up, concerns about the efficacy of their use, equity of their use, and their sustainability soon followed. This article examines how data analytics have successfully been applied in measuring the outcomes of telemedicine in the light of COVID-19 pandemic providing a multidimensional analysis in a manner that assesses the outcomes in terms of clinical, operational, and social-economic factors. Using descriptive, predictive and prescriptive analytics, healthcare organizations and policymakers could crunch data matrices that covered a sea of electronic health records (EHRs), insurance claims, wearable health apps for fitness trackers and patient feedback sites. These instruments allowed us to achieve a very detailed picture of the trends in the use of telemedicine as well as clinical efficacy in treating chronic and acute diseases without being physically present and the level of patient satisfaction. The Centres for Disease Control and Prevention (CDC) claimed that compared to those of the same month of 2019, telehealth visits rose by 154% in March 2020 in the U.S. In addition, McKinsey & Company report observed an increase in the number of consumers interested in telehealth, with 76% reporting interest in using telehealth as compared to 11% before the pandemic. One of the central directions is the application of analytics to analyse telemedicine access inequalities. It has been revealed by the pandemic, as the digital divide which is driven by social-economic advantages of individual, geographical, racial and age-related disadvantages were manifested more clearly than ever. Researchers found that 38% of low-income families in America had access to dependable internet access, which subordinates fair digital access to virtual care to a large extent. The analytics were important to recognize these disparities and implement policy interventions specially geared towards them. The practical results like a 20% decrease in the levels of no shows and better triaging processes only confirm the promise that telemedicine holds under the influence of data. The analysis of case studies of the US, India and other countries is provided, where various healthcare systems used analytics to achieve telehealth optimization and real-time decision-making.