COVID-19 has not only disrupted lives, economies and industries; it has been the most significant disruption to the global healthcare industry, triggering an unprecedented transformation. The pandemic accelerated the already growing reliance on healthcare data-based technologies. As a result, healthcare providers are now asked to aggregate more data sources to create accurate diagnoses, treatment plans and strategies.
The start of a transformation
In the Asia Pacific, we are leveraging data to provide accurate and reliable statistics. SafeEntry, an initiative by the Singapore government, is a digital check-in system that logs individuals visits to prevent and control the transmission of COVID-19 through contact tracing. The distribution of TraceTogetherToken was also followed by the new mandate requiring participants to have a TT App or Token to conduct SafeEntry check-in for larger-scale business-to-business (B2B) events.
Even though the current pandemic does not measure the extent of change, digital healthcare will continue to evolve. We are seeing the beginnings of this transformation, which is expected to change business, clinical and healthcare delivery processes even after the pandemic. There are already some early examples of how robotics can meet our healthcare needs, from measuring blood to taking temperatures. But these new techniques will require a real paradigm shift, putting the use of data, whether old or real-time, at the forefront.
Teleconsultation, for example, is experiencing astronomical growth as we speak, with a rate of 300 to 500%. The adoption of remote monitoring now allows healthcare teams to monitor, manage and engage patients while leaving them in the comfort of their own homes. Physicians can use a large amount of potentially useful information to compare or analyze patient data.
For high-risk individuals, care coordinators are relying on teleconsultation and remote monitoring to reduce the number of patient visits to their offices, while ensuring better patient outcomes and reducing costs. Of course, it will require an organization to ensure that the use of patient data remains a benefit and not a risk, which implies a strong ethical imperative.
Data at the forefront
From a technical point of view, one of the main obstacles encountered was the availability of test kits. It took days to collect the samples, process and send them to overwhelmed diagnostic suppliers, then wait for the results and communicate them to patients, further compounded the problem. Many patients who were positive deteriorated and had to be admitted to intensive care units and emergency departments, overloading hospitals.
Fortunately, healthcare leaders and startups have responded to this crisis by offering AI-based applications. These applications reside in the cloud and can be deployed on mobile devices. Many of these applications can capture and store patients' vital signs on online portals for instant access by healthcare teams.
At a different level, another challenge was the lack of preparedness for the pandemic, which culminated in a different crisis by region. In the future, opinion leaders in the healthcare field will likely establish pandemic and epidemic surveillance and response centres as part of their strategic scenario and policy planning initiatives, even at the health system level.
Equipped with data feeds from government health agencies, self-service analysis tools, these leaders will create "war rooms" that will not only monitor outbreaks and diseases in other parts of the world, but also provide useful information through visual analysis dashboards that will proactively monitor, analyze and measure both demand and supply-side implications.
The power of insight
In light of all these new challenges, healthcare leaders see tremendous potential for analytics to deliver on the promise of better quality care at lower cost by empowering their executives, leaders, clinicians and nurses to harness the power of predictive and prescriptive analytics. Many healthcare organizations are looking to harness the vast potential of AI and its four components: ML, natural language processing (NLP), deep learning and robotics - to transform their clinical and business processes.
They seek to apply these advanced technologies to make sense of an ever-expanding tsunami of structured and unstructured data, and to automate iterative operations that previously required manual processing. The social distancing imperative has also seen the advent and deployment of medical robots for new applications, ranging from capturing vital signs, acting as a means or intermediary for telehealth, to food and drug distribution - a promising area of AI innovation that is gaining momentum this year.
2020 will be a pivotal year for the healthcare world, which has painfully realized the importance of data in this and other areas and yet will grow from this realization. As the complexity of data increases, it is imperative to adopt both descriptive and predictive analysis, while learning ML and NLP to obtain the necessary information. However, we will need to be able to ask the right questions, so that advances in technology do not come at the expense of ethics.
Julian Quinn, Senior Vice President of APAC, Alteryx authored this article.
The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/Natee127