With over 130,000 COVID-19 cases in Australia, the healthcare industry has been working diligently to find new ways to curb the spread of the disease and ensure better health for the population.
As a result, the healthcare industry has become more reliant on data analytics than ever before.
While data analytics has always played some part in the healthcare industry, after the COVID-19 pandemic, the data analytics landscape for the healthcare industry has broadened, and new avenues for big data analytics have come to light.
The pandemic has resulted in a dynamic environment that keeps delivering new revelations related to the pandemic and a multitude of new healthcare options for keeping people safe. Healthcare data analytics models have to change and adapt rapidly to keep up with this dynamic environment.
In this post, we explore how healthcare data analytics has changed post-COVID-19 and what this could mean for the future.
The healthcare industry has become increasingly reliant on the use of IoT technologies such as wearable sensors and monitors that help keep track of COVID-19 patients and to monitor the health of individuals who are suspected of having the disease.
These devices collect and transmit an ocean of data, which—with the help of data analytics—healthcare professionals can use to gain insights that help identify areas of improvement in healthcare facilities
For instance, with the help of advanced algorithms and artificial intelligence, medical professionals can have better insights into the logistics involved in deciding which patients need treatment more urgently and determining the most effective ways to treat them.
Businesses across industries quickly realised that the war against COVID-19 can’t be won by fighting alone.
As a result, many industries formed alliances to find solutions to bring the effects of the pandemic under control. The health industry itself started working with organisations from different industries for this very reason.
For example, by partnering with a virtual drug discovery platform provider, healthcare professionals and institutes like Harvard Medical School were able to use data analytics to compare the efficacy of drugs against COVID-19 proteins, which helped find new treatment options.
With these collaborations, the healthcare industry is receiving large amounts of data, which can fill the gaps in their understanding of the current pandemic situation and future approaches to healthcare.
The pandemic had made it clear how critical collaborations are for the healthcare industry to leverage its data analytics capabilities.
Telehealth was offered as a convenient alternative to traditional healthcare systems, allowing people to connect with medical specialists remotely.
Today, telehealth has become a common standard due to social distancing laws. Even in a post-COVID scenario, telehealth is used by many people because of its convenience.
Due to this, there is an urgent need to improve the capabilities of telehealth platforms, and Big data analytics has become a crucial tool in this process.
Healthcare analytics systems use big data to analyse patient information for a more accurate diagnosis.
Big data can also help improve communication between telehealth providers and patients, making telehealth more intuitive and user-friendly.
Data analytics once played a moderate role in healthcare, but post-COVID, it has evolved and opened new opportunities for improving treatments, diagnosis, and relationships with patients.
If you work in the healthcare industry and are looking to leverage your data analytics capabilities, our Selerity analytics desktop is what you’re looking for.
This is the ultimate platform for managing your SAS ecosystem and enhancing your SAS experience.
Get in touch with the Selerity team for more information.