Can data analytics transform the healthcare sector post-pandemic?

It’s not exactly surprising that the ongoing COVID-19 pandemic has fundamentally changed not only how we as a society view our health, but also the healthcare sector itself. In this blog post, we’ll explore the different ways in which attitudes towards data analytics and artificial intelligence have shifted over the course of the past two years, and how the industry is embracing these new approaches to improve quality of care and boost equity.

Data analytics in healthcare isn’t the newest concept: it’s been around for some time, but to varying degrees, with a stronger focus on drug development and the clinical trial process rather than everyday patient care. There are several reasons as to why the latter hasn’t historically been viewed as a priority, but recent global events have led to a big shift in approaches towards individual treatment.

Healthcare providers have been presented with a unique opportunity to identify areas for development and growth in terms of implementing data analytics solutions. High-quality analytics are essential for organizations to create a 360-degree picture of their clients, customers, and patients. We’ve already been seeing hints towards this - with the adoption of telehealth services as a solid starting point – but there are a number of ways in which data analytics is set to benefit the sector post-pandemic.

Across the globe, we’re witnessing organizations leverage the power of data analytics, improving health equity and the overall quality of and access to treatment - through a multitude of initiatives such as telehealth services - whilst also exploring different aspects of the drug development process. Up until now, the patient hasn’t necessarily always been at the center of healthcare, with individual thoughts and opinions pushed to one side in order to make way for clinical preferences and one-size-fits-all blockbuster solutions. Although there is some sense to this, the past two years have caused a substantial shift in how we view our health, with many healthcare providers recognizing the fact that personalized medicine is on the rise. 

Data analytics offers a wealth of opportunities for organizations looking to reconfigure the way in which patients are considered not just once the drug itself comes to market, but throughout the entire clinical trial process. There are myriad ways in which the implementation of data analytics can streamline this stage in the drug development story, making the product candidate cheaper, more effective, and more in line with patient wants, needs, and expectations.

Of course, all data analytics solutions come with their own unique set of challenges, which might seem a little intimidating when first toying with the idea of establishing data analytics solutions. That being said, the opportunities provided by these exciting new ideas far outweigh any potential concerns surrounding their employment at the beginning of the process. 

With the appropriate advice and support networks in place, installing a data framework that meets the needs specific to an organization is a lot more straightforward than might first be anticipated. There’s huge potential for change when it comes to data analytics in the healthcare sector, especially considering the needs faced by businesses adapting to a post-pandemic future.

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