Healthcare

How can data analytics improve health equity?

It’s no secret that there are a multitude of issues when it comes to ensuring equitable and fair access to quality treatment within the healthcare sector – for a variety of different reasons – and the ongoing COVID-19 pandemic has brought many of these problems to light. In this blog post, we’ll explore how key players in the pharma and medical industries can harness the power of data analytics to improve the current state of affairs, ironing out existing flaws in the process and moving one step closer to making healthcare accessible to all.


COVID-19 has obviously put huge amounts of pressure on healthcare systems and providers, exposing a large number of disparities based on a variety of factors, including but not limited to socio-economic status, location, age, and racial and gender identity.

Data analytics has contributed significantly over the course of the past decade to improving patient outcomes, breaking down some of the barriers that exist in today’s healthcare system – but there’s still a lot of progress to be made. It’s been of particular use during the COVID-19 pandemic, allowing healthcare providers to prepare effective responses based on insights derived from the analysis of data across different spectrums of the scientific community.

In theory, there’s no reason why the power of analytics can’t help to solve the inequity crisis – but data first needs to be made accessible and actionable for key players in the medical care industry. When it comes to leveraging data for these purposes, considering the importance of mitigating sources of potential bias in analytics is paramount. Inherent bias in sourced data often gets reinforced the longer it goes undetected, and ensuring an organization is monitoring the maturity of its AI framework will help to keep issues like this in check.

Additionally, ensuring that the data of diverse populations is included throughout the analytics process is crucial – it’s hugely important to consider all the different types of data sources before conducting an in-depth analysis. By combining a variety of data sources, it’s far more feasible for analysts to guarantee and verify the accuracy of the information they’re dealing with, resulting in data that’s simply more reliable.

A solutions-oriented approach to medical equity is entirely possible, with patient-reported data playing a major role in its development. By listening to what patients have to say and considering their opinions, the healthcare sector is putting the person who matters most back into the center of it all. Highlighting the invaluable information derived from these types of data sources and applying these actionable insights at a population level will enable everyone from data analysts and medical researchers to healthcare providers to make real progress in closing the equity gap across the patient care spectrum.

When used responsibly and ethically, data analytics has the potential to make big changes in the healthcare sector by targeting inequities and reducing disparities, and we shouldn’t’ underestimate it. There are many significant and substantial challenges when it comes to the practicalities of improving healthcare multi-dimensionality, and only by overcoming these will the healthcare industry be able to fully realize the benefits and advantages this innovative technology can offer us.

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