How can population health improve through data analytics?

We’ve talked about how data analytics has the potential to improve the lives of individuals on the Permea blog before, but how exactly can this concept influence population health as a whole? In this blog post, we’ll explore the ways in which these small actions add up, and how analytics can affect public health on a much wider scale.

We all know that prevention is better than cure, and insights derived from data analytics offer healthcare providers with a unique opportunity to address issues with at-risk individuals before they require further intervention. By stopping certain conditions or diseases from developing, individuals are better protected, causing less strain on healthcare services and benefitting the system as a whole. 

Although this might seem relatively obvious, there are certain aspects of the data analytics model that can support expansion of health equity, tackling the growing problem of medical deserts. Defined as an area in which the local population does not have adequate access to sufficient or appropriate healthcare services, the prevalence of medical deserts has only increased throughout the course of the COVID-19 pandemic, with many flaws in the existing system exposed. The vast majority of these pockets of inequity are found in rural areas, with millions of people across the globe living in regions at least a sixty minute drive from a hospital with trauma care services. 

This is where data analytics steps in. By collecting relevant data and analysing the current state of affairs, healthcare providers are able to highlight at-risk populations and offer unique solutions to tackle this issue, while also monitoring progress and developments once these suggestions have been taken into account. For areas in which physical care facilities are not deemed realistic due to infrastructure difficulties – such as practical geographic issues, or a particularly small local population - an expansion of telehealth services based on real-world evidence might be a suitable model, with many remote regions having already benefitted from their introduction over the past two years.

Addressing and filling gaps in the current system isn’t going to happen overnight, and there will be a number of prominent issues that need to be overcome. That being said, the widespread implementation of data analysis by healthcare providers is improving care itself – providing better quality and more accurate services, based on insights drawn from concrete data and patient feedback.

Data analysis allows us to see the bigger picture when it comes to generating a better understanding of population health, creating a more developed and nuanced level of public health intelligence. Existing systems have long been under pressure - something the gradual introduction of evidence-based insights will be able to ease, encouraging a shift to a more proactive and sustainable way of approaching these problems.

There’s a substantial and well-documented connection between public health outcomes and individual action. By offering tangible solutions to the many challenges presented by health inequity, it’s becoming increasingly clear that data analytics holds the key to a sustainable future within the healthcare sector.

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