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The Importance Of Data Analysis In A Healthcare Setting

Updated: May 8

There’s a lot of technology available these days that can deliver all sorts of benefits, no matter what industry you’re operating in, but something that can make a huge difference to organisations in the healthcare sector is data analysis.


A significant amount of data is generated by the industry and this can all be used to drive deeper insights for patient outcomes, patient care, operational efficiencies and more.


Data analysis is ideal for helping healthcare professionals respond quickly to changing health environments (like a global pandemic), as well as helping to improve disease research and prediction, early detection, automated administration, new drug discoveries, personalisation of patient care, more efficient data sharing and so on.


In a clinical setting, for example, data analytics can be used to reduce waiting times, reduce readmission rates by predicting the most at-risk patients and also give people more options for appointments.


The process involves examining raw data to identify trends, identify areas ripe for improvement and gain macro and micro insights using current and historical information to help support decision-making across the board.


What has been interesting about the last two years is that the covid-19 crisis has really driven adoption of data analysis and predictive models - and it’s likely that this trend will continue now and well into the future.


Ultimately, it comes down to patient outcome and patient care, and data analysis can really help deliver in this regard.


If you’d like to find out more about RTT and Non-RTT (Follow-Up) validation in the NHS, get in touch with Source Group today.

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