3 Ways to Apply Big Data Analytics for LSS Improvements in Healthcare

Big data is all around us, and its applications in various fields are nothing short of amazing. The demand for Big Data Analytics is expected to rise significantly in the coming years, generating revenue opportunities worth USD 235.08 billion between 2022 and 2028. Many specialists from a diverse range of areas are still exploring the full potential of what big data and related analytic techniques can do for us, and healthcare is quickly shaping up to be one of the hottest beds of development in this regard. We’re already seeing some amazing results from the proper integration of big data into healthcare workflows, and we’re likely only seeing the tip of the iceberg at this point.

1. Improved diagnosis accuracy

Cases where a certain issue could be treated earlier by identifying it correctly are not rare, and misdiagnosis is still a common issue in healthcare, even in places where it’s gone through serious development. Big data analytics can assist in these cases significantly, by allowing physicians to compare the conditions of their patients against a carefully evaluated database of known factors and symptoms. That way, the accuracy of diagnosing certain conditions can be improved dramatically, leading to an overall greater rate of satisfaction among patients.

Not only that, but patients may also occasionally receive specifically directed tips for their future healthcare and the best practices that they should follow for it, customized to their own condition thanks to the ability to see certain factors which would normally be outside of the physician’s control.

2. Easier triaging

And on that note, assigning patients the correct course of treatment should become much easier and more streamlined in the future if we continue to use big data analytics and keep collecting all the relevant information from evaluations. It’s sometimes surprisingly easy to determine what kind of treatment a patient should be assigned to before they’re even properly diagnosed by a physician, which can in turn remove a lot of work from the shoulders of physicians themselves, allowing them to focus more actively on the actual treatment procedures.

This is a self-feeding loop too as we continue to gather data and evaluate patients according to specific criteria, we’re going to see an even greater accuracy in evaluation results in the very near future. Things may even get to the point where a specialist is not required to handle a large portion of the pre-treatment procedures, giving them much more flexibility in how they want to approach the actual treatment itself.

3. Improved caretaker capabilities

Which brings us to a very important point that is likely going to become obvious really soon. Physicians and other specialists in the healthcare field should soon find themselves with a much broader range of capabilities as opposed to just a decade or so ago, allowing each doctor to perform tasks outside of their direct scope of abilities. Of course, we’re not likely to see something like a general physician performing brain surgery, but with the help of accurate and quick analytics, it should be possible to gather enough information to perform some more basic procedures on patients, saving time in getting them through intermediate treatment steps.

The current nature of healthcare is indeed quite complicated and it’s not rare to see conflicts between those practicing in the field, as they’re sometimes unable to reconcile the differences in their analysis of patients. With the help of data analytics though, there should be far fewer conflicts in the near future, especially when it comes to deciding on an appropriate course of treatment.

Conclusion

While we still have a long road to walk until we see some true changes in the system, some of the effects of big data on healthcare are already becoming obvious and it’s hard to ignore many of the benefits that it brings to the table. As long as people continue to contribute to the data collection and analysis, we’re likely not far from the point where healthcare will see a complete transformation and will enter a new era.