Big data to improve patient outcomes
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Today’s article is how we can use Big Data to improve patient outcomes? When analytics is not enough,how Big Data is used! using human-led useful algorithms, to solve problems related to
Available data across all industries are increasing, therefore accurate analysis is needed.Here we used the word ACCURATE, cause if you come to wrong conclusion,it can be a matter of life or death.To help in analysis,computers and algorithms are used, but they are not enough, we need humans for insight works.
Electronic records, health insurance claims, real-time monitoring by connected mobile devices. More medical information is being generated and gathered today than ever before by using computers and humans.Due to the rise in population,it increases pressure on healthcare services & healthcare costs are rising worldwide.How to make
healthcare services more efficient is an increasing concerned question.How to use data to gain best results ? how to face the challenges & maximize the use of analytics & big data !
Though Artificial Intelligence is improving,some lines of code strings can’t help us to derive insights by their own.
Google flu trends is best example of it. when it first launched,it was hailed as a breakthrough.Its ability to spot flu,by analyzing search engine was seemed far better than traditional approach. But, the tool’s predictions were off the mark! becuse the algorithm didn’t distinguish between someone who had symptoms and someone who was merely asking about symptoms.With such a vast amount of data, the volume of false data became so great as to render the findings almost meaningless.The idea was good. Today, such experiences helps us to improve analytics & algorithms. it shows just analytics & smart code is not enough.we need humans who are expers in these fields. To improve healthcare services, we need to combine data scientists,coders and persons with deep medical expertise.
As every coin has two sides, Big data too has few disadvantages.Big data helps in improving but it also creates some challenges and hurdles.
Technological hurdles are raised due to explosion of data. it has to deal with much large volume of data having unstructured and dissimilar formats.
Organizations often over-comply with privacy laws, assuming them to be more restrictive than they actually are. The net effect is that entities become overly conservative about sharing data.
Data Inconsistencies are raised due to the issue of data quality.Huge amount of data from multiple organizations increses data inconsistencies. Often, de-identified informations also creates troubles,the garbage information also increses due to it.
Big data is not automated,it doesn’t run itself! it needs human supervision. when high amount of data is concerned,it needs more intervention of humans.It’s not enough to get analysts in only at the start – they need to be there at the end, to continually monitor results.
As a result, both people and technology are becoming increasingly able to extract true insight, While machines helps in the data-crunching, humans are and will continue to play vital role in understanding and monitoring.
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