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⚕️MED+TECH | Data Analytics in Healthcare: The Good, The Bad, & The Ugly

Part 1

Data is the new oil.

Don't believe me? Check out where Dubai Investors are betting their billions on :) This sought-after resource, whereby eventually the whole globe will depend on entirely, is rapidly bending our reality as we speak. Hence, keep a keen eye on boss moves like these 👇

Relevant Business Moves

Moro Hub and Huawei break ground on solar data center in Dubai

​link to post: here

It is but a moral obligation of mine to lay out a universal definition of Data Analytics prior to exposing you to the beautiful l'état de l'art de Data Intelligence in Healthcare.

Data Analytics is the science of discovering associations and understanding patterns and trends within data, which provides an enormous value in transforming the growing amount of data into actionable information; to support strategic and tactical decision-making processes within an ecosystem.

Most folks, however, are only unveiled to the tip of the iceberg which is data analysis and visualization (presentation). What’s underneath the workings is an ongoing challenge in its own merit: data acquisition from clinical , financial, administrative, research systems, data integration, data cleaning, data warehousing, data governance, and data provenance. These elements are very complicated in the healthcare space due to several inherited hurdles such as lack of interoperability, fragmented historical data, distorted patient data, redundancy, and the good-all-privacy concerns. I will flesh these out at later posts. They need extra care and attention.

Irrespective of the current challenge it is but fair to reinforce the ultimate aim here, which is to have an interconnect and real-time responsive healthcare delivery — a value-based healthcare system of some sort.

Therefore, when applying data analytics to the healthcare sphere, one needs to bear in mind that the density of the data, the lack of standardization among different exported data, and the thin-line of whether a certain datapoint is perceived as an identifier of patient-related information or not. Let alone the actual reliability level of models being used to extract potential actionable information out of raw data. We are merely scratching the surface and what a joy ride this challenge will be!

In this blog series, we will explore the whole life cycle of data analytics in healthcare. Subscribe for more updates.⚕️


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