Whitepaper: Four Phases of Long Term Visualization Planning

Posted on January 31, 2020

It’s a Marathon Not a Sprint

Four Phases of Long Term Visualization Planning

In a time of unprecedented data collection flowing through an invisible, online superhighway, technological advancement is driving rapid software upgrades and the ability to process billions of bits of data in fractions of a second. Folders and paper charts in medical exam rooms have long been replaced by laptops and tablets running state-of-the-art software that records your every sneeze. Now what?

Collecting data is a bit like collecting Lego blocks. You have containers full of colorful pieces, but what would you prefer to look at, a mish-mash of plastic, or a beautifully crafted model built with those thoughtfully collected blocks? We all can agree that healthcare data, like building blocks, is best viewed and understood visually.

Those who are experienced in the hobby of building models with blocks will tell you that when you first begin, it is better to start with a project containing 50 pieces or less rather than going immediately for the 10,000-piece mega model. Over-eagerness tends to make the novice attempt a leap that is too great, and this can lead the builder down a road of frustration… that most likely ends at incompletion.

So why do healthcare organizations try to make giant leaps in the world of data analytics? Are Electronic Health Record and billing systems overpromising – and underdelivering – their built-in “State-of-the-Art” analytics packages and ease of data access, modeling, and visualization? Most major analytics vendors boast about building dashboards with just a few simple mouse clicks, but is this leading to unrealistic expectations and slowing down effective progress towards useful reporting, visualized insights, and solutions?

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