Sessions

27 – Turning Data Analysts into Data Scientists (technical, analyst)

The value of predictive analytics in healthcare settings is well established. In fact, 47 percent of health system CIOs say they plan to increase predictive analytics spending in the coming months. But how can you get a great return on that investment? The most common strategy is to hire data scientists. While data scientists are critical to any predictive analytics program, they are also difficult to find and expensive to hire. And new hires always take a long time to become productive. What if there were another solution — one that already exists in your organization? With the latest technology advancements, you can now effectively turn your incumbent data analysts into citizen data scientists. By focusing on a small set of artificial intelligence (AI) problems with known solutions, learning some basic data science principles and tools, and following the lead of an in-house or consulting data scientist, your data analysts can lead the way on your organization’s AI journey.

This session, designed for data analysts and their managers, covers a seven-step program for easily incorporating key data science principles and tools into analysts’ everyday actions. Starting with the use case of predicting readmissions, we’ll walk through how to organize the data, apply AI algorithms to generate predictions, and present the predictions to clinicians in the right way so that they are accepted.

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