5 Unbelievable Ways To Be a Better Healthcare Data Scientist

Damian MingleChief Data Scientist

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Overview• For a Data Scientist, it’s important to dig

into the details of the project before you start modeling

• A Data Scientist who has the business of healthcare in mind will attempt to identify factors that might get in the way of a successful project

• At different phases of a project there are differing needs for information, but once you have moved past data gathering, a successful Data Scientist’s objective becomes diving into the details quickly and at a deep level

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5 Ways to be a better Data Scientist 1. Conduct a Resource Inventory• Know the in's-and-out's of the available resources for a project • Realize the important variables such as fixed extracts, access to live data,

warehoused data, and operational data• Remember to include computing resources such as hardware and software

2. Understand the Requirements, Assumptions, and Constraints• Risky assumptions should always

prioritized first • Watch for data traps• Consider any and all resources,

and technology constraints • Think outside the box when it

comes to limitations

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Five Ways to be a better Data Scientist 3. Determine Risk and Contingencies• Have a backup plan or two in place in the

event unknown issues arise• Experience suggests there are landmines

around every corner, so plan for alternatives from the beginning

4. Document Meaning• Develop a working glossary of relevant

business terminology, it will help keep you and others on track

• Have Data Science terminology defined and illustrated with examples, but only work with the terms that directly relate to the business problem at hand (use the KISS strategy)

5. Calculate Costs and Risk• Compare the associated costs

of the project against the potential benefits

• Knowing this at the beginning of the project is clearly more beneficial to you and the organization than at the close

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SummaryKey Point: As Data Science matures in terms of the business of healthcare, a Data Scientist needs to be more aware of assessing the situation, taking an inventory, learning about the risk and developing contingencies, and understanding the cost benefits of having a successful Data Science project.

Remember: Not every Data Scientist will take these steps, but then again not every Data Scientist is highly successful. Like water in the desert----a solid Data Science methodology is critical to the very survival of the underlying business. Do not leave your organization thirsty when it needs you most!

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Questions? Connect Us!

Damian Mingle

@DamianMingleLinkedIn: Damian R Minglewww.DamianMingle.com

WPC Healthcare

@WPChealthcareLinkedin: WPC Healthcarewww.WPCHealthcare.com