Reporting on data and being a data analyst requires different but shared skillsets. Understanding the difference allows a person to not only interpret the information presented with more accuracy but also identify opportunities where the story can be improved so future decisions can be strengthened.
In this session, we will walk through some dashboard examples that not only assess your current analytic skills but also identify how you can develop other skills necessary to be the best data sleuth in healthcare.
We will begin our journey by uncovering why it is important to identify the real purpose and discover why it truly matters. People sometimes ask for things because they have a goal or a problem to solve, which may not really be the root cause, just the most recent fire they are trying to extinguish. Uncovering the true goal and how that relates to the bigger picture is a skill, and it takes additional skills, such as mapping, grouping, and workflow analysis to truly dive deeper than the superficial ask. Rolling up your sleeves and digging into the ‘behind the scenes’ story transforms a report filled with discrete and continuous data elements in different graphs for one purpose into a pathway of insights for different users who rely on the same data for different problems where all users can see how the data relates.
Knowing where to start is the hardest part but understanding that analytics is not a linear path helps! No matter where you enter on the journey, you can always pivot if you set the realistic expectation ‘data is messy.’ In order to report on healthcare data (or any data), someone has to transform it and someone has to clean it up. Fully understanding your topic prevents you from the ‘data trap’ mindset that the data is correct or what you see is the ‘source of truth.’ The statistician George Box said ‘All models are wrong but some are useful,’ which can be applied to analytics as well because of the limitations we have due to use/application of technology, laws/regulations, and differences between implementations of regulations/standards, which can vary across organizations and settings.
All of this combined can impact how a person views the data that is reported. As a data sleuth and analytic expert, it is important to unravel the complexities of what lies underneath. Come join us and learn how you can identify the complexities of using data to tell a story and what to do when you come across a cryptic story.