Data Analytics 101: Why the approach matters

By: Jeannine Cain MSHI, RHIA, CPHI

We all know data is created and used to help support decisions, but are we too naive about who touches the data and how the data is processed? Over the years, I have made decisions based on the data provided to me, trusting it was right, only to learn later that the information was missing key pieces of information or processed in a way that changes the meaning. This is why I started on a journey to learn the methods surrounding analytics and ensure the quality, appropriate use, and validity of data extends beyond the dataset. No matter the discipline, you can trace back decisions to data, whether good or bad, factual or opinion, it is still what we use to make decisions.

Let’s start talking about healthcare data!

Healthcare data is extremely complex because there is so much we do not get to see or understand, and not everyone does things the same way because each situation is unique. However, even though things may look the same, they aren’t, which means we have to be careful when comparing the data. During my journey, I have discovered that one person does not have all the answers, and working with data is a shared responsibility at minimum between technology, analysts, HIM professionals, administrative, and clinical staff. There are so many decisions that need to be made when acquiring, cleansing, and displaying data, that it only makes sense to approach the process through a collaborative effort to ensure that the right story is told.

It goes back to the phrase ‘data is messy’, and in healthcare, it is very true! Healthcare data takes a lot of cleaning! Even before you can begin cleaning, it takes a lot of patience, knowledge, skill, and resources. More importantly, it takes money. Money to pay for the people to work with the data and money for the tools and licenses necessary to work with data. This is exactly why working with healthcare data doesn’t relate to one degree, one skill, or a particular piece of knowledge. It is a collaborative journey between a team of individuals because healthcare is not linear. It is a confusing path that intersects and continuously contradicts what we think we know when we change settings or organizations.

Do you remember sitting in the doctors office with the search and find activity found in one of the magazines, and you had a list of items to find hidden in a picture? Did you find all of the items 100% of the time? Healthcare data is very much like that activity. If we compare data to that search and find, can you image someone not familiar with the items on the list trying to locate something? Hopefully this example really shows the importance of understanding the parts different people or tools play into acquiring, cleaning, and transforming data to make it useful. If we performed an assessment, we can only conclude why it is so expensive and it takes a lot of resources to gain a little bit of insight to only a small portion of the problem.

In my next blog post, we will start talking about the acquisition of healthcare data.