We had the opportunity to sit down with Alex Whitfield, Manager of the Data Team here at Ascendco to speak with him about data foundation. Alex has been with Ascendco for nearly 4 years now, but before that, he was a team lead for a Sterile Processing department. He has brought this first hand experience to his current role as Data Manager and uses it to improve our processes to benefit our clients. 

 

What do we mean when we say the term “data foundation”? Well, simply put, it is all of the information that has been collected over the years to build a base of knowledge in order for the facility to run properly. Specifically for Sterile Processing, this includes, but is not limited to; count sheets, trays and instrument inventory, sterilizer parameters, and so much more. The problem lies in keeping this data up to date. It is a lot of work to maintain the most accurate and up to date information in an ever changing sterile processing department. This common issue lead us to one main question we had for Alex:

 
Why is a strong data foundation important for a successful software transition?

Alex: “People tend to look to new software to solve issues and of course, some systems may have unique features that fit the specific needs of facility workflow more than others. But often, that is only a small piece toward the actual solution. Brian Reed’s (Ascendco CEO) quote “garbage out, garbage in” is referring to moving to a new software system without a data cleanse prior to the switch. You’re taking the same data you always had (potentially old, stale, and inaccurate) and moving it into a new software and expecting things to work. It’s like getting a new car, but then replacing the new engine with your old one. It looks nice, but when you open up the hood, it’s the same old problems.”

 
That makes sense, can you explain what a data cleanse is and the process that it involves?

“A data cleanse is the transition step between your old process and a new software system. This is when the old data is sifted through for outdated items, repetitive information, disorganized naming structure and then cleaned up to establish an accurate state of fresh data in the new software system. This is practically mandatory for the success of the switch.

 
The key objectives of Ascendco’s data cleanse are:
1) Standardization – for a common language among the health system
2) Near elimination of free text – for advanced filtering, analytics, and data governance.”
 
 
Once you have a strong data foundation, it ensures that all the features of your software system can be optimized and fully functional.  Additionally, Ascendco’s routine data maintenance prevents old problems from creeping back in and maintains the integrity of your new, clean data.