Like Peas & Carrots: Data Cleansing & Product Standardization
Tags: cleansed data services, dirty data, EHRs, healthcare supply chain, Novation, procurement, sourcing, standardization programs, uniform device identification. FDA ruling
In supply chain management (SCM), unreliable, inconsistent and out of date “dirty data” is the bane of the profession. With healthcare spending approaching 20% of the U.S. GNP and medical supplies accounting for more than 40% of that number, the fact that the industry is only now moving toward a Uniform Device Identification (UDI) system is mind blowing. We’re almost glib in our recognition that healthcare has lagged behind other industries in SCM and procurement sophistication, yet the FDA just announced its guidance on UDI adoption less than 30 days ago?
Most industry sources suggest that “dirty data” and its ripple effects cost the industry as much as $11 billion each year –and we’re just talking about supply chain waste (i.e. medical products and services). In fact, dirty patient data (Master Patient Indices) are yet another long-standing problem that isn’t counted in that estimate.
Taking “dirty data” and turning it into “cleansed data” is a service that most all of the GPOs now offer. And despite all the talk of automation –everyone who offers these services claims to have a “secret sauce”—the last mile of the process is the most important and it remains very labor intensive. But there is an obvious reason for that: Most providers are hell bent on re-building and documenting actual histories when the opportunity to do a little revisionist thinking is staring them right in the face.
Supply chain data can be cleansed incrementally –category by category. Instead of digging through the archives and trying to find, organize and digitize a history that most SCM teams would prefer to forget, these projects should be executed in the context of product standardization initiatives. In other words, instead of “getting the data right” on 174 different types of orthopedic drill bits from 6 manufacturers, why not make the decision to standardize on 1-2 product lines (if possible) and collaborate with the selected manufacturer(s) to help you get your demand pegged and your item master current and accurate? Not a bad thought.
“By utilizing a combination of clean source data and advanced analytics, savings opportunities can be cultivated and maximized,” said Tim Vandermolen, product manager, information and data services, Novation. “Industry research has shown that through the use of data cleansing and advanced spend analytics, health care organizations can realize savings of 0.5 to 1.5 percent of their annual supply chain spend. These savings can make a big difference for a hospital’s bottom line.” Naturally, I fully agree, except that I believe the savings opportunities are even greater.
The point of this post is to encourage providers who are overwhelmed with the dirty data problem to think about it a little differently. I know from personal experience how daunting and expensive the problem can be –from a provider’s perspective and from the perspective of a company that sold data cleansing services. Frankly, these projects can be torturous.
As I was reminded this weekend: Combining data cleansing with standardization initiatives just makes sense. When I’m cleaning out my garage, I throw a lot of things away –that’s the whole point.