ClickCare Café

Big Data and Healthcare Collaboration

Posted by Lawrence Kerr on Thu, Sep 20, 2012 @ 02:00 AM

Big data is a large part of our lives as medical professionals. And the demand for big data is growing. Here are but a few examples that each of us encounters every day. 

  • Usual and customary fees -- their determination
  • Best Hospitals, Best Doctors
  • Length of Stay, Outliers 
  • Meta-analysis studies
  • Prescription surveillance of narcotics
  • Prescribing patterns by big pharma
  • Disease outbreak control
  • Payment and incentives based on percentile of RVUs (relative value units)
  • Free -- something gets measured so somebody else can pay (Nielsen Ratings)
We question, then, how does bad data going in, affect what comes how?
How does that affect us every day?  Healthcare collaboration is affected by Big Data
One approach that industrialists have had toward healthcare collaboration is monetizing Big Data. Hence, we find a plethora of “free” so called collaborative websites. “Free” forums, “Free” references. “Free” consultations. And better than “Free”, honoraria for one’s opinion. While not always needed, pictures and words offer a more accurate communication. But let’s spend a few minutes on “Free”. Chris Anderson has written a book, appropriately enough for this blog, entitled Free. He describes the many forms of free. One that we are all familiar with is free broadcast TV. Free to us, but paid for by a third party, those who pay $3.5 million for 30 second Super Bowl ads. We are willing to watch the ads in exchange for watching football for free. We pay for free later by purchasing what we have been shown. Of course, blogging in general is either filled with ads or offered as a gateway. It is either a lot of posters for the circus, or the barker for the sideshow. It brings new terms to old concepts. Pay Per Click and Organic Search are two of them. Competition for Eyeballs is another.

Another form of free is the free trial. ClickCare offers iClickCare as a free trial with the hope that when familiar with our service you will go ahead and buy it. If you don’t, you still have basic functions for free, and we hope that you will come back and purchase a subscription. This form of free is clear and explicit.

However, there are other forms of free which are less explicit and may be even nefarious. This is where Big Data comes into play. We are all familiar with our paying for our free searches by allowing what we search for, how we searched, and where we came from, to be used by others. Increasingly, we are offered free access to sites offered as a means to enable sharing among professionals. Someone pays for these sites. What do they get in return? Among the returns are aggregated data about what drugs we subscribe, how a marketing campaign worked, or who is a thought leader who can be leveraged/manipulated to increase sales.

This is where Big Data may be hurting us as individuals.

Conversely, as individuals, how do we hurt big data. Really it comes down to the now proverbial -- GIGO -- garbage in / garbage out. In order to satisfy the massive thirst of Big Data, we are asked to reduce our complexity of decision making and care management to CPT and ICD codes. These are unwieldy and time consuming. Imagine that if a patient needs an xray for an injured finger that was just fine before it (inexplicably) struck a wall, then we need an ICD-9 or ICD-10 code. We need to order an xray. We have patients waiting, the EMR is flashing that it has an un-filled field. We know what the film will look like and we know that the finger bone is attached to the hand bone. Knowing all of that, we might  accept that the code for fractured hand is close enough. We will still get to see the fracture. The finger is part of the hand after all, we get the xray, the patient gets the treatment, and Big Data gets the garbage. The Big Data, counting the bits and bytes delivers erroneous:

Usual and customary fees—their determination 

 Fee for treatment

 
 

Best Hospitals, Best Doctors

 

Best outcome because of wrong comparison

 

Length of Stay, Outlier

 

Simpler code for a more complex problem

 

Meta-analysis studies

 

Large numbers of pooled errors

 

Prescription surveillance

of narcotics

 

Narcotic prescribed for less painful injury.

Prescribing patternsby big pharma

Sales representative sits in wrong waiting room 

Disease outbreak control

All of a sudden there are more hand hand than finger fractures

 

Payment and incentives based on percentile of RVUs (relative value units)

Wrong unit, right treatment

Free—something gets measured so something else can pay (Neilsen Ratings)

 

Ask for free data analysis, get the data you pay for. Data gets more accurate information, and qualitative as well as quantitative data as well.

 

 

As the healthcare debate continues, and numbers are described in billions and trillions, we will see more big data. There are a lot of beans to count. As healthcare collaboration feeds more accurate information to big data, the value of analysis is improved. 

Learn more how ClickCare can assure that the data you use is rich, focused and related. 

Click me 

References and attribution:

Bean Counter

http://rickmarolt.info/?page_id=276


Tags: healthcare collaboration, big data in healthcare, big data

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