I’ve been quietly observing the herds of opportunistic snake oil salesmen disguised as healthcare IT professionals and consultants promising gold mines with the supposedly amassed data that healthcare providers have in their electronic repositories.
These unscrupulous “experts” are promising that this BIG BAD Data can be used for wonders such as: population health management, clinical decision support, case management, bundled payments and you name it. Most of these “experts” have never been in healthcare until the billions showed up and if they were indeed in healthcare they have no background in healthcare IT!
What an opportunistic combination, wouldn’t you agree?
Most healthcare providers have been collecting data but not in a consistent way with a sound basic data governance model.
Most hospitals have paper charts that collect the data in unstructured and disorganized ways.
Most of the hospitals that have purchased and invested millions or billions of dollars in EMRs have either been unable to implement them or have failed at implementing them. Those that have “succeeded” implementing them have done so in partial and mediocre ways.
There is a BIG reason why the USA government is spending billions of dollars to get the providers to use EMRs in order to start collecting relevant and pertinent data! Providers have not been collecting data whatsoever.
So where is this supposedly BIG BAD Data coming from?
Well, some geniuses from major software vendors thought they could get this data from the HL7 transactions that had been moving back and forth between systems. Yes, indeed. They used some sort of “aggregation” software to extract this data out of HL7 v2.x messages. What a disaster! Who in their sane mind would think that transactional near real time data could be used as the source for aggregated data? The answer is: those that attempted it and failed forever in healthcare.
My advice to CEOs and CIOs of healthcare providers is: “Do not spend millions of dollars trying to get something out of something you do not have”. Do not let other folks make you invest in their pet projects. Most BIG BAD Data projects are sponsored by clinicians that don’t understand data in the sense of mining it for specialized purposes.
In healthcare you don’t need BIG BAD Data but instead you need quality, pertinent, relevant and accurate data.
You will never be able to manage population health with aggregated tweets, Facebook comments or aggregated HL7 v2.x messages.
Clinical Decision Support systems are medical devices which require well-governed data provenances and not BIG BAD Data.
Do you want BIG Data solutions? Then start implementing your EMRs in order to start collecting discrete relevant and pertinent data and you may get there in several years.
Go BIG but don’t go BAD!
Cheers!
#HIT100 presents: "The EHR Guy's Corner" 
As a Breaking Bad fan I LOVE the play on that title… and great points to. A friend and colleague puts it this way..
Data is like salt water – you can drown in it but you can’t drink it without filtering in. We are drowning in data while dying of thirst for information
I couldn’t agree more. I hate getting those calls “Spent X million dollars and a year and don’t have anything to show for it, can you help?” There is no magic bullet, expertise and experience matter. Thanks for saying this!
Terrific analogy in that quote @drnic1
Reblogged this on healthcare software solutions lava kafle kathmandu nepal lava prasad kafle lava kafle on google+ <a href="https://plus.google.com/102726194262702292606" rel="publisher">Google+</a>.
GIGO, raises its ugly head – garbage in, garbage out. What’s more concerning is that when faced with the prospect of having spent huge sums of money in implementation of strategies to mine this wanting data, the real prospect of someone either sweeping it under the rug (machiavellian) or not understanding the flaws in interpretation (realistically, more likely) using the data to reach conclusions which cause real patient harm. It hurts when its only money and wasted effort, but is reprehensible when it affects patient lives negatively. Data, like people, must be vetted.