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Big Data Moves to Healthcare: A Description. A Warning. A Solution. 2

Posted by Lawrence Kerr on Thu, Oct 25, 2012 @ 03:55 PM

This is Part 2 of a three-part blog post. Emphasis of Big Data acquisition and analysis is supposed to improve healthcare. We emphasize that healthcare collaboration is a way to deal with the massive amounts of data considered to be medical knowledge that has grown beyond mastery of anyone. That said, we also are concerned that attempts to improve quality and profitability remove focus from care and caring. The first post described one source of errors. This second post will show how this error can happen in clinical practice -- with or without healthcare collaboration. The third will suggest a solution. The whole set of the three should bring fair warning to those who hear the sirens of Big Data which is done poorly, and help them look to solutions which are done well.

The past few weeks have brought huge attention to the analysis of data to health care. Much promise has been given to disease detection, epidemiology trends, bioterrorism, and business intelligence. Savings are promised as well as improved care.

iClickCare helps erroneous interpretation by including images, words, discussion andWaiting in line for healtcare collaboration judgment.

EMR and EHRs with financial metrics are the foundations upon which Big Data is being built. They are taking up a considerable part, even a majority, of the day in the life of the provider. What of the rest of the day, a day like this one? To be kind in description, less than user friendly EMR's are being inserted into the office work flow. This process is called “Go Live” which is a stretch of definition of zombie-like software.

All of a sudden four exam rooms are filled and three more patients sit anxiously in the waiting room. The first exam room is occupied by an elderly, somewhat demented, 86 year old with black and blue eyes following a fall. His facial fractures are multiple, and not classic. There are fractures across and within the edentulous maxilla, the nasal bones are involved. There is an extension to the orbit on one side. The zygomatic arch is displaced. With difficulty, they could be classified as LeFort II and a half. Not exactly, but sort of close enough. For patient care, the classification does not matter, the treatment will be the same. We will need to code this visit properly, we know. Why? Because and it will take searching through lists of codes.

The second room corrals a crying 13 month old who has just been sent to the office from the emergency room with a dog bite of the left lower eyelid. She is accompanied by two distraught parents and one distraught grandmother. The next room in line finds a pleasant demanding 54 year old who has body dysmorphic syndrome and is very happy from the scar after the facial basal cell carcinoma that was removed but is also very concerned about her aging body, skin turgor, wrinkles and cheek bones.

healthcare collaboration avoids nurses as butler.jpgThe fourth room has another child with a facial deformity and what his mother describes as moderate to severe autism. He is accompanied on the visit by his brother who shares the same spectrum disorder. There are multiple sharp-edged drawers being opened and slammed closed. The mother’s third child is to be picked up from preschool in just a few minutes. Is surgery to be done?

The fifth room is quiet. Just a calm patient who is thankful for the care, and doesn’t mind waiting. Who would want to keep her waiting? Another form of pressure rests within.

We know that all who care for patients find themselves in similar storms. In part, this exacerbated by patient expectation, such as this Scrubs blog from one our Pinterest followers. In part, it is further caused by the frustration of not doing as smooth a job of healthcare delivery as was possible with less mechanical documentation.

Can you see the potential for error in this scenario? More to follow in Part 3 when we will describe the error and suggest a solution...

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Waiting in line sketch: Jonny Pickton

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

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