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EMRs and the Data Entry Paradox; Same Concept Not Applicable in the LIS World

Posted Oct 12 2012 12:00am

In a previous post, I discussed three ways in which data can be entered into EMRs by physicians in the name of efficiency (see: Three Ways to Document a Physician/Patient Visit in an EMR ). These same methods can also be used to bill inappropriately for physician services. I came across another note that discusses physician attitudes toward EMR data entry that the author refers to as the "data entry paradox" (see: The Data Entry Paradox ). Below is an excerpt from it:

Everyone...has been touting the virtues of the vast troves of data already or soon to be available in the electronic health record (EHR), which will usher in the learning healthcare system. There is sometimes unbridled enthusiasm that the data captured in clinical systems, perhaps combined with research data such as gene sequencing, will effortlessly provide us knowledge of what works in healthcare and how new treatments can be developed. The data is unstructured? No problem, just apply natural language processing....If we have poor underlying data, the analyses may end up misleading us. We must be careful for problems of data incompleteness and incorrectness.

There are all sorts of reasons for inadequate data in EHR systems. Probably the main one is that those who enter data, i.e., physicians and other clinicians, are usually doing so for reasons other than data analysis....I also know of many clinicians whose enthusiasm for entering correct and complete data is tempered by their view of the entry of it as a data blackhole. That is, they enter data in but never derive out its benefits. I like to think that most clinicians would relish the opportunity to look at aggregate views of their patients in their practices and/or be able to identify patients who are outliers in one measure or another. Yet a common complaint I hear from clinicians is that data capture priorities are more driven by the hospital or clinic trying to maximize their reimbursement than to aid clinicians in providing better patient care.

Another challenge for clinicians is the time required for electronic data entry. There is no question that the 20th century means of clinical documentation, mostly consisting of scribbling illegible notes on paper, was much easier and faster than typing and/or clicking. While I think that few clinicians want to go back to hand-written notes, there is an appeal of their ease of use, at least for the person doing the entry. Related to the time for electronic data entry is the “tension” between structured data, which makes aggregation and analysis easier, and “flexible” (or narrative) data, which allows the clinician to tell the story of the patient. Many clinicians report that excess structuring of data (i.e., pointing and clicking) loses the story of the patient, although those who process the data know that structured data is easier to analyze.

The EMR data entry paradox relates to the fact that the physicians entering clinical data are often pressed for time and do not perceive that they derive any major benefits from this documentation. Because of this, the quality of some of the data may be suspect. Moreover, physicians are accustomed to telling a narrative story in the medical record and often balk at entering structured data which is easier to analyze but may hinder the development of such a narrative. Finally and as noted in the first paragraph, physicians and nurses may be under pressure from hospital executives to use EMR documentation to maximize reimbursement.

Interestingly enough, these complaints have generally never arisen in the LIS world in the 30 years that I have been involved with it. In part, most of the data generated in clinical pathology using automated analyzers is transferred to the LIS database without any massaging. It's then left to the test-ordering clinician to develop diagnostic and therapeutic conclusions with these results. Even on the surgical pathology side where diagnoses are reported rather than data, the prose has gotten stripped down over the years to only the basics. This is due to the volume of work that needs to be completed. Moreover, all lab professionals view the LIS database as an extremely valuable tool. It's interrogated constantly to retrieve the results of past tests and to generate new diagnoses.

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