“Meaningful Use” Defined

Mark and I have written in the past year about the concept of “meaningful use” associated with EHR funding in the US and the open and transparent process by which “meaningful use” is being defined.  At the very end of last year (still hard to remember that it is now 2010), two documents were posted that, among other things, offer an initial definition of “meaningful use” and describe the process by which the definition was conceived:



Three stages of meaningful use are specified:

  • Stage 1 (beginning in 2011): The proposed Stage 1 meaningful use criteria “focuses on electronically capturing health information in a coded format; using that information to track key clinical conditions and communicating that information for care coordination purposes (whether that information is structured or unstructured, but in structured format whenever feasible); consistent with other provisions of Medicare and Medicaid law, implementing clinical decision support tools to facilitate disease and medication management; and reporting clinical quality measures and public health information.”
  • Stage 2 (beginning in 2013): CMS has proposed that its goals for the Stage 2 meaningful use criteria, “consistent with other provisions of Medicare and Medicaid law, expand upon the Stage 1 criteria to encourage the use of health IT for continuous quality improvement at the point of care and the exchange of information in the most structured format possible, such as the electronic transmission of orders entered using computerized provider order entry (CPOE) and the electronic transmission of diagnostic test results (such as blood tests, microbiology, urinalysis, pathology tests, radiology, cardiac imaging, nuclear medicine tests, pulmonary function tests and other such data needed to diagnose and treat disease). Additionally we may consider applying the criteria more broadly to both the inpatient and outpatient hospital settings.”
  • Stage 3 (beginning in 2015): CMS has proposed that its goals for the Stage 3 meaningful use criteria are, “consistent with other provisions of Medicare and Medicaid law, to focus on promoting improvements in quality, safety and efficiency, focusing on decision support for national high priority conditions, patient access to self management tools, access to comprehensive patient data and improving population health.”

The rules in which the meaningful use criteria are incorporated will be published in the Federal Register by mid January and will be subject to a 60-day comment period effective.  The interim final rule will become effective 30 days after publication.


2 responses to ““Meaningful Use” Defined

  1. The issue that pops up to me is how much leeway EMR vendors will have when it comes to capturing coded information. Will it be 75%, 95% or 100% of all patient data that must be captured in some kind of ICD-9 or ICD-10 format? I think this is important because to do true population health, and measure the value of an EMR over time then 100% of patient data should be coded. I just look at the situation in Canada and look at the first few generations of certified EMR vendors, and notice how few (if any) could capture 100% of the patient data in a truly structured format.

    A whole lot of vendors fudged it and captured data in free text fields. Even a small amount of this unstructured data can cause havoc for anyone looking to truly manage the health of population. This is especially important for those suffering from one or more chronic conditions.


  2. As I discussed in an earlier blog post, there appears to be a disconnect between the type and format of the data needed for public / population health purposes and the data needed the delivery of day to day patient care. Mark, I believe that you are correct in your assertion that we need more structured data to support population health analysis. So, how do we bridge the gap between how physicians want to enter patient health information and the need for structured data?

    The same challenge of sorting through highly unstructured data is faced by anyone attempting to use Google or a similar search engine. Research in Web 3.0 technologies (also called the semantic web) is focused on dealing with this challenge using technology such as Natural Language Processing (NLP). I suggest that we can take advantage of this technology to transform unstructured data suited to physician care of their patients into structured data that is more readily shared and used for population health analysis.


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