The Data Life Cycle

This year and most of next will likely be spent figuring out how to get EHR systems installed in hospitals and physician offices. Most of the organizations making this transition will be doing so as a reaction to the federal government’s incentives and penalties for not doing so. But there is a much bigger, long-range picture that should provide a framework useful to healthcare leaders. The meaningful use rules require providers to report quality measures to various agencies for analysis. Some of this will be used to determine whether or not the system is being used at all in order to manage incentive payments, especially in the beginning. Other data, some not even conceived of yet, can be used to help improve what we know about medicine and to develop best prevention and treatment practices. This diagram¬†shows one way to look at the process (click to enlarge).

From "data" to "knowledge"

Today, at least in the US, we’re in the first quadrant in the lower left corner. Here, we are just entering the first round of data collection on a national level. In the next quadrant, data will be aggregated and studied for various purposes. Early on, the type of data collected will help determine compliance with meaningful use, and other quality reporting initiatives. In quadrants 1 and 2, it’s still data, or at best “information,” while quadrants 3 and 4 represent the process of learning from that information and then finding ways to transfer that knowledge into support systems that can improve point of care quality and value to both the patient and the healthcare system.

The interesting questions that must be addressed in order to accomplish this are at the heart of “The Art of Medicine and Technology,” and what we want to explore on this site. Some questions arise at each point along the cycle:

Quadrant 1:

  • What kind of data must we collect at this point in order to add value in Quadrant 4?
  • Are we collecting it now?
  • Will it require re-engineering systems?

Quadrant 2:

  • Who does this work?
  • Who has access to the data?
  • How do we ensure that the analysis is unbiased and adds to the art of medicine?
  • Are there any ethical issues involved in doing mass aggregation and analysis of health data?

Quadrant 3:

  • What do we want to learn?
  • Can technology help us uncover unanticipated discoveries?

Quadrant 4:

  • How will this knowledge translate to support systems?
  • Can we trust what we do?
  • Is it ethical to transfer knowledge “in progress” to computerized systems?
  • How many cycles are required before physicians move from trust to reliance on technology?

As always, your comments are welcomed!

-Rod Piechowski

Copyright © 2010, Rod Piechowski, Inc., Consulting

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