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Tag: Stage 2

Five Things EHR Vendors Should Do Right Now

Last week I was invited to attend the second annual NIST forum for EHR Usability called “A Community-Building Workshop: Measuring, Evaluating and Improving the Usability of Electronic Health Records.” NIST, in collaboration with the ONC, unveiled its initial discussion points for what it might consider as the “Usability Criteria” in the upcoming Meaningful Use Stage 2 regulations. At the event I met with Dr. Melanie Rodney, Distinguished Researcher at Macadamian and a member of the HIMSS Usability task force; I was impressed by the work that she and her firm were doing in EHR usability space. At the NIST forum I was able to spend time with experts in the both the fields of EHRs (like me) as well as in usability and user experience (like Melanie). We learned that the government believes that while usability can be key in increasing product effectiveness, speed, enjoyment, etc., NIST is going to focus on EHR usability for the improvement of patient safety. I asked Melanie and Lorraine Chapman, Director of User Research at Macadmian, to share with us what we in the EHR technical community should do in light of what we learned at the NIST forum last week. Here’s what Melanie and Lorraine said:

While the specifics are still forthcoming, vendors have a window of opportunity today to get ahead of NIST – and ahead of competitors – by proactively addressing meaningful use in advance of the 2013 deadline. Let’s look at what vendors can do, combining the information NIST has given so far with fundamental usability best practices:

Step 1: Set Usability Goals related to Patient Safety

These are specific, measurable goals such as “Our EHR must provide a 99% error-free rate of medication entry”. NIST has given the following examples of use error categories, each of which might be driving 1 or more goals.

  1. patient ID errors
  2. mode errors [e.g., dose related]
  3. data accuracy errors
  4. visibility errors [e.g., tapered dose 80-20mg – 80 shows vs. 20]
  5. consistency errors [ e.g., pounds vs. kilos ]
  6. recall errors [e.g., 1 time dose]
  7. feedback errors [1 tablet vs. 1/4 tablet]
  8. data integrity errors [ next vs. finish to enter injection just administered]

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