Ask the expert: What do we do with imprecise peer review data?

Believe it or not, imperfect data is usable data. Imperfect data should never prevent the peer review process from occurring, as long as you don’t rely on it exclusively. Here are four helpful principles regarding the interpretation of imprecise data:
 

• Don’t wait for perfect data. Perfect should never be the enemy of good. Work with the data you have and learn its uses. A good way to do that is to distribute the data to physicians with the caveat that you just want them to see it and give constructive feedback.
• Look for big differences. The data aren’t that precise, so don’t create the illusion of precision. Two targets that create three zones (excellent, acceptable, and needs follow-up) are adequate.
• The data are a starting point to ask the right questions. Ask “Why are you different?” not
  “Why are you bad?” Ask the physician what he or she thinks could account for the data, and then explore together whether that is true.
• Make the data better. Commit as a medical staff and hospital to identify key data error sources and take responsibility to fix them.

This week’s question and answer are from Measuring Physician Competency: How to Collect, Assess, and Provide Performance Data by Robert Marder, MD, CMSL; Mark Smith, MD; Marla Smith, MHSA; and Vicky Searcy, CPMSM, published by HCPro.