Interpretive Notes Steps to Improvement Data Quality Actions

For technical notes, please see page 31 of the Data Dictionary.

Interpretive Notes

Tips to help you understand the data and put it in context.

Steps to Improvement

Concrete steps you can take to improve care, based on your data. Assuming you have established that the data are good enough to direct action AND that improving performance in this area is a priority for your team, you may wish to discuss the following options with your clinical leaders, Quality Improvement committees, team staff and/or patients:

Reference:

  1. S. Ali Imran, Rémi Rabasa-Lhoret, Stuart Ross. Targets for Glycemic Control. Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Can J of Diabetes 2013;37(supp 1):S31-S34.

Data Quality Actions

Tips to help you understand the quality of your data and, if necessary, take steps to improve it.

Estimate the impact of data quality

The data are almost certainly not a definitive estimate of your team’s actual performance. However, they might be “good enough” to help you decide if your team needs to improve or not. To determine if the data are “good enough” for that, estimate how likely it is that one or more of the issues outlined in the interpretive notes above are a problem with your team. Then, run the “imperfect data impact calculator” to see if the issue(s) could lead to a different decision related to the need for improvement. To use the Imperfect Data Impact Calculator, work with your clinical leaders and staff to establish an approximate impact of data quality.  Is the data quality issue causing your performance to look like TWICE or HALF or 10% (or other number) less or more than it actually is? Plug that number into the “imperfect data impact calculator.” It will show you whether the data quality issue(s) you think you have would change your initial decision regarding the need to improve. You may find it hard to generate consensus about the impact of data quality issues on the level of performance shown in the D2D report. In that case, consider the following options:

If the Imperfect Data Impact Calculator points to the same decision (i.e., a need to improve or NOT) even after data quality issues are considered, the data are likely “good enough” for you to whether you need to improve care.

Increase the quality of the data

Divide the number of patients with diabetes who have an individualized HbA1C target recorded in the EMR (numerator) by the total number of patients with diabetes (denominator). This data comes from your EMR.

 If the “imperfect data impact calculator” shows that the issues in your data may not be good enough for you to decide to change processes of care, you might consider:

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