Tools for improving the quality of data capture for clinical inquiry

This column presents an innovative approach for maintaining momentum and enthusiasm during the arduous process of monitoring data quality. Data quality refers to ?the totality of features and characteristics of a data set, that bear on its ability to satisfy the needs that result from the intended use of the data,? a definition developed on the basis of the International Organization for Standardization?s definition of quality. 1 (p602) In the era of electronic health record documentation, nurses increasingly are able to use the data captured and recorded in the course of usual patient care delivery for the secondary purpose of clinical inquiry, but this process works only if data have been collected appropriately. For example, if the incidence of catheter-associated urinary tract infections is rising, an excellent clinical inquiry project would be to review the documentation for all patients who had a urinary catheter during the time period of the spike in infection rate. The team would examine each of the factors associated with catheter care and might even design the evaluation to compare these factors before, during, and after the spike to look for differences associated with infection. However, what if important factors or steps in catheter care were not consistently or reliably recorded, even in required electronic fields? In this situation, the poor data quality would prevent the clinical inquiry project from moving forward and possibly prevent an opportunity for significant improvement in patient care outcomes. References