What does the process of stratification involve in healthcare measurements?

Stratification in healthcare measurements involves dividing data into subgroups to allow for more precise analysis of each segment. This process is fundamental in understanding variability within a population. By stratifying data, healthcare providers can identify specific trends, differences, or issues that may not be obvious when examining the overall data.

For instance, if a hospital is analyzing patient outcomes, stratifying by factors such as age, gender, or diagnosis can reveal that certain groups may have significantly different results. This targeted analysis helps healthcare professionals to tailor interventions more effectively and improve patient care by addressing the unique needs of each subgroup.

The other approaches listed do not align with the concept of stratification. Random sampling of patient feedback is a method for collecting unbiased data, creating aggregated metrics combines various data points into a summary statistic, and utilizing a single average metric overlooks the nuances and variations present in patient outcomes. Therefore, these alternatives do not focus on the critical aspect of analyzing differences within subgroups, which is central to the stratification process.