Quality Requirements and Standards
The ninth of an extended discussion of HbA1c methods and the analytical quality necessary for patient care. This discussion finally starts to plot performance on a Method Decision chart. Turning numbers into easily understood graphic displays - that's the best part of statistics. So how many HbA1c methods hit the bullseye, and how many miss the target completely?
The eighth part of an extended discussion of HbA1c methods and the analytical quality necessary for patient care. This discussion tackles the subject of how we make decisions about the acceptability of performance. We may run studies, calculate statistics, but how do we interpret them in the end? Using Sigma-metrics and a tool called the Method Decision chart, we can make decisions clearer.
The sixth part of an extended discussion of HbA1c methods and the analytical quality necessary for patient care. Studies in the literature can generate loads of statistics. But readers may find it hard to determine if the right numbers were calculated - or what conclusions should be drawn from the statistics that were calculated.
The seventh part of an extended discussion of HbA1c methods and the analytical quality necessary for patient care. This discussion tackles the subject of how we judge method performance. We may run studies, calculate statistics, but how do we interpret them in the end? With POC devices, a new tool called "error grids" is increasingly coming into play.
The fifth part of an extended discussion of HbA1c methods and the analytical quality necessary for patient care. When we say HbA1c, do we all agree on what is actually being measured by the test?