Quality leadership and quality control

Abstract

Different quality control rules detect different analytical errors with varying levels of efficiency depending on the type of error present, its prevalence and the number of observations. The efficiency of a rule can be gauged by inspection of a power function graph. Control rules are only part of a process and not an end in itself; just as important are the trouble-shooting systems employed when a failure occurs. 'Average of patient normals' may develop as a usual adjunct to conventional quality control serum based programmes. Acceptable error can be based on various criteria; biological variation is probably the most sensible. Once determined, acceptable error can be used as limits in quality control rule systems. A key aspect of an organisation is leadership, which links the various components of the quality system. Leadership is difficult to characterise but its key aspects include trust, setting an example, developing staff and critically setting the vision for the organisation. Organisations also have internal characteristics such as the degree of formalisation, centralisation, and complexity. Medical organisations can have internal tensions because of the dichotomy between the bureaucratic and the shadow medical structures.

Figure 1

The 1_2S Quality Control rule.

Figure 2

Random and Systematic Error.

Figure 3

Power-Function Graphs for 1_2S. The x-axis is in units of SD for systematic error (SE) or random error (RE) where ΔSE indicates a change in the magnitude of the SE. There are different curves for 1,2 or 4 controls per run.

Figure 4

Example of Trouble-shooting Flowchart for an External Quality Assurance Programme (with the permission of John Calleja).