Quality improvement and measurement: what non-executive directors need to know

An overview of quality improvement and measurement for non-executive directors of health boards.

Appendix 2a - The three reasons for measurement

Data and its measurement for improvement are used differently from data employed for judgement or for research. It is vital that Board members know the difference between these and the expectations on Board members for each type of measurement. In this video Mike Davidge explains how measurement for improvement is different to traditional measurements used in healthcare.






Achievement of target

New knowledge

Improvement of service

Testing strategy

No tests

One large test

Sequential tests

Sample size

Obtain 100% of available, relevant data

e.g. percent of patients who have been seen within a predetermined waiting time

'Just in case' data

e.g. systematic analysis of an outpatients' invitation to attend notes to test the effectiveness of a new IT system

'Just enough data', small sequential samples

e.g. five case notes from yesterday - followed by five today to see if staff are actually undertaking and recording all three elements of a care bundle

Type of hypothesis

No hypothesis

Fixed hypothesis

Hypothesis flexible, changes as learning takes place

Variation (bias)

Adjust measures to reduce variation

Designed to eliminate unwanted variation

Accept consistent (random) variation

Determining if a change is an improvement

No change focus

Statistical tests, p-values

Run charts or Shewhart control charts

Adapted from: The Three Faces of Performance Measurement: Improvement, Accountability and Research. Solberg, Leif I., Mosser, Gordon and McDonald, Susan Journal on Quality Improvement. March 1997, Vol.23, No. 3.


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