Measuring the quality of patient data with particular reference to data accuracy.
Health Authorities receive vast quantities of data from providers relating to patients
treated. Ibis data is used to survey the health of the resident population and to determine
future healthcare services. It is therefore essential that the quality of this data is measured.
North Staffordshire Health Authority already monitor, to a certain extent, the quality of
data received. However, accuracy is one attribute of quality not monitored. This thesis
proposes a method to measure the accuracy of patient data, in particular clinical coding.
The traditional method of measuring accuracy determines whether a data item is correct or
incorrect. The definition of accuracy, however, is the measure of agreement with an
identified source. The proposed measure ranks incorrect clinical codes by their level of
inaccuracy. Concepts from measurement theory are used to ensure that this measure
adhered to the rules of the theory.
This alternative method of measuring data accuracy was tested on a sample of inpatient
data. From the results, the most appropriate way to analyse clinical data whilst still
maintaining a level of accuracy satisfactory for the intended information purposes could be
identified. Managers at North Staffordshire Health Authority were surveyed for their
views on the usefulness of this alternative method of measuring data accuracy compared
with the traditional method. Auditing a sample of data like this does not help to prevent
errors occurring. Therefore, to identify how data accuracy could be improved in the long
term, the source of the errors were discovered by examining the data life cycle.