Management of leg ulceration is an important part of community nurses’ workload but previous evidence suggests the quality of diagnosis and treatment of venous leg ulceration may be below that which should be expected.
This thesis uses Judgement Analysis and Think Aloud methodologies to explore the performance of 18 tissue viability specialist nurses and 18 generalist community nurses managing patients with leg ulceration. The nurses made diagnostic judgements and treatment choices and assigned confidence ratings on 110 clinical scenarios generated from real patient cases. These were presented online, as written scenarios, and using photographs of wounds to add visual information. Data for the judgement ‘ecology’ was derived from consensus judgements of a group of ‘expert’ nurses using the same scenarios. Logistic regression models were constructed to examine ideographic Lens Model statistics for individual nurses. Comparisons were made between groups of nurses with different levels of education and expertise. Think Aloud data from three generalist nurses was analysed to identify their cognitive processes.
The results showed that clinical decisions and judgements about venous leg ulceration are made in uncertain decision environments. In this study, community nurses achieved levels of accuracy below the achievable levels of judgement accuracy indicated by the diagnostic and treatment ecology models. Education alone was not a predictor of superior clinical performance. The ABPI was an important but under-weighted cue in diagnosis and the diagnosis (as a cue) was an important but under-weighted cue in treatment choice. Despite high levels of experience, nurses were under-confident in their judgements. A range of cognitive approaches to reasoning were apparent.
The main contribution of this thesis is exposing the complexity of the clinical environment for leg ulceration and in setting out models for diagnostic judgment and treatment choices for venous leg ulceration. These models provide a starting point for developing robust strategies for supporting community nurses’ judgement and decision making