Table 3. Examples of how dimensions of technology-related prescribing errors can be used to prioritise CPOE optimisation goals.

Optimisation goal	Relevant TRE dimension to begin review	Explanation
Reduce dose errors	Manifestation of error (data subset: all dose errors)	Examine dose errors to ascertain their underlying mechanisms to identify areas for CPOE improvement. Dose errors can be further stratified by those with potential or actual harm to patients.
Reduce errors with a high risk to patient safety	Manifestation of error (data subset: errors rated as having a high potential for harm AND errors with high-risk medications)	Examine errors with higher potential harm rating and errors with high-risk medications to identify their underlying mechanisms. These can be further stratified by their clinical error category (eg, duplicate therapy error).
Optimise CPOE drop-down menus	Underlying mechanisms of errors (data subset: selection errors)	Examine all selection errors and their manifestations (ie, clinical error types) to identify where they are occurring at a higher frequency, signalling need for drop-down menu modification.

CPOEcomputerised provider order entryTREtechnology-related error