SHINE: Putting surgical outcomes data to work
Guy Thorburn on behalf of STAAR (St Andrew’s Anglia Ruskin Research Group)
Funded by the Health Foundation, an independent charity working to continuously improve the quality of health care in the UK.
There is widespread awareness of the importance of monitoring and/or publishing surgical outcomes data. However there is less acknowledgement that monitoring outcomes is a necessary but not sufficient step in the process of improving those outcomes. Furthermore, surgical outcomes data without the context of patient risk factors can be misleading and detrimental.
We are therefore piloting a toolkit that allows clinicians to collect operative information, risk factor information, and operative outcomes prospectively. The initial pilot is in Clefts, Burns and Microsurgery at one centre. We use bespoke web-based software. It collates the information, corrects for the risk factors for individual patients, and instantly presents the updated information to the clinician in an intuitive graphical form. The system uses CUSUM and related statistical methods.1
This tool is particularly good at rapidly identifying runs of either better- or worse- than expected outcomes. The software also alerts the clinicians when predefined limits are reached, and provides a standardised method for acting on the information. The alerts are deliberately set as an early warning system, therefore within typical confidence limits (such as 95% probability). The system does not use comparative statistics, whether between surgeons or units, instead focussing on quality improvement for all. However it does collect the data that clinicians would require if they later wish to export for comparative use.
A particularly useful aspect of the system is that it can highlight runs of good form, and provides a structure to ensure these are analysed and reproduced. Previous research indicates that clinicians and teams are likely to respond more rapidly and effectively than to negative prompts.
The metrics we are assessing in this project include: clinician satisfaction with the interface and efficiency of data collection; completeness of data collection; improved resource use; impact on complication rates.
1 Roberts G, Thorburn G, Collins D, Smailes S, Dziewulski P. Development and implementation of prospective outcome monitoring in a regional burns service using cumulative sum (CUSUM) techniques. Burns. 2012 Dec 27. pii: S0305-4179(12)00350-6. doi: 10.1016/j.burns.2012.10.018. [Epub ahead of print]
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