Amit Patel

Several factors affect the rate of complication. Some are outlined below …

1. Quality of data (e.g. Definition of complications, details, the way and by whom data is collected)
2. Completeness of data (e.g. Failure to record known and unknown complications. Patient attending different hospital after discharge)
3. Pre-existing co-morbidities (e.g. Young fit vs. old frail patients)
4. Expertise of surgeon (e.g. Training, experience, workload and ability to self-criticise)
5. Level of risk aversion (e.g. Surgeons offering operations to high-risk patient have a higher complication rates)
6. Complexity of pathology (e.g. Benign vs. cancer conditions)
7. Complexity of procedure (e.g. First operation vs. multiple previous operations)
8. Hospital resources (e.g. availability of advanced technology and instruments)

If the aim of analyses is to monitor individual surgeons outcome over time, these factors do not matter much. However if the aim of analyses is to compare the outcomes among surgeons, inclusion of such factors is extremely vital to allow adjustment of the pre-existing risk and patient population variations. This, in reality, is very difficult to achieve. Any direct conclusive comparisons, therefore, between surgeons or hospitals should be done with an extreme caution. That said, such analyses and comparisons serve as an extremely useful and powerful monitoring tool to raise initial trigger for investigation when significantly higher than expected level of complication rate is observed.