New Zealand Statistical Association 2024 Conference

Soyoon Annie Park

University of Auckland

Investigating the effect of repeated patients in surgical outcomes research

Evaluating post-operative outcomes using retrospectively collected health data often involves patients with multiple eligible operations. Including all operations can violate statistical independence assumptions. A common solution is to include only the first operation.

In a retrospective audit of postoperative outcomes, we found significant variation in mortality rates based on how repeat patients were accounted for. Specifically, our first cohort had a 90-day mortality rate of 3.6% when selecting the first operations, compared to 4.2% with random selection. Another cohort had a mortality rate of 2.8%, compared to 3.4% with random selection.

Accurate reporting and analysis of post-operative outcomes is highly important in the field of surgical and peri-operative medicine, with mortality serving as a gold-standard objective measure for assessing performance. However, in longitudinal data sets where individuals may be exposed to an operation of interest multiple times, there is no clear guidance on how to select an index event.

Major surgical outcome studies often use the first operation selection approach, possibly to minimise bias. This approach may underestimate mortality risk, as patients undergoing frequent surgeries are less likely to die during the first contact. This effect may vary with the study period, leading to inconsistent bias. To our knowledge, no research has examined the impact of different methods for handling repeat patients on operative mortality. This study investigates these methods using health data from the Ministry of Health and Te Whatu Ora Te Toka Tumai and aims to refine methods to accurately capture the true mortality risk associated with surgical procedures.