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Published on: November 10, 2023
What can we learn about the impact of cancelled planned operations on waiting times? A case study using the 2017/18
Maria Ana Matias1, Rita Santos2, Nils Gutacker2
1Centre for Health Economics, University of York, York, YO10 5DD, UK. mariaana.matias@york.ac.uk.
Background:
Cancelled operations can potentially impact both health and patient experience through their effect on waiting times. However, identifying causal relationships is challenging. One possible solution is to consider 'exogenous shocks' to the system as a type of natural experiment to quantify impacts. In this study, we investigate the 2017/18 national cancellation policy in the English National Health Service (NHS), introduced to alleviate winter pressures due to influenza related admissions. Our aim is to see whether this policy can be used to isolate the impact of changes in the supply of care on waiting times and so inform system recovery from major exogenous shocks, such as the coronavirus pandemic.
Methods:
To assess the impact of cancellations on hospital activity and waiting times, we use aggregate quarterly hospital-level data on planned admissions and last-minute planned operations (2013/14 to 2019/20); and individual-level data on waiting times for planned care (2015/16 to 2018/19). We analyse trends in volume of activity and waiting times, and examine waiting times distributions for patients who were admitted for planned surgery from the waiting list before and after the 2017/18 cancellation policy.
Results:
The final quarter of 2017/18 had the highest number of cancelled planned operations since 2013/14 and the lowest number of planned admissions since 2015/16. However, the trend in mean and median waiting times was similar across the study period. Therefore, the 2017/18 national postponement policy had no identifiable impact on waiting times trends.
Conclusions:
Despite the high numbers of cancelled planned operations in 2017/18, we could not identify an impact on waiting times. A plausible explanation is that hospital managers routinely anticipate winter pressures and reduce planned activity to manage bed occupancy. Therefore, the 2017/18 national postponement policy merely reinforced existing local decisions. The lack of a suitable counterfactual from which to infer what would have happened in 2017/18 in the absence of a postponement policy makes it impossible to isolate the impact on waiting times. This means that previous NHS cancellation policies are of limited use for informing system recovery from major exogenous shocks, such as the coronavirus pandemic.
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