Our results indicate a marked increase in the rate of hip and knee replacement surgery over a 10-year period as well as an increasing seasonal variation in surgeries. The provision of services decreases during holiday times. Peak performance occurs in the fall months. Despite the increase in the provision of hip and knee replacements, the waiting times for these services have increased dramatically. Ontario data indicates that fewer 50% of eligible patients receive a joint replacement within 6 months.  What explains this seeming paradox? We hypothesize that seasonal fluctuation in service provision contributes to the problem.
There appears to be two major driving factors that can contribute to increasing waiting times. The segment of the population over the age of 65 has increased by approximately 23% percent over the years in this study (1,172,620 to 1,446,227). Secondly, there is marked seasonal variation in the provision of surgery indicating that the provision of surgery is not constant. Peak service occurs only in the months of October, November, and to a lesser extent, May and June. This may reflect both provider and recipient preferences not to have surgery during holiday times. Although holidays exert an influence on the provision of service, they do not affect the demand which relates to osteoarthritis, the predominant indication for surgery. This has not changed during the study period. Holidays exert a significant influence on the rate of service provision as the troughs correspond to the summer holidays, winter holidays and March school breaks.
As well, it is possible that utilization caps in the province of Ontario explain the lower rates of service provision during January-March. Until 2005, the salary of orthopedic surgeons was capped at a certain level adding financial disincentives to perform surgery for which they would not be full remunerated. The fiscal year runs from April 1 – March 31, so the January – March rates corresponds to the time that surgeons would be approaching the cap. As the caps have been lifted in 2005, their effect on rates will be testable in the years to come.
In a simple schemata, waiting lists can be understood operationally in terms of the relationship between inputs (increasing number of people needing surgery), throughputs (including seasonal fluctuation and system features), and outputs (completed surgeries). It can be hypothesized that waiting times for hip and knee replacement could be reduced with more constant supply. Eliminating seasonal fluctuations in service provision and benchmarking services to peak delivery months would increase capacity by about 400 to 500 procedures per annum. The cyclic peaks and troughs likely exacerbate waiting times as the cycle is repeated annually while the need increases steadily.
The results highlight the importance of system behaviour in seasonal fluctuation of service delivery. The OECD report identified several determinants of waiting lists including physician availability and remuneration but did not consider time of surgery as an important factor in the creation of waiting times . Recent reports on waiting times for hip and knee replacements in Canada have examined geographical variation, but did not examine rates as dynamic over time despite recognizing time of surgery as a crucial component of waiting times . Although it is well known that seasonal increases of health service demand are associated with viral pathogens, such as influenza, it is less well appreciated the extent to which human behaviour influences health services delivery. Attempts to rectify waiting lists without considering human behaviour will likely fail to address many issues determining waiting lists.
There are certain caveats to this analysis. First, we lack an estimate for the prevalence of need for surgery. We have assumed that the prevalence of need has increased over time in this analysis using an aging population as a proxy for surgical demand. Secondly, this analysis is limited to the province of Ontario as the unit of aggregation. Therefore, it will overlook important geographic variations within the system which may play a role in waiting list dynamics. Such factors as OR time and availability, and the number of surgeons available to perform such surgeries, are obviously important determinants of waiting times. We restricted our analysis to this population as it is the population with by far the greatest need for the procedure.