The challenges in providing timely access to health care are becoming increasingly common and cross many disciplines. Whether the conversation is around delays for elective surgery, emergency department overcrowding or long waits for specialist appointments, the frustration is felt by patients, practitioners and healthcare administrators alike. The recent Preferential Access Inquiry in Alberta highlighted that long wait times lead to inappropriate attempts to expedite access, and suggested that Alberta implement waiting list management strategies. However, such strategies are expensive and have not only been largely unsuccessful, but they represent an acceptance of long wait times rather than a proactive approach to reducing them.
Simply put, waiting lists occur when the demand for a service exceeds the system’s ability to provide that service. The natural conclusion is that there is an inadequate supply of resources (e.g. providers, testing facilities, hospital beds) to meet patient demand. While some systems truly do not have sufficient resources, in reality wait times can be reduced by making more effective use of available resources. In essence, to improve access we need to find ways to work smarter not harder.
As part of a systems approach to the problem of timely access, it is important to understand the relationship between supply and demand. One such relationship, utilization (defined as demand divided by supply), can give us a clearer sense of why delays are occurring.
For example, if we have the ability to perform four CT scans per day, but have a daily average of five patients requiring a scan, our expected utilization level is 5/4 = 1.25. This system will not be able to meet demand, and we expect wait times to increase over time. If we have 20 CT scanners for those five patients, the expected utilization is 0.25, and we expect little or no wait.
Where the problem becomes more challenging is when the expected utilization is approximately one; when demand levels approach resource supply, the formation of waiting lists depends on other factors such as variation. There are two categories for the cause of variation. Natural variation occurs for reasons that are out of our control, such as the clinical case mix or the arrival frequency of patients. Artificial variation is due to system design factors, such as appointment scheduling rules and staff availability.
For example, if elective surgical patients are admitted on Mondays to undergo surgery during the week, there will be fewer beds early in the week and possibly many beds later in the week as these elective patients are discharged. The impact on the hospital of this type of artificial variation is that patients arriving through the emergency department will experience avoidable delays early in the week.
The approach to long wait times in health care has historically been to argue for more resources or to develop complex policies to manage wait times. Both of these approaches may be relevant, but each represents additional cost to the system. Rather, we need to give more thought to the impact of variation; specifically, we should aim to eliminate artificial variation (by smoothing elective surgical admissions through the week, for example) and manage natural variation (perhaps by trying to schedule the existing resource supply around expected demand patterns).
With increasing pressures to meet patient demand, constrained budgets may limit the ability to increase resources to eliminate waiting lists. Instead, an analysis of demand, supply, utilization and variation can provide a clearer picture of why delays might be occurring and how best to mitigate them. Currently, this approach is being used by operations researchers, in partnership with Canadian health care organizations, to improve the efficiency of health services delivery. Examples from Alberta include the reduction in wait times for elective joint replacement surgery and the improvement of response times for ambulance services. However, these are isolated examples, of which there are far too few given that the lack of timely access is such a widespread problem in health care. It is time for other health care systems to follow suit.