Long Waiting Time in Canadian Universal Health Care

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

Table of Contents

Background
Problem
Hypothesis
Analysis
Conclusion
References

Background

Canadian Universal Health Care (UHC) is not the most problematic one in the world. This fact is supported by recent international surveys, which prove that healthcare systems are handled with varying degrees of success in different countries (Osborn, Squires, Doty, Sarnak, & Schneider, 2016). However, many of UHC’s issues have become prominent enough to be researched. One of the most common concerns of UHC is the waiting times (WTs). In this paper, the WTs of Canadian UHC will be investigated from the perspective of economic concepts and theories to determine potential solutions to this issue; it is hypothesized that tailored efficiency interventions should help to reduce WTs.

Problem

The problem of WT in UHC is multifaceted and nuanced. To prove that it exists, the Canadian Institute for Health Information [CIHI] (2018) demonstrates that depending on the procedure, up to 31% of patients receive relevant care during a period that is longer than the established benchmark (in 2018). Importantly, this number has been growing; for example, in 2014, only 18% of hip replacement patients did not receive their procedure in time, but in 2018, the number went up to 25%.

On the other hand, WTs are becoming shorter for hip fracture repair (HFR), bypass surgery, breast, and colorectal cancer surgery, and they are very short for radiation therapy. In general, WTs are more likely to increase for non-emergency cases (Moscelli, Siciliani, & Tonei, 2016). However, greater WTs are more likely to affect people with lower economic status and minorities (Hajizadeh, 2018; Martin et al., 2018; Socías et al., 2016). Importantly, WTs are not just inconvenient; they can be dangerous. Depending on a condition, increased WT can result in complications and readmissions, which imply worse health outcomes and increased costs (Moscelli et al., 2016; Pincus et al., 2018). As a worst-case scenario, WT can be connected to increased mortality (Bohm, Loucks, Wittmeier, Lix, & Oppenheimer, 2015; Moscelli et al., 2016). Also, the inconvenience of WT can be a cause for stress and anxiety, which are dangerous for one’s well-being (Tran et al., 2015). In the end, the goal of healthcare systems is to provide timely care (Allin, Veillard, Wang, & Grignon, 2015). Thus, time is an important factor in Canadian UHC, and WTs are a serious problem.

Hypothesis

An overview of relevant sources suggests that a common solution to reducing WT is improved efficiency, which is tied to resource scarcity. Here, it will be hypothesized that by identifying inefficiencies, WTs can be decreased. This process will involve equity-efficiency trade-offs and working with allocative efficiency. This way, scarce resources will be allocated in the most efficient ways, and WT in critical areas will be decreased.

Analysis

Theoretical Framework: Economic Models and Concepts

The presented paper uses a literature review and synthesis as a basis for its analysis. Since a recent article about an improvement effort, which is relevant for WT, is available, the paper will also include a case study. Both parts of the analysis will be framed with the help of economic terminology. Specifically, the concepts of efficiency, allocative efficiency, different types of economic evaluations, the Health Capital Model (HCM), and supply-and-demand dynamics will be introduced. Also, the topic of funding will be briefly mentioned. These concepts and frameworks will be discussed with the findings of the literature review for their mutual framing and explanation.

Analysis of the Issue of WT from the Perspective of Economic Models and Concepts

Research demonstrates that specific causes of prolonged WT are numerous. The most common ones include the shortage of specialists, inefficient patient transferring, inefficient communication, and inefficient guidelines that fail to prioritize cases appropriately (Bohm et al., 2015; Yadav, Goldberg, Barense, & Bell, 2016). Consequently, the primary issue is efficiency (and its connection to resource scarcity), which is a concept that can be described in economic terms.

Efficiency has been a very topical concern for healthcare for some time. Research proves that this statement applies to all healthcare systems, including that outside of Canada (Osborn et al., 2016). One of the reasons why it might be the case is that healthcare has to balance scarce resources to satisfy the sort of inelastic demand that is predicated on needs, which are often connected to survival (Ivers, Brown, & Detsky, 2018; Jaafaripooyan, Emamgholipour, & Raei, 2017). With the general belief that healthcare is a public good (Ivers et al., 2018; Weil, 2016), efficient resource management is crucial for Canadian UHC to ensure the benefit of as many people as possible (with prioritization of those who are in most need). From this perspective, prolonged WT is a sign of inefficiency that can have devastating consequences.

Efficiency, especially when related to WT, tends to come with trade-offs, including those related to equity. For example, the most common solution to WT in critical life-and-death cases is the prioritization of such cases (Bohm et al., 2015). This prioritization tends to depend on the volumes of resources available (supply) and the significance of need (demand) (Sepehri, 2015). Admittedly, an alternative individual solution to WTs is having a greater paying capacity, which is demonstrated by the fact that poorer Canadians are more likely to have greater WTs than richer ones (Hajizadeh, 2018). However, it is not a solution to the systemic issue. Rather, the specifics of the demand for healthcare services suggest the importance of the adequate prioritization of patients with the greatest needs in the context of limited resources.

One of the scarce resources that Canadian UHC is constrained by, which is critical for WT, is the shortage of healthcare professionals. Importantly, this scarcity varies by specialty and geographic location (Jiang, 2016; Yadav et al., 2016). Naturally, long-term policies can help to acquire more units of particular resources and relocate them to underserved regions. For example, in the case of professionals, better salaries in rural regions can be helpful, and for equipment, improved funding can work, even though funds management is another important concern for UHC (Jiang, 2016). However, at any given time, the issue of the scarcity of resources is resolved with the help of their management. For example, a common solution to the scarcity of professionals (or specific equipment) is the facilitation of transfers for people from underserved areas into better-served ones (Bohm et al., 2015). This method does appear to help to restructure the availability of a resource, which is why it can reduce WT.

However, another problem that is frequently encountered during resource management is the efficiency of its processes. For example, Bohm et al. (2015) commented on the challenge of transporting people to receive crucial services and transporting them back to ensure that they do not take up beds, which are in high demand. Consequently, while the described solution is supposed to facilitate more efficient use of resources and reduced WT, it can have the opposite effect when it is not done correctly. Consequently, WT reduction depends on developing and testing efficient solutions.

To ensure the efficiency of a healthcare intervention, it is helpful to use economic analyses. A cost-effectiveness analysis would focus on the natural units of health outcomes that are received for a given price, a cost-utility analysis would introduce the concept of Quality-Adjusted Life Years, and a cost-benefit analysis would attempt to represent health outcomes with monetary equivalents (Beecham et al., 2019; Torre-Díez, López-Coronado, Vaca, Aguado, & Castro, 2015). All these approaches are connected to the HCM, according to which health can be viewed as a resource and investment, which means that units of health capital can be determined and even quantified (Sepehri, 2015). Economic analysis can help to assess a program, policy, guideline, or any other intervention, which is why these three tools are another solution to the WT problem. When a new intervention aimed at WT reduction is implemented, the analysis of its outcomes (especially as compared to a prior solution) per required costs should determine its usefulness.

To summarize, research suggests that the primary cause of extended WT is efficiency. Efficiency, in turn, is connected to the scarcity of resources, including professionals, technology, and funding, because allocative efficiency depends on the effective distribution of resources. Future policies can be developed to generate more resources of some type (for instance, professionals). However, in every individual situation, the analysis of solutions to their management should be guided by an understanding of supply, demand, and the specifics of health capital. The resulting decisions may result in trade-offs, but economic analysis, which accounts for the value of diverse health outcomes, may be carried out to determine the effectiveness of particular choices. This framework will now be illustrated with the help of a case study.

Case study information

CIHI (2018) reports reduced times in HFR as the only WT that went down for a benchmarked procedure in Canada over the past few years. A recent study investigated a quality improvement effort that successfully targeted such an outcome. Specifically, Bohm et al. (2015) carried out a pre-test post-test inquiry, and it evaluated the outcomes of a WT solution which was designed in response to specific delay issues that had been identified for HFR patients.

The intervention was very complex because multiple fixable delays had been found. From the perspective of resource-intensive features, the intervention involved creating additional operating room slates for orthopedic trauma patients. Other than that, the project involved a review of guidelines, relevant education for staff (including instructions for working with patients on clopidogrel), and improved communication between facilities to ensure the efficient management of cases. Three of the solution components were introduced to improve rural patient transfers into and from surgical facilities. The relevant guideline changes included the requirement for accepting rural patients in any case (regardless of bed availability) and their direct transferring to surgical wards. Also, the intervention required reserving medicine consultations for specific cases only. The solution proved to be effective; Bohm et al. (2015) show that it reduced WTs and mortality (at one month and one year) in HFR patients.

Theory application

HFR is a good example of a critical need, in which WT is a risk factor. As a result of greater WT, especially WT that exceeds 48 hours, HFR cases develop complications (Pincus et al., 2018). Therefore, based on a significant need in the context of limited resources, HFR can be justifiably prioritized. This decision can result in equity-efficiency trade-offs, an example of which is the creation of additional surgery slates for orthopedic patients. It is reasonable to assume that the management of scarce resources (surgery rooms and equipment, time, professionals) was required. Similarly, trade-offs were most likely necessary due to the demand for accepting rural HFR patients regardless of bed availability. The prioritization of HFR is a direct illustration of working to redirect scarce resources toward the greatest healthcare needs.

However, some resources must have been saved by managing them more efficiently. For example, improved collaboration with other centers enabled quick repatriation of patients who no longer required services; consequently, the availability of wards and beds must have improved. Similarly, the authors commented on updating the guidelines to remove excessive pre-operation procedures (clopidogrel delays and medicine consultations), thus saving the most crucial resource for WT, which is time.

From the perspective of evaluating the solution, the authors focused on health capital; the primary outcome of the study was mortality. Additionally, the authors commented on the length of stay, which also decreased dramatically. The latter outcome was beneficial from the perspectives of costs and efficiency. Moreover, it is a fact that excessive WT in HFR cases leads to complications, which also increase costs (Pincus et al., 2018). Therefore, the positive outcomes and cost-savings of the intervention must have been noteworthy. On the other hand, it is also important that the solution’s trade-offs could result in costs, increased WTs, and other problems for other, less prioritized cases. Therefore, the outcomes of the solution are multifaceted and could benefit from economic analyses, but Bohm et al. (2015) did not conduct one.

To summarize, the presented case illustrates the value that economic framing can have for the analysis of the WT issue. The named frameworks can help to explain, justify, or guide the prioritization of cases; they can also direct resource management efforts and be used to evaluate specific solutions. When viewed from the perspective of supply and demand, WT in HFR is the result of limited resources and their inefficient application. By targeting these two issues, as well as their more specific manifestations, Bohm et al. (2015) managed to improve WT and health outcomes in HFR patients. While the presented case incorporates a critical case of WT, it is not difficult to apply the same logic to less life-threatening issues. Rather, the example should be used as an illustration of a successful WT reduction effort, and its methods can be used elsewhere.

Conclusion

Extended WT in Canadian UHC is a significant problem because of the numerous negative outcomes that can be associated with it; they can range from stress to deaths. Research suggests that the primary cause of extended WT is efficiency, which is connected to the problem of resource scarcity. Since both terms are economic, the application of HCM, economic analyses, and the concepts of supply and demand can guide and help to evaluate solutions to WT. Based on one case study, this paper shows that an economic framework can assist in prioritizing needs, promote an appropriate distribution of resources, direct one toward solutions to inefficiencies, and assess them and their outcomes. Consequently, the application of economic terms to healthcare is justified, and it may be one of the keys to improved WT in Canadian UHC.

References

Allin, S., Veillard, J., Wang, L., & Grignon, M. (2015). How can health system efficiency be improved in Canada? Healthcare Policy | Politiques De Santé, 11(1), 33-45. Web.

Beecham, J., Bonin, E. M., Görlich, D., Baños, R., Beintner, I., Buntrock, C.,… Potterton, R. (2019). Assessing the costs and cost-effectiveness of ICare internet-based interventions (protocol). Internet Interventions, 16, 12-19. Web.

Bohm, E., Loucks, L., Wittmeier, K., Lix, L., & Oppenheimer, L. (2015). Reduced time to surgery improves mortality and length of stay following hip fracture: Results from an intervention study in a Canadian health authority. Canadian Journal of Surgery, 58(4), 257-263. Web.

Canadian Institute for Health Information. (2018). Canada: Benchmarks for treatment and wait time in. Web.

Hajizadeh, M. (2018). Does socioeconomic status affect lengthy wait time in Canada? Evidence from Canadian Community Health Surveys. The European Journal of Health Economics, 19(3), 369-383. Web.

Ivers, N., Brown, A., & Detsky, A. (2018). Lessons from the Canadian experience with single-payer health insurance. JAMA Internal Medicine, 178(9), 1250. Web.

Jaafaripooyan, E., Emamgholipour, S., & Raei, B. (2017). Efficiency measurement of health care organizations: What models are used? Medical Journal of the Islamic Republic of Iran, 31(1), 505-511. Web.

Jiang, S. (2016). Physician shortage problem in Canada from 1980 to 2015. Journal of General Practice, 4(6), 1000e112. Web.

Martin, D., Miller, A., Quesnel-Vallée, A., Caron, N., Vissandjée, B., & Marchildon, G. (2018). Canada’s universal health-care system: Achieving its potential. The Lancet, 391(10131), 1718-1735. Web.

Moscelli, G., Siciliani, L., & Tonei, V. (2016). Do waiting times affect health outcomes? Evidence from coronary bypass. Social Science & Medicine, 161, 151-159. Web.

Osborn, R., Squires, D., Doty, M., Sarnak, D., & Schneider, E. (2016). In new survey of eleven countries, US adults still struggle with access to and affordability of health care. Health Affairs, 35(12), 2327-2336. Web.

Pincus, D., Wasserstein, D., Ravi, B., Byrne, J. P., Huang, A., Paterson, J. M.,… Wodchis, W. P. (2018). Reporting and evaluating wait times for urgent hip fracture surgery in Ontario, Canada. Canadian Medical Association Journal, 190(23), E702-E709. Web.

Sepehri, A. (2015). A critique of Grossman’s canonical model of health capital. International Journal of Health Services, 45(4), 762-778. Web.

Socías, M., Shoveller, J., Bean, C., Nguyen, P., Montaner, J., & Shannon, K. (2016). Universal coverage without universal access: Institutional barriers to health care among women sex workers in Vancouver, Canada. PLOS ONE, 11(5), e0155828. Web.

Torre-Díez, I., López-Coronado, M., Vaca, C., Aguado, J., & Castro, C. (2015). Cost-utility and cost-effectiveness studies of telemedicine, electronic, and mobile health systems in the literature: A systematic review. Telemedicine and E-Health, 21(2), 81-85. Web.

Tran, K., Sandoval, C., Rahal, R., Porter, G., Siemens, R., Hernandez, J.,… Collaboration with the System Performance Steering Committee. (2015). Wait times for prostate cancer treatment and patient perceptions of care in Canada: A mixed-methods report. Current Oncology, 22(5), 361. Web.

Weil, T. (2016). What can the Canadians and Americans learn from each other’s health care systems? The International Journal of Health Planning and Management, 31(3), 349-370. Web.

Yadav, G., Goldberg, H., Barense, M., & Bell, C. (2016). A cross-sectional survey of population-wide wait times for patients seeking medical vs. cosmetic dermatologic care. PLOS ONE, 11(9), e0162767. Web.

Click Here To Order Now!