It is interesting to consider that the median population age in Canada is 40 years and furthermore, that in British Columbia the average age is even higher at 41.4 years (Statistics Canada, Population estimates, age distribution and median age as of July 1, 2012, Canada, provinces and territories, 2012). With an average life expectancy of 83 years for females and 79 years for males, we can deduct that most of our current population has reached the middle age category and is moving upwards into the senior category (Statistics Canada, Life expectancy at birth, by sex, by province, 2012).
A journal article by Zhang et al. notes the need for Long Term Care (LTC) capacity planning as our elderly population grows. This article discusses the importance of finding the appropriate approach to take when determining the appropriate level of investment in capacity for these LTC facilities, while also determining that the ideal goal of successfully doing so would be to set an ideal wait time to be admitted to these facilitates.
Principles of Operations Management, a textbook by Heizer & Render, teaches us that capacity planning is a detrimental decision, as it require a large portion of a given businesses fixed costs (Heizer & Render, 2010).This is because capacity decisions are at the heart of a processes ability to be effective. Regardless of if a company is in the business of manufacturing goods, or providing a service, if it cannot produce to meet the demand due to an inadequate capacity, it has the grave potential to disappoint consumers, lose loyalty and furthermore, lose revenues. On the other side of the spectrum, it is also devastating to have an abundance of capacity, as the business can end up being ineffective in costs, leading to idle and unused space.
Heizer & Render note that in determining appropriate capacity levels in a service sector, such as a LTC facility, many considerations must be taken into account. These include demand management or capacity management, as well as bottlenecks. (Heizer & Render, 2010). Managing demand in a service sector entails putting into place an appropriate scheduling system for patients, clients or customers. Managing capacity is utilizing the appropriate amount of staff available to service the given patients, clients or customers. In current topic of LTC facilities, we can identify a detrimental bottleneck, whereas bottlenecks are “the limiting factor or constraint in a system” (Heizer & Render, 2010).
Adequate planning for capacity by examining the bottlenecks of LTC facilities is detrimental to our society. With the aging population, we may end up seeing a bottleneck in the form of bed availability. If we do not have enough space in these LTC facilities, then these individuals will end up seeking care in hospitals. In Canada, hospitals generally see an average patient stay for 7 days (OECD, 2011). For elderly patients in need of long term care, an average stay ranges between 3 to 4 years (The Council on Aging of Ottawa, 2008). Having the elderly seek care in hospitals will create a domino effect in which the average citizen who is in need of emergency services will be unable to be treated, as these beds will be taken by elderly individuals who, on one hand, do need care, but on the other hand, are not proper facility for long term stay.
Zhang et al propose that the proper means for capacity planning in LTC facilitates to avoid the bottleneck of bed availability is using simulation optimization. Without getting too far into the elaborate algorithmic gist of this concept, it can be surmised that simulation optimization is a process that considers a variety of factors such as demographic and survivals statistics (and forecasting), while also putting in practice a “multiyear planning horizon” (Zhang, Puterman, Nelson, & Atkins, 2012). A multiyear planning horizon is essential, as it takes into consideration decisions that require a minimal time horizons (short range) while also being able to focus in on decision that require multiple years to plan (long range). It is this particular time horizon that is to aid in developing an idea wait time at LTC facilities, to combat the potential growth of our aging population.
The way in which we choose to plan for the elderly and their inevitable need for long term care is critical to our own health, in the present day and future. We all may need the emergency services provided by our local hospitals, and in the future, we too may require assistance from long term care facilities.
How does Canada’s aging population affect capacity of the healthcare system?
CHFI. (n.d.). Image: The Aging Population. Retrieved January 27, 2013, from CHFI: http://www.cfhi-fcass.ca/Libraries/Cartoons-Copyright/Aging-EN.sflb.ashx
Heizer, J., & Render, B. (2010). Capacity amd Constraint Management. Upper Saddle River, New Jersey: Prentice Hall.
OECD (2011), “Average length of stay in hospitals”, in Health at a Glance 2011: OECD Indicators, OECD Publishing. http://dx.doi.org/10.1787/health_glance-2011-33-en
Statistics Canada. (2012, May 31). Life expectancy at birth, by sex, by province. Retrieved January 26, 2013, from Statistics Canada: http://www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/health26-eng.htm
Statistics Canada. (2012, September 27). Population estimates1, age distribution and median age as of July 1, 2012, Canada, provinces and territories. Retrieved January 26, 2013, from Statistics Canada: http://www.statcan.gc.ca/daily-quotidien/120927/t120927b003-eng.htm
The Council on Aging of Ottawa. (2008). Long Term Care Insurance in Canada: What is it and do I need it? ISBN 1-895495-41-5.
Zhang, Y., Puterman, M. L., Nelson, M., & Atkins, D. (2012). A Simulation Optimization Approach to Long-Term Care Capacity Planning. Operations Research, 60(2), pp. 249–261. doi:http://dx.doi.org/10.1287/opre.1110.1026