Multiple sclerosis in Canada 2011 to 2031: results of a microsimulation modelling study of epidemiological and economic impacts - HPCDP: Volume 37-2, February 2017
Volume 37 · Number 2 · February 2017
Multiple sclerosis in Canada 2011 to 2031: results of a microsimulation modelling study of epidemiological and economic impacts
Nana Amankwah, MScFootnote 1. ; Ruth Ann Marrie, MD, PhDFootnote 2.; Christina Bancej, PhDFootnote 1. ; Rochelle Garner, PhDFootnote 3. ; Douglas G. Manuel, MDFootnote 3. ,Footnote 4. ,Footnote 5. ,Footnote 6. ,Footnote 7. ,Footnote 8. ,Footnote 9. ; Ron Wall, PhDFootnote 1. ; Philippe Finès, PhDFootnote 3. ; Julie Bernier, MAFootnote 3. ; Karen Tu, MDFootnote 9. ,Footnote 10. ,Footnote 11. ; Kim Reimer, BScFootnote 12.
This article has been peer reviewed.
Correspondence: Nana Amankwah, Social Determinants and Science Integration Directorate, Health Promotion and Chronic Disease Prevention Branch, Public Health Agency of Canada, Room 903 A3, 785 Carling Avenue, Ottawa, ON K1A 0K9; Tel: 613-291-3181; Email: email@example.com
Introduction: The objective of our study was to present model-based estimates and projections on current and future health and economic impacts of multiple sclerosis (MS) in Canada over a 20-year time horizon (2011–2031).
Methods: Using Statistics Canada’s Population Health Microsimulation Model (POHEM) framework, specifically the population-based longitudinal, microsimulation model named, we identified people with MS from health administrative data sources and derived incidence and mortality rate parameters from a British Columbia population-based cohort for future MS incidence and mortality projections. We also included a utility-based measure (Health Utilities Index Mark 3) reflecting states of functional health to allow projections of health-related quality of life. Finally, we estimated caregiving parameters and health care costs from Canadian national surveys and health administrative data and included them as model parameters to assess the health and economic impact of the neurological conditions.
Results: The number of incident MS cases is expected to rise slightly from 4 051 cases in 2011 to 4 794 cases per 100,000 population in 2031, and the number of Canadians affected by MS will increase from 98 385 in 2011 to 133 635 in 2031. The total per capita health care cost (excluding out-of-pocket expenses) for adults aged 20 and older in 2011 was about $16 800 for individuals with MS, and approximately $2 500 for individuals without a neurological condition. Thus, after accounting for additional expenditures due to MS (excluding out-of-pocket expenses), total annual health sector costs for MS are expected to reach $2.0 billion by 2031. As well, the average out-of-pocket expenditure for people with MS was around $1 300 annually throughout the projection period.
Conclusion: MS is associated with a significant economic burden on society, since it usually affects young adults during prime career- and family-building years. Canada has a particularly high prevalence of MS, so research such as the present study is essential to provide a better understanding of the current and future negative impacts of MS on the Canadian population, so that health care system policymakers can best plan how to meet the needs of patients who are affected by MS. These findings also suggest that identifying strategies to prevent MS and more effectively treat the disease are needed to mitigate these future impacts.
Keywords: multiple sclerosis, economic burden, Canada, microsimulation modelling, incidence, prevalence
- Multiple sclerosis (MS) is associated with a significant economic burden on society.
- The number of incident MS cases is expected to rise slightly in Canada from 4 051 cases in 2011 to 4 794 cases per 100 000 population in 2031.
- The MS prevalence for women aged 20 years and older is approximately 3 times higher than that for men.
- Most people affected by MS have an informal caregiver.
- Direct costs and indirect costs (e.g. out-of-pocket expenses) associated with MS are expected to increase over the next 20 years.
Multiple sclerosis (MS) is an unpredictable, chronic, inflammatory and degenerative disease of the central nervous systemFootnote 1,Footnote 2,Footnote 3,Footnote 4. It is the most common non-traumatic disabling neurological condition among young adults in CanadaFootnote 5. Onset is typically between the ages of 20 and 40 years, and women are affected more often than menFootnote 1,Footnote 5 . Although the etiology of MS remains unknown, genetic predisposition and environmental factors jointly trigger the diseaseFootnote 2,Footnote 6.
The prevalence of MS varies geographically, and high-prevalence areas include Canada, the northern United States, most of northern Europe, New Zealand, southeastern Australia and IsraelFootnote 9,Footnote 10,Footnote 11,Footnote 12. According to the MS Society of Canada’s Action on MS reportFootnote 13, nearly 80% of Canadians with MS may find themselves unemployed. Determining the reasons for the high prevalence and lessening the burden of living with MS and other chronic neurological conditions have become major health policy concerns in Canada. Therefore, the Government of Canada initiated the National Population Health Study of Neurological Conditions (NPHSNC) to increase understanding of these conditions, with the long-term goal of reducing the burden of neurological conditions in CanadaFootnote 9.
Given the societal effects of MS, it is essential that comprehensive studies are undertaken to deal with the current impact and to plan for the future impact of the disease. We used Statistics Canada’s Population Health Microsimulation Model (POHEM) framework, specifically the population-based, longitudinal, microsimulation model named POHEM-Neurological, to examine the health and economic impacts of the disease in Canada, including the expected incidence, prevalence, mortality and direct and indirect costs associated with MS over a 20-year time horizon from 2011 to 2031. The objective of this study is to provide key information to help shape strategies and public health policies on MS.
Population Health Model (POHEM)-Neurological
Statistics Canada’s POHEM-Neurological framework is a population-based, longitudinal, microsimulation modelFootnote 14 created as part of Canada’s NPHSNC. The NPHSNC included 13 research projects and three national surveys aimed at examining multiple neurological conditions affecting CanadiansFootnote 9,Footnote 14,Footnote 15. The POHEM model was generated using MODGEN (Model Generator) software, version 11, a microsimulation programming language developed by Statistics CanadaFootnote 14. The model was developed to project the burden of select neurological conditions in Canada, including MS, from a societal perspective that includes health impacts and direct and indirect heath care costs by synthesizing the wide range of information from projects within the NPHSNC. POHEM is an empirically grounded model that uses Canadian demographic data and estimates of disease incidence and mortality rates to produce projections over the life cycle dynamics of CanadiansFootnote 16. The model’s basic unit of analysis is individual people, or “actors,” whose life course is modelled in continuous time using a Monte CarloFootnote * approach. The dynamic simulation recreates the Canadian population at a given point in time (historically and in the future) and ages it, one actor at a time, until each actor’s death.
Caregivers, clinicians and individuals with policy expertise provided advisory input to the POHEM-Neurological modelFootnote 14. The project’s advisors and research team created the model specification, including the purpose, structure and data sources. The main characteristics of the model were as follows:
- Population-based–reflecting the Canadian population, including important subpopulations designated by age, sex and region.
- Open with respect to population–allowing the population to change over time to reflect historical and projected births, deaths, immigration and emigration.
- Coherent and consistent–using a common definition of MS throughout the model and consistent in the approach used to model the epidemiology and costs related to the condition. Case ascertainment required that a clinician diagnose MS. A generic preference-based measure of health-related quality of life, the Health Utilities Index Mark 3 (HUI3; described later), was used to ascertain disease severityFootnote 17.
- High predictive accuracy–able to generate accurate projections for the total Canadian population and for specific sex and age subgroups.
- Useful for population health planning–can be used to estimate future MS burden, including health care costs and caregiver burden.
- Flexible and robust–able to be developed further. Risk factors for the development of MS apart from age and sex were excluded from the current study. However, sociodemographic and health behaviour risk factors are part of other POHEM disease models and NPHSNC studies, and risk factors could be included in future MS modellingFootnote 18.
Four steps made up the process of microsimulation model development: initialization, yearly updates, model validation and projection (Table 1). Only Canadian, population-based data sources were used for model initialization and yearly updates (data not shown; available from the authors upon request).
|Model generating step||Model activity||Details of the model step|
|Step 1: Generate an initial Canadian population||Initiated a predictive model by creating a synthetic cohort of Canadians.||Historic birth cohorts combined with annual deaths, immigration, and emigration. Observed demographic data to 2006 projected to 2031.Footnote a|
|Step 2: Update annual MS incidence and other model parameters||Each year to 2031, update population characteristics, MS incidence, health status and health care costs.||Each year, update synthetic cohort for demographic changes, MS incidence and deaths. For people with and without MS, estimate Health Utilities Index, health care use (formal and informal) and deaths.|
|Step 3: Validate and calibrate the model||Compare projected MS to observed prevalence in 2009.||Compare projected to observed MS prevalence, by age and sex. Calibrate the model if needed (no calibration undertaken for MS).|
|Step 4: Generate final projections from 2011–2031||Project MS incidence, prevalence, mortality, health utilities index and health care costs from 2011–2031.||Generate output tables from projections.|
Abbreviations: MS, multiple sclerosis; POHEM, Population Health Model.
Initialization began with historic birth cohorts from 1872, which we subjected to the observed historic death rate, similar to other Statistics Canada health modelsFootnote 19,Footnote 20. We added migration (immigration and emigration) to the birth cohorts, also reflecting historic observed or estimated events. The birth cohorts used observed data up to 2006; and projected births, deaths and migration following standard Canadian population projections (mid-growth scenario) as estimated by Statistics Canada for 2007 onward.
Yearly updates of actors’ health profiles
An actor’s health profile consists of six characteristics: (1) demographics (e.g. age, province of residence); (2) MS status; (3) health status; (4) presence of an informal caregiver; (5) health care costs; and (6) mortality (date of death). Each actor’s health profile was updated throughout the year, either at the occurrence of an event (e.g. birthday, date of diagnosis of MS) or at the change of the calendar year, depending on the profile characteristic. All characteristics were calculated and modelled for people with and without MSFootnote 20 (data sources available from authors upon request).
Figure 1 shows life-course parameters used in the simulation model.
Overview of the POHEM-Neurological model implementation
Text Equivalent - Figure 1
Figure 1 - Overview of the POHEM-Neurological model implementation
Figure 1 shows life-course parameters used in the simulation model. The model uses status quo assumptions to project the future impact. It assumes that MS incidence and risk and prognostic factors will remain stable throughout the projection period, consistent with findings in Nova Scotia and Manitoba.
MS status: incidence
Since the model uses status quo assumptions to project the future impact, it assumes that MS incidence and risk and prognostic factors will remain stable throughout the projection period, consistent with findings in Nova ScotiaFootnote 21 and ManitobaFootnote 22. We generated prevalent MS actors in two steps. First, we applied empirical estimates of sex- and age-specific MS incidence rates to the model’s synthetic Canadian population for each year, both historical and projected. We estimated incidence rates using a validated case definition algorithmFootnote ± that had a sensitivity of 84.0% for adults aged 20 years and olderFootnote 23, and specificity of 99.9%Footnote 24 applied to a cohort from the province of Ontario. Individuals under age 20 years were excluded, given the low incidence of acquired demyelinating syndromes (ADS) leading to MS in Canadian children and adolescents. Incidence and prevalence rates estimated from the British Columbia (BC) population were of comparable magnitude to those of the published studies from Canadian settings and provincial/territorial pilotsFootnote 22,Footnote 23,Footnote 24,Footnote 25.
Using these age - and sex-specific incidence rates, actors were classified as being diagnosed with MS, based on each actor’s risk of developing MS at the beginning of each new calendar year. Incident MS cases accumulated over time to generate prevalent cases of MS.
Second, we applied MS-specific mortality risk to actors with MS. The MS mortality risk was a product of a mortality ratio for people with MS multiplied by the baseline mortality rate for the Canadian population within POHEM-Neurological. The general population mortality rate gradually decreases over time, reflecting the projected mortality (life expectancy) using birth cohorts and the Lee-Carter model as estimated by Statistics CanadaFootnote 26. This means that the projected mortality for people with MS decreased at the same rate as for Canadians living without MS, largely consistent with observations in British ColumbiaFootnote 27. Using the BC administrative data prevalence cohort, we examined the number of deaths among individuals with MS, and compared it to the death rate among individuals without a neurological condition.
HUI3 is a utility-based measure that reflects health states ranging from perfect health (HUI3 = 1.0) through death (HUI3 = 0), including states considered to be worse than death (minimum HUI3 = –0.36), allowing for a range of severity levelsFootnote 17. The HUI3 assesses functional health across eight dimensions–cognition, emotion, mobility, dexterity, pain and discomfort, speech, vision and hearing–and was used based on the need for a common framework to assess functional health and disability due to MS. It validly measures and predicts functional health status and quality of life in people with MSFootnote 17,Footnote 28,Footnote 29. Age-specific HUI3 means for people with MS were estimated from the 2011 Survey on Living with Neurological Conditions in Canada (SLNCC)Footnote 30, while HUI3 values for people without MS were derived from all cycles (1994–2010) of the National Population Health Survey (NPHS)Footnote 31.
The impact of MS can also be assessed by the years of life lost (YLL) due to the condition, that is, years lost due to premature death from a disease. To perform the YLL calculation, we first calculated the age of death for all actors with MS in each calendar year. Next, we estimated YLL for a scenario in which the mortality hazard for MS was the same as for actors without MS and recalculated the age of death: YLL was the difference in age of death between the two calculations. Health-adjusted life years lost (HYLL) indicates the years of life lost living in a healthy state, combining morbidity and mortality experience, and was estimated from the product of years of life lived (age of death) multiplied by the annual HUI3 for each actor over their lifetime.
Informal caregiving refers to unpaid caregiving provided by family and friends to Canadians living with a chronic health condition, disability or aging needs. For each actor in the model, we assessed informal caregiving at the end of every calendar year based on an actor’s age, MS status and health status (HUI3). If an individual was assigned the presence of an informal caregiver, additional characteristics were also assigned based on empirical estimates from SLNCC and augmented with the 2012 General Social Survey (GSS)Footnote 32: (1) hours of care received; (2) health status of their caregiver; and (3) out-of-pocket expenses incurred by caregivers.
Health care costs
Formal health care costs were estimated among incident and prevalent cohorts with MS, and were ascertained using administrative data in British Columbia and Ontario. We estimated the health care costs using 2010-dollar value; as such, inflation is not factored into the costs projections. In addition, prevalent and counterfactual cohort costs were obtained for the period 01 April, 2009, through 31 March, 2010, in both Ontario and BC. We examined incident cohort costs in Ontario over the same period. We obtained available incident cohort costs in BC for the 12-month period starting on 01 April of the incident year (2006, 2007 or 2008).
Formal health care costs were those covered by provincial health plans in health components grouped as follows: (1) acute hospitalization; (2) physician services; (3) prescription drugs dataFootnote ‡; (4) rehabilitation hospitals; (5) Ontario provincially funded home care; (6) Ontario residence and care in a long-term care facility; and (7) Ontario provincially funded assistive devices. Also, per capita out-of-pocket caregiver costs and informal care by caregivers (hours of care per week) were estimated from a national sample of caregivers from the 2012 GSS, whereas per capita out-of-pocket costs to individuals living with neurological conditions were estimated from a national sample through the SLNCC. Out-of-pocket expenses were those expenses not covered by private insurance or provincial health care plans, such as the cost of prescription and over-the-counter medications, assistive devices, rehabilitation therapy such as physical or occupational therapy and home care services. We estimated formal health costs separately for incident cases (within the first 12 months following incidence) or prevalent case (one year or more since incidence) of MS. As out-of-pocket costs are not captured in administrative databases, we used survey data to assess those expenses.
Comorbidity, counterfactual population and costs estimation
Individuals living with MS frequently have comorbid conditionsFootnote 33,Footnote 34. Such conditions may be precursors to or related sequelae of MS, or may be present independent of MS. Individuals both with and without MS may experience some of these conditions. As such, it is sometimes difficult to isolate the contribution of MS to health care costs, caregiving or mortality, in the presence of comorbid conditions. To address this issue, we identified a counterfactual (nonneurological) population cohort to determine the net impact of MS. For example, if the prevalence of comorbidity X is greater among individuals with MS than without MS, then the additional health care costs (or receipt of caregiving hours) associated with this greater morbidity should be attributed to individuals living with MS. Conversely, if individuals with MS use less of a particular health care resource compared to individuals without a neurological condition, this lower utilization should also be reflected in our model.
The counterfactual nonneurological cohort consisted of all individuals in the respective datasets who had not otherwise been classified as having any of the seven neurological conditions of interest for the NPHSNC microsimulation project. In addition to MS, these conditions were Alzheimer’s disease and other dementias, cerebral palsy, epilepsy, Parkinson’s disease and parkinsonism, traumatic brain injuries and traumatic spinal cord injuries.
The model-projected prevalence of MS in 2010 was higher than that observed in the British Columbia data, and higher than that reported in some, but not all, Canadian provinces. Prevalence estimates across Canada are variable, with estimates per 100,000 population based on administrative data ranging from 207.3 in Ontario in 2010Footnote 24 to 266.9 in Nova Scotia in 2010Footnote 21, and as high as 357.6 in the contiguous province of Alberta in 2004Footnote 35. Despite this variance, the estimated age- and sex-specific prevalence rates are quite similar to estimates based on the 2010–11Footnote 36. Canadian Community Health Survey (CCHS; see Figure 2), recognizing that the CCHS did not capture those living in long-term care, who represent 5.8% to 9.2% of the MS population aged 65 years and olderFootnote 37. As such, we made no additional calibration to adjust POHEM-Neurological MS prevalence projections.
Prevalence rates of multiple sclerosis, by age and sex, projected from the POHEM-Neurological and estimates from other data sources, Canada, various dates
Abbreviations: CCHS, Canadian Community Health Survey; CI, confidence interval; MS, multiple sclerosis; POHEM, Population Health Model.
Text Equivalent - Figure 2
Figure 2 - Prevalence rates of multiple sclerosis, by age and sex, projected from the POHEM-Neurological and estimates from other data sources, Canada, various dates
Figure 2 shows that the model-projected prevalence of MS in 2010 was higher than that observed in the British Columbia data, and higher than that reported in some, but not all, Canadian provinces. Prevalence estimates across Canada are variable, with estimates per 100 000 population based on administrative data ranging from 207.3 in Ontario in 2010 to 266.9 in Nova Scotia in 2010, and as high as 357.6 in the contiguous province of Alberta in 2004. Despite this variance, the estimated age- and sex-specific prevalence rates are quite similar to estimates based on the 2010–2011 Canadian Community Health Survey (CCHS; see Figure 2), recognizing that the CCHS did not capture those living in long-term care, who represent 5.8% to 9.2% of the MS population aged 65 years and older. As such, we made no additional calibration to adjust POHEM-Neurological MS prevalence projections.
We projected 13 main model outputs through to 2031 including: (1) incident and prevalent MS cases in Canada; (2) YLL with MS; (3) HYLL; (4) health care costs, including costs for each of the seven sectors; (5) out-of-pocket expenses; and (6) hours of informal caregiving. In addition, we projected three parameters from the perspective of caregivers for MS: (1) hours of caregiving; (2) out-of-pocket expenses; and (3) health status (HUI3).
The number of incident MS cases is expected to rise slightly from 4,051 cases in 2011 to 4,794 cases per 100,000 population in 2031 (data not shown). Among Canadians aged 20 years and older, MS prevalence is projected to rise gradually from 380 per 100,000 population in 2011 to 430 per 100,000 population in 2031, corresponding to 98,835 Canadians living with MS in 2011 and 133,635 Canadians living with MS in 2031 (Figure 3). The small increase in prevalence over the 20-year horizon reflects the assumption of stable MS incidence and mortality.
POHEM-Neurological projected multiple sclerosis prevalence count (person years) and rate, population aged 20 years and older, both sexes, Canada, 2011–2031
Text Equivalent - Figure 3
Figure 3 - POHEM-Neurological projected multiple sclerosis prevalence count(person years) and rate, population aged 20 years and older, both sexes, Canada, 2011–2031
Figure 3 demonstrates that the number of incident MS cases is expected to rise slightly from 4051 cases in 2011 to 4794 cases per 100 000 population in 2031 (data not shown). Among Canadians aged 20 years and older, MS prevalence is projected to rise gradually from 380 per 100 000 population in 2011 to 430 per 100 000 population in 2031, corresponding to 98 835 Canadians living with MS in 2011 and 133 635 Canadians living with MS in 2031. The small increase in prevalence over the 20-year horizon reflects the assumption of stable MS incidence and mortality.
The MS prevalence for women aged 20 years and older is approximately 3 times higher than that for men (Figure 4). In 2011, the prevalence per 100,000 population was 580 for women compared to 200 for men. In 2031, the model projected a rate of 620 per 100,000 population for women compared to 220 per 100,000 for men. The prevalence of MS increases dramatically for both sexes from ages 20 to 24 years until the age group 60 to 69, after which the prevalence begins to decline, reflecting the fact that incidence is highest for individuals in their late thirties through their early sixties.
POHEM-Neurological projected multiple sclerosis prevalence count (person years) and rate, by age and sex, Canada, 2011 and 2031
Text Equivalent - Figure 4
Figure 4 - POHEM-Neurological projected multiple sclerosis prevalence count(person years) and rate, by age and sex, Canada, 2011 and 2031
Figure 4 shows that the MS prevalence for women aged 20 years and older is approximately 3 times higher than that for men. In 2011, the prevalence per 100 000 population was 580 for women compared to 200 for men. In 2031, the model projected a rate of 620 per 100 000 population for women compared to 220 per 100 000 for men. The prevalence of MS increases dramatically for both sexes from ages 20 to 24 years until the age group 60 to 69, after which the prevalence begins to decline, reflecting the fact that incidence is highest for individuals in their late thirties through their early sixties.
Regarding functional health and disability due to MS, the SLNCC showed that people of both sexes with MS have lower HUI3 scores compared to people with no neurological condition (Figure 5). Although HUI3 scores declined with age in both populations, on average, the HUI3 declined 15 years earlier in the MS population, and the gap in HUI3 scores persisted across all age groups. These trends were projected to remain the same throughout the projection period, as the model assumes no change in age-specific HUI3 (for those with MS or with no neurological condition).
Average Health Utilities Index Mark 3 score, population with multiple sclerosis and those with no neurological condition, by age, both sexes, Canada
Text Equivalent - Figure 5
Figure 5 - Average Health Utilities Index Mark 3 score, population with multiple sclerosis and those with no neurological condition, by age, both sexes, Canada
In figure 5, regarding functional health and disability due to MS, we see that the SLNCC showed that people of both sexes with MS have lower HUI3 scores compared to people with no neurological condition. Although HUI3 scores declined with age in both populations, on average, the HUI3 declined 15 years earlier in the MS population, and the gap in HUI3 scores persisted across all age groups. These trends were projected to remain the same throughout the projection period, as the model assumes no change in age-specific HUI3 (for those with MS or with no neurological condition).
Although people with MS born in more recent decades can expect to live longer than those born in earlier decades, they will not live as long as those without MS. Women with MS born between 2010 and 2019 will live five fewer years than women without MS, while men with MS born in the same decade will live four fewer years than men without MS. People living with MS will experience longer periods of living in poor health relative to their counterparts who do not have MS (Table 2). For instance, females diagnosed with MS born between 2010 and 2019 are projected to lose an average of 19.8 years in full health compared to 12.4 years for their counterparts who do not have MS. Similarly, males with MS born in the same decade are projected to lose 17.2 years in full health compared to 10.7 years for those who have not been diagnosed with MS.
|Decade of birth||Individuals with MS (YL)||Individuals without MS (YL)||HALY for individuals with MS||HALY for individuals without MS|
Abbreviations: HALY, health-adjusted life years; MS, multiple sclerosis; POHEM, Population Health Model; YL, years lived.
Table 3 provides a snapshot of the observed 2011 per capita health care costs for Canadians with MS and those without MS. At all ages, the mean total health care costs were substantially higher for those with MS than without MS. For instance, in the 20 to 24 age group, the projected total health care costs are about 13 times higher forthose with MS than for those without MS. The health care costs attributed to living with MS remain consistently 5- to 10-fold higher from ages 25 to 64 years, then drop to four times higher and remain stable for the rest of the age categories. When health care costs are subdivided, physician, hospital and prescription drug costs are consistently higher in the MS population than in the non-MS population (Table 3). However, the disparity between populations is greatest for drug costs, which are over 40-fold higher in the MS population aged 20 to 24 years than in the non-MS population.
|Age group||With MS ($)||Without MS ($)||Ratio of MS to non-MS cost by age group|
|Health care sectorFootnote a||Physician||Hospital||Prescription drugs||Health care sectorFootnote a||Physician||Hospital||Prescription drugs||Health care sectorFootnote a||Physician||Hospital||Prescription drugs|
Abbreviation: MS, multiple sclerosis.
The additional expenditures incurred by Canadians aged 20 years and older with MS are about three to eight times higher in the three main components (physician, hospital and drugs) than the expenditures incurred in the absence of seven major neurological conditions mentioned above. The additional costs incurred by those with MS are consistently higher among people aged 25 to 49 years but thereafter begin to stabilize and then decrease (Table 4). By age 70 years, the gap between the base and additional expenditures decreases to three-fold and remains at that level for the age groups 70 years and above, likely reflecting accrual of morbidity in the general population.
|Total costs ($ millions)|
Abbreviations: MS, multiple sclerosis; POHEM, Population Health Model.
Note: Base costs are those equal to the mean per capita costs among individuals without neurological conditions, if applied to individuals with MS. Additional costs represent the difference in costs for individuals with MS compared to base costs.
The total projected health care sector costs show that the additional expenditures due to MS are about four times higher than the base expenditures associated with the condition. As well, these costs are projected to increase over the projection period. Additional expenditures incurred for drugs for the population with MS are about 10 to 20 times higher than for Canadians living without any of the seven major neurological conditions noted earlier. The trend is prominent between the ages of 20 and 49 years and persists throughout the 20-year projection period.
The total out-of-pocket expenses incurred by Canadians with MS are projected to increase from $126 million in 2011 to $170 million in 2031 (Table 5). Out-of-pocket costs start to rise around age 25 until age 54 years, when the costs begin to stabilize, and then begin to decrease after age 65 years; the decrease in the per capita cost may be partly due to mortality. The average out-of-pocket expenditure for people with MS is around $1,300 annually throughout the projection period.
|Total costs ($ millions)|
The utilization of informal caregiving also reflects an additional burden on family and others associated with people living with MS. Based on 2011 data the proportion of Canadians receiving informal care is higher among those with MS than those with no neurological conditions across all age groups. It is estimated that 34% of those aged 20 to 24 years with MS have an informal caregiver, rising to 59% for those with MS aged 60 to 64 years (see Figure 6). In general, the burden for informal caregiving on people with MS emerges earlier and remains high throughout their lifetime.
POHEM-Neurological projected proportion of individuals with an informal caregiver, individuals with MS and those without a neurological condition, by age group, Canada, 2011
Text Equivalent - Figure 6
Figure 6 - POHEM-Neurological projected proportion of individuals with an informal caregiver, individuals with MS and those without a neurological condition, by age group, Canada, 2011
We can see in figure 6 the utilization of informal caregiving also reflects an additional burden on family and others associated with people living with MS. Based on 2011 data the proportion of Canadians receiving informal care is higher among those with MS than those with no neurological conditions across all age groups. It is estimated that 34% of those aged 20 to 24 years with MS have an informal caregiver, rising to 59% for those with MS aged 60 to 64 years. In general, the burden for informal caregiving on people with MS emerges earlier and remains high throughout their lifetime.
We used the POHEM-Neurological microsimulation model with status quo assumptions to project the changing nature of MS in Canada with respect to the incidence of new cases, rising prevalence and future burden, in terms of costs and impact on health over the next 20 years. By 2031, the prevalence of MS will exceed 400 persons per 100,000, corresponding to more than 133,000 affected Canadians, and a 13% change from 2011. After accounting for additional expenditures due to MS, total health sector costs for MS are expected to reach $2 billion by 2031. Further, 65% of people living with MS are projected to need informal care by 2031.
We found that people living with MS have a reduced life expectancy, and have longer periods of living with a poorer health-related quality of life (as reflected by lower scores on the HUI3), which limits their ability to participate in activities of daily living. Other studies have also shown that the MS population has lower quality of life than the general populationFootnote 38. The HUI3 is strongly associated with physician-scored measures of disabilityFootnote 39, which tend to worsen with older ageFootnote 40, consistent with our findings. Temporal trends in these associations have not been evaluated; thus, an assumption of stability in these trends across time was reasonable. As MS typically presents in young adults between the ages of 18 and 40 years, early disability and premature death mean that affected individuals have a reduced potential to contribute to economic activities.
Consistent with the existing literature, model outputs indicate that per capita health care expenditures are higher for individuals with MSFootnote 41 than those in the non-MS population. Although the rate of hospitalization has declined in the MS population over time, rates remain higher than in an age- and sex-matched population without MSFootnote 42. Other health care services are also used more heavily by the MS population than the general population.38 Prescription drug expenditures are particularly high, likely reflecting the very high costs of disease-modifying therapies for MSFootnote 43. We observed that among those aged 20 to 34 years, the group most likely to be using disease-modifying therapies, prescription drug expenditures constituted 62.5% to 69% of total health care expenditures. In a survey of 1909 Americans with MS in 2006, disease-modifying therapies constituted the single biggest MS-related costFootnote 44, and in a US-based study that used administrative data, pharmacy expenditures constituted 65% of total MS-related health care costs in 2004Footnote 45.
Although the microsimulation model projected only a slight increase in the prevalence of MS over the next 20 years, the burden of MS on affected individuals, the health system and society is projected to increase substantially. This increase reflects the improving life expectancy for people MS, with long periods lived in poor health and with functional disability. Formal health care costs will increase, and persons with MS will incur substantial out-of-pocket costs, which are expected to increase over the 20-year horizon. The demand for informal caregiving will also increase, further affecting the health and economic well-being of informal caregiversFootnote 46,Footnote 47,Footnote 48.
Strengths and limitations
Our study projections fill gaps in current pan-Canadian population-based estimates, and are also consistent with the existing Canadian literature.
POHEM-Neurological used status quo assumptions related to incidence, relative mortality and functional health. With the exception of risks associated with age and sex,Canada’s population growth, migration patterns and aging patterns are assumed to remain the same over the 20-year projection time horizon. Other risk factors were not considered because it was unclear which risk factors were most salient, and because they were likely to vary over the projection period. The future trend in terms of a cure for MS is assumed to remain unchanged over the projection period, although advances in health care could provide alternative ways to prevent, diagnose or treat MS. POHEM-Neurological presumes that incident cases of MS begin to occur at age 20, but up to 5% of individuals have symptom onset under age 16 yearsFootnote 49, although some of these individuals will not be diagnosed until adulthood. The effects of this assumption are likely to be small, given that most MS cases are diagnosed at age 20 years and older. The model shows peak incidence occurring at a later age than other Canadian studies undertaken in Nova ScotiaFootnote 21 and ManitobaFootnote 22; however, the overall incidence rates produced by the model were similar to these earlier studies.
Other limitations should be considered. The model projected a conservative increase in the prevalence of MS of 6.5% per decade. In all Canadian provinces where it has been evaluated over time, the prevalence of MS has increasedFootnote 21,Footnote 22,Footnote 23,Footnote 24,Footnote 36, consistent with our findings. However, the degree of change has varied, from 13.5% per decade in ManitobaFootnote 22 to 55% per decade in OntarioFootnote 24. That variance could be a reflection of the application of diagnostic or reporting criteria, or, our findings may underestimate the future impact of MS.
Our findings also assume that there will be no major treatment advances that can improve function or reduce mortality, and that the general patterns of health services utilization will persist in the future (i.e. status quo assumptions). Future iterations of the POHEM-Neurological could address the limitations posed by such assumptions by incorporating additional primary research on risk- and prognosis-factor dynamics in MS.
Microsimulation itself has certain limitations, including susceptibility to the quality of data used as input parameters, and the ability to model and quantify uncertainty of projectionsFootnote 50. With respect to input data quality, while attempts are made to ensure that the most appropriate data are used in the model, newer data that are more accurate will become available in the future. Such information can be updated in a microsimulation model in the future, and the impact of such changes can be assessed. Regarding the projection uncertainty, methodologies intended to improve projection accuracy are currently under development that could be applied in future scenario projectionsFootnote 51,Footnote 52.
POHEM-Neurological has shed light on the escalating costs of MS and its social, economic and health impacts. People living with MS face progressive physical and cognitive impairment and reduced quality of life. A key policy issue is the cost of MS and how best to mitigate the cost to society, as health care costs are projected to persistently increase, particularly for prescription drugs. Future microsimulation studies can be tailored to provide the evidence needed by policy makers to support the allocation of limited health care dollars. For instance, POHEM-Neurological could provide evidence to support cost-benefit analyses of various policy recommendations aimed at reducing the societal impacts of the condition.
This study was supported by the Institute for Clinical Evaluative Sciences (ICES), which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). The opinions, results and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred.
Parts of this material are based on data and information compiled and provided by CIHI. However, the analyses, conclusions, opinions and statements expressed herein are those of the authors, and not necessarily those of CIHI.
Dr. Karen Tu is a research scholar in the Department of Family and Community Medicine at the University of Toronto.
Conflicts of interest
The authors disclose no conflict of interest.
NA, RM, CB and RG contributed to the paper concept, drafting, analysis interpretation and critical review of the article. RM provided specialised content expertise on MS, while CB, RG, DGM, RW, PF, JB, KT and KR contributed to data acquisition, microsimulation modelling and review of the article.
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