Longitudinal administrative data can be used to examine multimorbidity, provided false discoveries are controlled for

Wong, Albert; Boshuizen, Hendriek C.; Schellevis, François G.; Kommer, Geert Jan; Polder, J.J.

doi:10.1016/j.jclinepi.2010.12.011

Cited by 45 publications

(35 citation statements)

References 25 publications

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“…Our results show increases between 25.2% and 78.7% in an 11-year period for all provinces and territories studied with the exception of Nunavut; further investigation is needed to determine why these increases have occurred. Wong et al 33 cautioned that there is the opportunity for an increased number of false positive cases to accrue over time, which may contribute to inflated rates of increasing prevalence across study years. For Nunavut, the large increases in prevalence may reflect the fact that Nunavut officially became a territory in 1999 and therefore its administrative databases may not have had time to sufficiently capture prevalent cases by 2001/02.…”

Section: Health Promotion and Chronic Disease Prevention In Canadamentioning

confidence: 99%

Estimating multimorbidity prevalence with the Canadian Chronic Disease Surveillance System

Feely

Lix

Reimer

2017

Health Promot Chronic Dis Prev Can

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Introduction The Public Health Agency of Canada’s Canadian Chronic Disease Surveillance System (CCDSS) uses a validated, standardized methodology to estimate prevalence of individual chronic diseases, such as diabetes. Expansion of the CCDSS for surveillance of multimorbidity, the co-occurrence of two or more chronic diseases, could better inform health promotion and disease prevention. The objective of this study was to assess the feasibility of using the CCDSS to estimate multimorbidity prevalence. Methods We used administrative health data from seven provinces and three territories and five validated chronic conditions (i.e. cardiovascular disease, respiratory disease, mental illness, hypertension and diabetes) to estimate multimorbidity prevalence. We produced age-standardized (using Canada’s 1991 population) and age-specific estimates for two multimorbidity definitions: (1) two or more conditions, and (2) three or more conditions from the five validated conditions, by sex, fiscal year and geography. Results Among Canadians aged 40 years and over in the fiscal year 2011/12, the prevalence of two or more and three or more chronic conditions was 26.5% and 10.2%, respectively, which is comparable to other estimates based on administrative health data. The increase in multimorbidity prevalence with increasing age was similar across provinces. The difference in prevalence for males and females varied by province and territory. We observed substantial variation in estimates over time. Results were consistent for the two definitions of multimorbidity. Conclusion The CCDSS methodology can produce comparative estimates of multimorbidity prevalence across provinces and territories, but there are challenges in using it to estimate temporal trends. Further expansion of the CCDSS in the number and breadth of validated case definitions will improve the accuracy of multimorbidity surveillance for the Canadian population.

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Section: Health Promotion and Chronic Disease Prevention In Canadamentioning

confidence: 99%

Estimating multimorbidity prevalence with the Canadian Chronic Disease Surveillance System

Feely

Lix

Reimer

2017

Health Promot Chronic Dis Prev Can

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“…The first category comprises studies that differentiate the effect of mortality by underlying cause-of-death. For example, decedents from cancer and respiratory diseases have significantly higher end-oflife spending than decedents from heart disease, indicating that the precise effect of mortality depends on the specific health problem (Bird et al 2002;Seshamani and Gray 2004;Wong et al 2011a), and also on the coexistence of other health problems (e.g., Wong et al 2011b;Häkkinen et al 2008). Second, there are studies that use both mortality and general health indicators to explain health expenditures.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

The effect of population aging on health expenditure growth: a critical review

et al. 2013

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Although the consequences of population aging for growth in health expenditures have been widely investigated, research on this topic is rather fragmented. Therefore, these consequences are not fully understood. This paper reviews the consequences of population aging for health expenditure growth in Western countries by combining insights from epidemiological and health economics research. Based on a conceptual model of health care use, we first review evidence on the relationship between age and health expenditures to provide insight into the direct effect of aging on health expenditure growth. Second, we discuss the interaction between aging and the main societal drivers of health expenditures. Aging most likely influences growth in health expenditures indirectly, through its influence on these societal factors. The literature shows that the direct effect of aging depends strongly on underlying health and disability. Commonly used approximations of health, like age or mortality, insufficiently capture complex dynamics in health. Population aging moderately increases expenditures on acute care and strongly increases expenditures on long-term care. The evidence further shows that the most important driver of health expenditure growth, medical technology, interacts strongly with age and health, i.e., population aging reinforces the influence of medical technology on health expenditure growth and vice versa. We therefore conclude that population aging will remain in the centre of policy debate. Further research should focus on the changes in health that explain the effect of longevity gains on health expenditures, and on the interactions between aging and other societal factors driving expenditure growth.

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“…The knowledge retrieved from a study of evolution of multimorbidity has the potential to identify populations at high risk of developing multimorbidity as well as repartitioning CDs across this continuum. Few studies [13], [14], [15], [16] have examined multimorbidity from a longitudinal perspective. Those studies focused mostly on the impact of CDs on disability, functional decline and mortality [14] or its relationship with nutrition [16].…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the strength of association between CDs at a specific time point (e.g. observed over expected ratio) [17], a longitudinal follow-up design is rarely used in the context of multimorbidity and could help understand causality [15]. To the best of our knowledge, no study has used a longitudinal study design to investigate the evolution of multimorbidity.…”

Section: Introductionmentioning

confidence: 99%

Understanding the Evolution of Multimorbidity: Evidences from the North West Adelaide Health Longitudinal Study (NWAHS)

et al. 2014

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ObjectiveThe aim of this study is to describe the evolution of multimorbidity.Study Design and SettingData from 1854 South Australians who participated in the North West Adelaide longitudinal Health Study(NWAHS) was collected between baseline (2000–2002) and follow-up (2008–2010). Status for eight chronic diseases (CDs) was determined by biomedical measurement or self-report. Chronic disease (CD) mean age of occurrence and order of appearance was investigated.ResultsThe prevalence of multimorbidity increased from 32% to 64% during the 7.8±1.1 years of follow-up. The estimated mean age of onset of a new CD was significantly older for hypertension, cardiovascular disease (CVD) and chronic obstructive pulmonary disease (COPD) and younger for hypercholesterolemia, asthma and other mental problem. Hypercholesterolemia was more likely to develop as a first than as a subsequent CD (39%vs.16%, p<0.0001) while CVD (1%vs.5%, p<0.0001), diabetes (5%vs.11%, p<0.001) and COPD (6%vs.16%, p<0.0001) were less likely. The presence of mood disorders at baseline was associated with an increased risk of developing other mental disorders (36%vs.12%, p<0.0001), diabetes (18%vs.9%, p<0.01) and asthma (30%vs.21%, p<0.05).ConclusionLongitudinal data could be used to study the evolution of multimorbidity and could provide information on CDs mean age of occurrence, order of appearance and impact on the development of future CDs.

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Longitudinal administrative data can be used to examine multimorbidity, provided false discoveries are controlled for

Cited by 45 publications

References 25 publications

Estimating multimorbidity prevalence with the Canadian Chronic Disease Surveillance System

Estimating multimorbidity prevalence with the Canadian Chronic Disease Surveillance System

The effect of population aging on health expenditure growth: a critical review

Understanding the Evolution of Multimorbidity: Evidences from the North West Adelaide Health Longitudinal Study (NWAHS)

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