The increasing burden and complexity of multimorbidity

Pefoyo, Anna J. Koné; Bronskill, Susan E.; Gruneir, Andrea; Calzavara, Andrew; Thavorn, Kednapa; Petrosyan, Yelena; Maxwell, Colleen J.; Bai, Yan; Wodchis, Walter P.

doi:10.1186/s12889-015-1733-2

Cited by 493 publications

(516 citation statements)

References 44 publications

(91 reference statements)

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“…Prevalence rates over time may also be influenced by the presence of individuals who have been incorrectly diagnosed with one or more chronic conditions. 6 Furthermore, provinces and territories that have only a single diagnosis code in physician billing claims may underestimate multimorbidity prevalence, as there is a decreased probability for multiple diagnosis codes to be captured in these data. 37 Finally, we should note that information about the severity of chronic conditions is not available in administrative data.…”

Section: Discussionmentioning

confidence: 99%

“…[2][3][4][5][6][7] Multimorbidity prevalence is expected to rise, in Canada as in other countries, due to an aging population and an increasing prevalence of such chronic diseases as diabetes and hypertension. 8 Multimorbidity is an important issue for health care providers and policy makers to monitor because it has been linked with potentially negative health outcomes, including decreased health-related quality of life 9 and increased health care utilization and costs.…”

Section: Introductionmentioning

confidence: 99%

“…However, no population-based studies have provided comparative estimates for all of Canada's provinces and territories. A few population-based studies have been conducted for individual provinces or territories, 6,13,14 but only one 6 of these has examined changes in multimorbidity over time, and none have examined variations across population subgroups. Given this background, the purpose of this study was to assess the feasibility of using the CCDSS to estimate multimorbidity prevalence across population groups defined by age, sex and geography, and over time.…”

Section: Introductionmentioning

confidence: 99%

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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: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimating multimorbidity prevalence with the Canadian Chronic Disease Surveillance System

Feely

Lix

Reimer

2017

Health Promot Chronic Dis Prev Can

View full text Add to dashboard Cite

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“…5,[7][8][9] Given the ubiquitous use of administrative data, however, multimorbidity has often been equated with multiple chronic conditions, especially when these conditions are identified from claims data. [10][11][12] In a previous study, 13 we argued that multimorbidity should be redefined to include the co-occurrence of chronic conditions, functional limitations, and geriatric syndromes. We demonstrated the strong cumulative effects of their co-occurrence on adverse health outcomes, including self-report of fair/poor health, self-rated worse health at 2 years, and 2-year mortality.…”

Section: Introductionmentioning

confidence: 99%

Combinations of Chronic Conditions, Functional Limitations, and Geriatric Syndromes that Predict Health Outcomes

et al. 2016

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BACKGROUND:The strategic framework on multiple chronic conditions released by the US Department of Health and Human Services calls for identifying homogeneous subgroups of older adults to effectively target interventions aimed at improving their health. OBJECTIVE: We aimed to identify combinations of chronic conditions, functional limitations, and geriatric syndromes that predict poor health outcomes. DESIGN, SETTING AND PARTICIPANTS Data from the 2010-2012 Health and Retirement Study provided a representative sample of U.S. adults 50 years of age or older (n=16,640). MAIN MEASURES: Outcomes were: Self-reported fair/poor health, self-rated worse health at 2 years, and 2-year mortality. The main independent variables included self-reported chronic conditions, functional limitations, and geriatric syndromes. We conducted tree-based classification and regression analysis to identify the most salient combinations of variables to predict outcomes. KEY RESULTS: Twenty-nine percent and 23 % of respondents reported fair/poor health and self-rated worse health at 2 years, respectively, and 5 % died in 2 years. The top combinations of conditions identified through our tree analysis for the three different outcome measures (and percent respondents with the outcome) were: a) for fair/poor health status: difficulty walking several blocks, depressive symptoms, and severe pain (> 80 %); b) for selfrated worse health at 2 years: 68.5 years of age or older, difficulty walking several blocks and being in fair/poor health (60 %); and c) for 2-year mortality: 80.5 years of age or older, and presenting with limitations in both ADLs and IADLs (> 40 %). CONCLUSIONS: Rather than chronic conditions, functional limitations and/or geriatric syndromes were the most prominent conditions in predicting health outcomes. These findings imply that accounting for chronic conditions alone may be less informative than also accounting for the co-occurrence of functional limitations and geriatric syndromes, as the latter conditions appear to drive health outcomes in older individuals.

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“…[6][7][8] The prevalence of patients living with multiple comorbidities is increasing as advances in medicine enable people to live and manage chronic diseases. [9][10][11] However, these medical gains have resulted in an increased burden on both patients and healthcare systems. Socioeconomic status and co-occurring psychosocial challenges further complicate health and healthcare in marginalized populations.…”

mentioning

confidence: 99%

The Lived Experience of the Hospital Discharge “Plan”: A Longitudinal Qualitative Study of Complex Patients

Carusone

O’Leary

McWatt

et al. 2017

Journal of Hospital Medicine

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BACKGROUND Transitions in care are a high‐risk time for patients. Complex patients account for the largest proportion of healthcare costs but experience lower quality and discontinuity of care. The experiences of complex patients can be used to identify gaps in hospital discharge practices and design interventions to improve outcomes. METHODS We used a case study approach with serial interviews and chart abstraction to explore the hospital discharge and transition experience over 6 weeks. Participants were recruited from a small hospital in Toronto that provides care to complex patients living with human immunodeficiency virus (HIV). Framework analysis was used to compare data across time‐points and sources. RESULTS Data were collected from 9 cases. Participants presented with complex medical and psychosocial challenges, including substance use (n = 9), mental health diagnoses (n = 8) and a mean of 5 medical comorbidities in addition to HIV. Data were analyzed and reported in 4 key themes: 1) social support; 2) discharge process and transition experience; 3) post‐discharge follow‐up; and 4) patient priorities. After hospital discharge, the complexity of participants' lives resulted in a change in priorities and subsequent divergence from the discharge plan. Despite the comprehensive discharge plans, with referrals designed to support their health and activities of daily living, participants experienced challenges with social support and referral uptake, resulting in a loss of stability achieved while in hospital. CONCLUSION Further investigation and changes in practice are necessary to ensure that discharge plans for complex patients are realistic within the context of their lives outside of the hospital.

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The increasing burden and complexity of multimorbidity

Cited by 493 publications

References 44 publications

Estimating multimorbidity prevalence with the Canadian Chronic Disease Surveillance System

Estimating multimorbidity prevalence with the Canadian Chronic Disease Surveillance System

Combinations of Chronic Conditions, Functional Limitations, and Geriatric Syndromes that Predict Health Outcomes

The Lived Experience of the Hospital Discharge “Plan”: A Longitudinal Qualitative Study of Complex Patients

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