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      Financial barriers and adverse clinical outcomes among patients with cardiovascular-related chronic diseases: a cohort study

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          Abstract

          Background

          Some patients with cardiovascular-related chronic diseases such as diabetes and heart disease report financial barriers to achieving optimal health. Previous surveys report that the perception of having a financial barrier is associated with self-reported adverse clinical outcomes. We sought to confirm these findings using linked survey and administrative data to determine, among patients with cardiovascular-related chronic diseases, if there is an association between perceived financial barriers and the outcomes of: (1) disease-related hospitalizations, (2) all-cause mortality and (3) inpatient healthcare costs.

          Methods

          We used ten cycles of the nationally representative Canadian Community Health Survey (administered between 2000 and 2011) to identify a cohort of adults aged 45 and older with hypertension, diabetes, heart disease or stroke. Perceived financial barriers to various aspects of chronic disease care and self-management were identified (including medications, healthful food and home care) from the survey questions, using similar questions to those used in previous studies. The cohort was linked to administrative data sources for outcome ascertainment (Discharge Abstract Database, Canadian Mortality Database, Patient Cost Estimator). We utilized Poisson regression techniques, adjusting for potential confounding variables (age, sex, education, multimorbidity, smoking status), to assess for associations between perceived financial barriers and disease-related hospitalization and all-cause mortality. We used gross costing methodology and a variety of modelling approaches to assess the impact of financial barriers on hospital costs.

          Results

          We identified a cohort of 120,752 individuals over the age of 45 years with one or more of the following: hypertension, diabetes, heart disease or stroke. One in ten experienced financial barriers to at least one aspect of their care, with the two most common being financial barriers to accessing medications and healthful food. Even after adjustment, those with at least one financial barrier had an increased rate of disease-related hospitalization and mortality compared to those without financial barriers with adjusted incidence rate ratios of 1.36 (95% CI: 1.29–1.44) and 1.24 (1.16–1.32), respectively. Furthermore, having a financial barrier to care was associated with 30% higher inpatient costs compared to those without financial barriers.

          Discussion

          This study, using novel linked national survey and administrative data, demonstrates that chronic disease patients with perceived financial barriers have worse outcomes and higher resource utilization, corroborating the findings from prior self-report studies. The overall exposure remained associated with the primary outcome even in spite of adjustment for income. This suggests that a patient’s perception of a financial barrier might be used in clinical and research settings as an additional measure along with standard measures of socioeconomic status (ie. income, education, social status).

          Conclusions

          After adjusting for relevant covariates, perceiving a financial barrier was associated with increased rates of hospitalization and mortality and higher hospital costs compared to those without financial barriers. The demonstrable association with adverse outcomes and increased costs seen in this study may provide an impetus for policymakers to seek to invest in interventions which minimize the impact of financial barriers.

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          Most cited references27

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          Full coverage for preventive medications after myocardial infarction.

          Adherence to medications that are prescribed after myocardial infarction is poor. Eliminating out-of-pocket costs may increase adherence and improve outcomes. We enrolled patients discharged after myocardial infarction and randomly assigned their insurance-plan sponsors to full prescription coverage (1494 plan sponsors with 2845 patients) or usual prescription coverage (1486 plan sponsors with 3010 patients) for all statins, beta-blockers, angiotensin-converting-enzyme inhibitors, or angiotensin-receptor blockers. The primary outcome was the first major vascular event or revascularization. Secondary outcomes were rates of medication adherence, total major vascular events or revascularization, the first major vascular event, and health expenditures. Rates of adherence ranged from 35.9 to 49.0% in the usual-coverage group and were 4 to 6 percentage points higher in the full-coverage group (P<0.001 for all comparisons). There was no significant between-group difference in the primary outcome (17.6 per 100 person-years in the full-coverage group vs. 18.8 in the usual-coverage group; hazard ratio, 0.93; 95% confidence interval [CI], 0.82 to 1.04; P=0.21). The rates of total major vascular events or revascularization were significantly reduced in the full-coverage group (21.5 vs. 23.3; hazard ratio, 0.89; 95% CI, 0.90 to 0.99; P=0.03), as was the rate of the first major vascular event (11.0 vs. 12.8; hazard ratio, 0.86; 95% CI, 0.74 to 0.99; P=0.03). The elimination of copayments did not increase total spending ($66,008 for the full-coverage group and $71,778 for the usual-coverage group; relative spending, 0.89; 95% CI, 0.50 to 1.56; P=0.68). Patient costs were reduced for drugs and other services (relative spending, 0.74; 95% CI, 0.68 to 0.80; P<0.001). The elimination of copayments for drugs prescribed after myocardial infarction did not significantly reduce rates of the trial's primary outcome. Enhanced prescription coverage improved medication adherence and rates of first major vascular events and decreased patient spending without increasing overall health costs. (Funded by Aetna and the Commonwealth Fund; MI FREEE ClinicalTrials.gov number, NCT00566774.).
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            The role of patient navigators in eliminating health disparities.

            Despite many important efforts to increase equity in the US health care system, not all Americans have equal access to health care-or similar health outcomes. With the goal of lowering costs and increasing accessibility to health care, the nation's new health care reform legislation includes certain provisions that expand health insurance coverage to uninsured and underinsured populations, promote medical homes, and support coordination of care. These provisions may help narrow existing health care disparities. Many of the most vulnerable patients, however, may continue to have difficulty accessing and navigating the complex US health care delivery system. This article explores the unique role that patient navigation can play in improving health outcomes for racial and ethnic minorities, as well as other underserved populations, in the context of a changing healthcare environment. Patient navigators can not only facilitate improved health care access and quality for underserved populations through advocacy and care coordination, but they can also address deep-rooted issues related to distrust in providers and the health system that often lead to avoidance of health problems and non-compliance with treatment recommendations. By addressing many of the disparities associated with language and cultural differences and barriers, patient navigators can foster trust and empowerment within the communities they serve. Specific patient navigator activities are discussed, and metrics to evaluate program efforts are presented. Copyright © 2011 American Cancer Society.
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              The effect of cost on adherence to prescription medications in Canada.

              Many patients do not adhere to treatment because they cannot afford their prescription medications, putting them at increased risk of adverse health outcomes. We determined the prevalence of cost-related nonadherence and investigated its associated characteristics, including whether a person has drug insurance. Using data from the 2007 Canada Community Health Survey, we analyzed the responses of 5732 people who answered questions about cost-related nonadherence to treatment. We determined the national prevalence of cost-related nonadherence and used logistic regression to evaluate the association between cost-related nonadherence and a series of demographic and socioeconomic variables, including province of residence, age, sex, household income, health status and having drug insurance. Cost-related nonadherence was reported by 9.6% (95% confidence interval [CI] 8.5%-10.6%) of Canadians who had received a prescription in the past year. In our adjusted model, we found that people in poor health (odds ratio [OR] 2.64, 95% CI 1.77-3.94), those with lower income (OR 3.29, 95% CI 2.03-5.33), those without drug insurance (OR 4.52, 95% CI 3.29-6.20) and those who live in British Columbia (OR 2.56, 95% CI 1.49-4.42) were more likely to report cost-related nonadherence. Predicted rates of cost-related nonadherence ranged from 3.6% (95% CI 2.4-4.5) among people with insurance and high household incomes to 35.6% (95% CI 26.1%-44.9%) among people with no insurance and low household incomes. About 1 in 10 Canadians who receive a prescription report cost-related nonadherence. The variability in insurance coverage for prescription medications appears to be a key reason behind this phenomenon.
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                Author and article information

                Contributors
                +1 (403) 620-5505 , dcampbel@ucalgary.ca
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                15 February 2017
                15 February 2017
                2017
                : 15
                : 33
                Affiliations
                [1 ]ISNI 0000 0004 1936 7697, GRID grid.22072.35, Department of Medicine, Cumming School of Medicine, , University of Calgary, Health Sciences Centre, ; Room G236, 3330 Hospital Dr NW, Calgary, AB T2N 4N1 Canada
                [2 ]ISNI 0000 0004 1936 7697, GRID grid.22072.35, Department of Community Health Sciences, Cumming School of Medicine, , University of Calgary, ; Calgary, AB Canada
                [3 ]ISNI 0000 0004 1936 7697, GRID grid.22072.35, O’Brien Institute for Public Health, , University of Calgary, ; Calgary, AB Canada
                [4 ]ISNI 0000 0004 1936 7697, GRID grid.22072.35, Libin Cardiovascular Institute of Alberta, , University of Calgary, ; Calgary, AB Canada
                [5 ]ISNI 0000 0004 1936 7697, GRID grid.22072.35, Faculty of Nursing, , University of Calgary, ; Calgary, AB Canada
                [6 ]ISNI 0000 0001 2097 5698, GRID grid.413850.b, , Health Analysis Division, Statistics Canada, ; Ottawa, ON Canada
                Article
                788
                10.1186/s12916-017-0788-6
                5309998
                28196524
                03d30643-718b-4766-8daf-4730baf17024
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 7 October 2016
                : 11 January 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000145, Alberta Innovates - Health Solutions;
                Funded by: FundRef http://dx.doi.org/10.13039/501100000155, Social Sciences and Humanities Research Council of Canada;
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Funded by: Canadian Foundation for Innovation
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Medicine
                Medicine

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