Health care use in response to health shocks: Does socio‐economic status matter?

2021 ◽  
Author(s):  
Denzil G. Fiebig ◽  
Kees Gool ◽  
Jane Hall ◽  
Chunzhou Mu
Keyword(s):  
Health Care ◽  
Economic Status ◽  
Health Care Use ◽  
Health Shocks ◽  
Socio Economic Status

National female literacy, individual socio-economic status, and maternal health care use in sub-Saharan Africa

2010 ◽  
Vol 71 (11) ◽  
pp. 1958-1963 ◽  
Author(s):  
Sarah McTavish ◽  
Spencer Moore ◽  
Sam Harper ◽  
John Lynch
Keyword(s):  
Health Care ◽  
Maternal Health ◽  
Economic Status ◽  
Maternal Health Care ◽  
Health Care Use ◽  
Sub Saharan Africa ◽  
Socio Economic Status ◽  
Sub Saharan ◽  
Female Literacy

scholarly journals Defining ‘actionable’ high- costhealth care use: results using the Canadian Institute for Health Information population grouping methodology

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Maureen Anderson ◽  
Crawford W. Revie ◽  
Henrik Stryhn ◽  
Cordell Neudorf ◽  
Yvonne Rosehart ◽  
...  
Keyword(s):  
Mental Health ◽  
Health Care ◽  
Health Information ◽  
Economic Status ◽  
Health Care Use ◽  
Care Utilization ◽  
Health Care Spending ◽  
Health Profile ◽  
Socio Economic Status ◽  
Canadian Institute

Abstract Background A small proportion of the population consumes the majority of health care resources. High-cost health care users are a heterogeneous group. We aim to segment a provincial population into relevant homogenous sub-groups to provide actionable information on risk factors associated with high-cost health care use within sub-populations. Methods The Canadian Institute for Health Information (CIHI) Population Grouping methodology was used to define mutually exclusive and clinically relevant health profile sub-groups. High-cost users (> = 90th percentile of health care spending) were defined within each sub-group. Univariate analyses explored demographic, socio-economic status, health status and health care utilization variables associated with high-cost use. Multivariable logistic regression models were constructed for the costliest health profile groups. Results From 2015 to 2017, 1,175,147 individuals were identified for study. High-cost users consumed 41% of total health care resources. Average annual health care spending for individuals not high-cost were $642; high-cost users were $16,316. The costliest health profile groups were ‘long-term care’, ‘palliative’, ‘major acute’, ‘major chronic’, ‘major cancer’, ‘major newborn’, ‘major mental health’ and ‘moderate chronic’. Both ‘major acute’ and ‘major cancer’ health profile groups were largely explained by measures of health care utilization and multi-morbidity. In the remaining costliest health profile groups modelled, ‘major chronic’, ‘moderate chronic’, ‘major newborn’ and ‘other mental health’, a measure of socio-economic status, low neighbourhood income, was statistically significantly associated with high-cost use. Interpretation Model results point to specific, actionable information within clinically meaningful subgroups to reduce high-cost health care use. Health equity, specifically low socio-economic status, was statistically significantly associated with high-cost use in the majority of health profile sub-groups. Population segmentation methods, and more specifically, the CIHI Population Grouping Methodology, provide specificity to high-cost health care use; informing interventions aimed at reducing health care costs and improving population health.

scholarly journals Mortality amenable to health care and its relation to socio-economic status in Hungary, 2004–08

2011 ◽  
Vol 22 (5) ◽  
pp. 620-624 ◽  
Author(s):  
Csilla Nagy ◽  
Attila Juhász ◽  
Linda Beale ◽  
Anna Páldy
Keyword(s):  
Health Care ◽  
Economic Status ◽  
Socio Economic Status

scholarly journals Inequities in curative health-care utilization among the adult population (20–59 years) in India: A comparative analysis of NSS 71st (2014) and 75th (2017–18) rounds

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241994
Author(s):  
Shreya Banerjee ◽  
Indrani Roy Chowdhury
Keyword(s):  
Health Care ◽  
Health Care Utilization ◽  
Economic Status ◽  
Adult Population ◽  
Supply And Demand ◽  
Strong Association ◽  
Sample Survey ◽  
Necessary Condition ◽  
Care Utilization ◽  
Socio Economic Status

Objective The study attempts (a) to compute the degree of socio-economic inequity in health care utilization and (b) to decompose and analyze the drivers of socio-economic inequity in health care utilization among adults (20–59 years) in India during the periods 2014 and 2017–18. Data source The analysis has been done by using the unit level data of Social Consumption: Health (Schedule number 25.0), of National sample Survey (NSS), corresponding to the 71st and 75th rounds. Methods Odds ratios were computed through logistic regression analysis to examine the effect of the socio-economic status on the health seeking behaviour of the ailing adult population in India. Concentration Indices (CIs) were calculated to quantify the magnitude of socio-economic inequity in health care utilization. Further, the CIs were decomposed to find out the share of the major contributory factors in the overall inequity. Results The regression results revealed that socio-economic status continues to show a strong association with treatment seeking behavior among the adults in India. The positive estimates of CIs across both the rounds of NSS suggested that health care utilization among the adults continues to be concentrated within the higher socio-economic status, although the magnitude of inequity in health care utilization has shrunk from 0.0336 in 2014 to 0.0230 in 2017–18. However, the relative contribution of poor economic status to the overall explained inequities in health care utilisation observed a rise in its share from 31% in 2014 to 45% in 2017–18. Conclusion To reduce inequities in health care utilization, policies should address issues related to both supply and demand sides. Revamping the public health infrastructure is the foremost necessary condition from the supply side to ensure equitable health care access to the poor. Therefore, it is warranted that India ramps up investments and raises the budgetary allocation in the health care infrastructure and human resources, much beyond the current spending of 1.28% of its GDP as public expenditure on health. Further, to reduce the existing socio-economic inequities from the demand side, there is an urgent need to strengthen the redistributive mechanisms by tightening the various social security networks through efficient targeting and broadening the outreach capacity to the vulnerable and marginalized sections of the population.

Sind vor dem Virus alle gleich? Gerechte Gesundheitsversorgung in der Krise

2021 ◽  
Vol 70 (7-8) ◽  
pp. 437-453
Author(s):  
Kristina Woock ◽  
Susanne Busch
Keyword(s):  
Health Care ◽  
Health Services ◽  
Health Care System ◽  
Economic Status ◽  
Risk Of Infection ◽  
Current Crisis ◽  
Socio Economic Status ◽  
Distribution Of Resources ◽  
Intergenerational Fairness ◽  
Care System

Im Rahmen der COVID-19-Pandemie wird die Frage nach einer gerechten Gesundheitsversorgung anhand verschiedener Interventionsebenen diskutiert. Menschen mit niedrigem sozioökonomischem Status weisen aufgrund ihrer höheren Exposition zum Virus ein höheres Infektionsrisiko auf. Intergenerationale Gerechtigkeit, beispielsweise im Kontext der Impfpriorisierung, ist ebenfalls in der Diskussion. Menschen, die nicht an COVID-19 erkrankt sind, nehmen Gesundheitsleistungen seltener in Anspruch. Um eine gerechtere Gesundheitsversorgung zu gewährleisten wird vorgeschlagen, dass eine sozial gerechte Grundstruktur nicht die gleichmäßige Verteilung von Ressourcen bedeutet, sondern dass eine gleiche Ausgangslage für alle den Ausschlag für mehr Gerechtigkeit in der Krise gibt. Abstract: Is the Virus a Respecter of Persons? Fair Provision of Health-Services in the Current Crisis. In the context of the COVID-19 pandemic the issue of a fair provision of health-services is being raised on different layers of intervention. People with a low socio-economic status face a higher risk of infection because of increased exposure to the virus. Intergenerational fairness is under discussion, for instance in the context of the prioritization of inoculation. People that suffer from other diseases than COVID-19 take less advantage of the health-care system. For ensuring a more suitable distribution of resources it is being suggested that not equality in the distribution of resources but equity in initial positions will ensure more justness in a crisis.

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