Inequities in access to healthcare: analysis of national survey data across six Asia-Pacific countries.

BMC Health Serv Res

Discipline of Public Health, Flinders University, Sturt Road, Bedford Park, South Australia 5042, Australia.

Published: July 2013

Background: Evidence suggests that there is a link between inequitable access to healthcare and inequitable distribution of illness. A recent World Health Organization report stated that there is a need for research and policy to address the critical role of health services in reducing inequities and preventing future inequities. The aim of this manuscript is to highlight disparities and differences in terms of the factors that distinguish between poor and good access to healthcare across six Asia-Pacific countries: Australia, Hong Kong, Japan, South Korea, Taiwan, and Thailand.

Methods: A population survey was undertaken in each country. This paper is a secondary analysis of these existing data. Data were collected in each country between 2009 and 2010. Four variables related to difficulties in access to healthcare (distance, appointment, waiting time, and cost) were analysed using binomial logistic regression to identify socio- and demographic predictors of inequity.

Results: Consistent across the findings, poor health and low income were identified as difficulties in access. Country specific indicators were also identified. For Thailand, the poorest level of access appears to be for respondents who work within the household whereas in Taiwan, part-time work is associated with difficulties in access. Within Hong Kong, results suggest that older (above 60) and retired individuals have the poorest access and within Australia, females and married individuals are the worst off.

Conclusion: Recognition of these inequities, from a policy perspective, is essential for health sector policy decision-making. Despite the differences in political and economic climate in the countries under analysis, our findings highlight patterns of inequity which require policy responses. Our data should be used as a means of deciding the most appropriate policy response for each country which includes, rather than excludes, socially marginalised population groups. These findings should be of interest to those involved in health policy, but also in policy more generally because as we have identified, access to health care is influenced by determinants outside of the health system.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3734194PMC
http://dx.doi.org/10.1186/1472-6963-13-238DOI Listing

Publication Analysis

Top Keywords

access healthcare
16
difficulties access
12
asia-pacific countries
8
access
8
hong kong
8
health
7
policy
7
inequities
4
inequities access
4
healthcare
4

Similar Publications

Background: Clinical practice guidelines (CPGs) are moving toward greater consideration of population-level differences, like health inequities, when creating management recommendations. CPGs have the potential to reduce or perpetuate health inequities. The intrinsic design factors of electronic interfaces that contain CPGs are known barriers to guideline use.

View Article and Find Full Text PDF

Background: Migrant female sex workers (MFSWs) can be exposed to various health risks due to their occupation, including mental and physical health, substance use, and experience of violence. However, they face substantial barriers to accessing healthcare services. The inadequate access to medical care for migrant female sex workers poses a challenge to the German healthcare system.

View Article and Find Full Text PDF

Background: Multimorbidity is a growing global concern, affecting patient outcomes and healthcare costs. In low- and middle-income countries, data on multimorbidity in primary care beyond prevalence is limited. Our study explored the demographic and clinical characteristics of multimorbidity among older people attending primary health care in Malawi.

View Article and Find Full Text PDF

Digital health interventions (DHIs), such as apps, websites and wearables, are being presented as solutions or enablers to manage the burden of cardiometabolic disease in healthcare. However, the potential benefits of DHIs may not be reaching the most in-need populations, who may face intersecting barriers to accessing health services and digital solutions. The Digital Interventions for South Asians in Cardiometabolic Disease (DISC) study used a mixed-method approach to focus on people of a South Asian background, a high-risk group for cardiometabolic disease.

View Article and Find Full Text PDF

Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!