1,720,965 research outputs found
Inequalities in the geographical distribution and workload of obstetrics and gynaecology specialists by gender in Turkey
No full textBackground: Women often have a preference for female obstetrics and gynaecology specialists (ob/gyns). Following the policy allowing physician selection by patients in Turkey, distribution of ob/gyns by gender across provinces has been an important indicator of access to healthcare. Aims: To analyse ob/gyns distribution by gender across provinces in Turkey, with emphasis on the relationship with conservativeness of the province and resulting physician workload. Methods: We measured the number of male and female ob/gyns by province in 2016 and the number of outpatient visits and deliveries performed by male and female ob/gyns in 2015. Pearson and Spearman correlation of the female ratio with votes for conservative parties was used to assess the distribution of ob/gyns. We then analysed the correlation with resulting workload of female ob/gyns and ran linear regressions of these variables controlling the number of ob/gyns in a province. Results: More conservative provinces, measured by the vote share for conservative political parties, have a higher ratio of female ob/gyns. Linear regression showed that a 1 percentage point (pp) increase in the vote share corresponded to a 0.69 pp increase in female ratio. For workload, a 1 pp higher female ratio resulted in a decrease in workload, measured as outpatient visits per female ob/gyn divided by that per male ob/gyn, by 0.014. Conclusion: Conservative provinces have more female ob/gyns, but other provinces compensate for that with higher female ob/gyn workload. High workload may have adverse health effects and result in lower quality of care.Publisher versio
Strangers in a New Land: Evaluating the Diagnostic Effectiveness of the Turkish Health System in the Context of Syrian Refugees
No full textThe study investigates the correlates of underdiagnosis and misdiagnosis in the Turkish health system between 2012 and 2016. It finds doctor time use intensity, university level patient load, and lack of technology all positively correlate with probability of underdiagnosis
Relating Dynamic Test Capacity, Digital Tracking of Countries and COVID-19 Performance: A Cross-Country Study
No full textThe
coronavirus pandemic (COVID-19) has killed more than a million people in the
world since its emergence in late 2019. There have been significant differences
in public policies, particularly policies to diagnose COVID-19, between
countries. Until vaccines are made available across countries, there were a few
preventive policies for understanding the routes and timings of the pandemic
transmission; contact tracing, quarantine, and physical distancing. In this
paper, we examine the sources of strength and health resilience that explain
the differences in COVID-19 performance between countries, in the last 2 years.
The health control mechanism is driven by stringency and testing capacities,
which can only be evaluated by digital
means and databases, and the health treatment abilities, which are
encapsulated in its trained set of health professionals, and health education
of its population.
The idea that the
paper puts forward is that in terms of testing capacity, the two characteristics
that are needed is 1-the fastest transmission from highest to lowest positivity
rate (identification-containment-isolation) and 2-identifying growing clusters.
The measure we capture this is looking at the range of maximum to minimum
positivity, and also the speed of spreading/surveying in the testing capacity
after it has reached the minimum positivity/maximum positivity, which gives us
a measure of how effectively the testing system is used in order for the disease
to stay under the limits of the health system. The ability to create a short
range means that the testing system is created in a utilitarian way, used to
identify the growing epidemic, and controlling the level of the growth
Transforming Health in Turkey An Evaluation of Two Decades of Reform
No full textThe study investigates the correlates of underdiagnosis and misdiagnosis in the Turkish health system between 2012 and 2016. It finds doctor time use intensity, university level patient load, and lack of technology all positively correlate with probability of underdiagnosis.</p
The Health Resilience and Welfare Inequality of the Turkish Population in Response to the Syrian Refugee Inflow
No full textRelating dynamic test capacity, digital tracking of countries and COVID-19 Performance: A cross-country study
No full textN/
Understanding household healthcare expenditure can promote health policy reform
No full textStudies of health care expenditure often exclude explanatory variables measuring wealth, despite the intuitive importance and policy relevance. We use the Household, Income and Labour Dynamics in Australia Survey to assess impacts of income and wealth on health expenditure. We investigate four different dependent variables related to health expenditure and use three main methodological approaches. These approaches include a first difference model and introduction of a lagged dependent variable into a cross-sectional context. The key findings include that wealth tends to be more important than income in identifying variation in health expenditure. This applies for health variables which are not directly linked to means testing, such as spending on health practitioners and for being unable to afford required medical treatment. In contrast, the paper includes no evidence of different impacts of income and wealth on spending on medicines, prescriptions or pharmaceuticals. The results motivate two novel policy innovations. One is the introduction of an asset test for determining rebate eligibility for private health insurance. The second is greater focus on asset testing, rather than income tests, for a wide range of general welfare payments that can be used for health expenditure. Australia's world-leading use of means testing can provide a test case for many countries.Publisher versio
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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