Utilization of office-based physicians with different medical specialities by socioeconomic status in men and women.

<p>Utilization of office-based physicians with different medical specialities by socioeconomic status in men and women.</p

Utilization of office-based general practitioners by socioeconomic status in men and women.

<p>Utilization of office-based general practitioners by socioeconomic status in men and women.</p

Sociodemographic characteristics of the study population (n = 6754).

<p>Sociodemographic characteristics of the study population (n = 6754).</p

Occupational injuries within the past 12 months by occupational group (age 18–70), GEDA 2010, n = 14,041.

<p>Occupational injuries within the past 12 months by occupational group (age 18–70), GEDA 2010, n = 14,041.</p

Socioeconomic Status and Use of Outpatient Medical Care: The Case of Germany

<div><p>Background</p><p>Socially disadvantaged people have an increased need for medical care due to a higher burden of health problems and chronic diseases. In Germany, outpatient care is chiefly provided by office-based general practitioners and specialists in private practice. People are free to choose the physician they prefer. In this study, national data were used to examine differences in the use of outpatient medical care by socioeconomic status (SES).</p><p>Methods</p><p>The analyses were based on data from 6,754 participants in the Robert Koch Institute’s German Health Interview and Examination Survey for Adults (DEGS1) aged between 18 and 69 years. The number of outpatient physician visits during the past twelve months was assessed for several medical specializations. SES was determined based on education, occupation, and income. Associations between SES and physician visits were analysed using logistic regression and zero-truncated negative binomial regression for count data.</p><p>Results</p><p>After adjusting for sociodemographic factors and health indicators, outpatients with low SES had more contacts with general practitioners than outpatients with high SES (men: incidence rate ratio [IRR] = 1.25; 95% confidence interval [CI] = 1.08–1.46; women: IRR = 1.20; 95% CI = 1.07–1.34). The use of specialists was lower in people with low SES than in those with high SES when sociodemographic factors and health indicators were adjusted for (men: odds ratio [OR] = 0.68; 95% CI = 0.51–0.91; women: OR = 0.56; 95% CI = 0.41–0.77). This applied particularly to specialists in internal medicine, dermatology, and gynaecology. The associations remained after additional adjustment for the type of health insurance and the regional density of office-based physicians.</p><p>Conclusion</p><p>The findings suggest that socially disadvantaged people are seen by general practitioners more often than the socially better-off, who are more likely to visit a medical specialist. These differences may be due to differences in patient preferences, physician factors, physician-patient interaction, and potential barriers to accessing specialist care.</p></div

Occupational injuries within the past 12 months among the gainfully employed (age 18–70), GEDA 2010, n = 14,041.

<p>Occupational injuries within the past 12 months among the gainfully employed (age 18–70), GEDA 2010, n = 14,041.</p

Data sources, data availability and definitions—COVID-19 cases.

Data sources, data availability and definitions—COVID-19 cases.</p

Data collection template all cause deaths.

Where appropriate for a study protocol, the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER, http://gather-statement.org/) have been considered in the preparation of this article [45]. (XLSX)</p

BoCO-19 partner institutions.

IntroductionThe COVID-19 pandemic has had an extensive impact on public health worldwide. However, in many countries burden of disease indicators for COVID-19 have not yet been calculated or used for monitoring. The present study protocol describes an approach developed in the project “The Burden of Disease due to COVID-19. Towards a harmonization of population health metrics for the surveillance of dynamic outbreaks” (BoCO-19). The process of data collection and aggregation across 14 different countries and sub-national regions in Southern and Eastern Europe and Central Asia is described, as well as the methodological approaches used.Materials and methodsThe study implemented in BoCO-19 is a secondary data analysis, using information from national surveillance systems as part of mandatory reporting on notifiable diseases. A customized data collection template is used to gather aggregated data on population size as well as COVID-19 cases and deaths. Years of life lost (YLL), as one component of the number of Disability Adjusted Life Years (DALY), are calculated as described in a recently proposed COVID-19 disease model (the ‘Burden-EU’ model) for the calculation of DALY. All-cause mortality data are collected for excess mortality sensitivity analyses. For the calculation of Years lived with disability (YLD), the Burden-EU model is adapted based on recent evidence. Because Covid-19 cases vary in terms of disease severity, the possibility and suitability of applying a uniform severity distribution of cases across all countries and sub-national regions will be explored. An approach recently developed for the Global Burden of Disease Study, that considers post-acute consequences of COVID-19, is likely to be adopted. Findings will be compared to explore the quality and usability of the existing data, to identify trends across age-groups and sexes and to formulate recommendations concerning potential improvements in data availability and quality.DiscussionBoCO-19 serves as a collaborative platform in order to build international capacity for the calculation of burden of disease indicators, and to support national experts in the analysis and interpretation of country-specific data, including their strengths and weaknesses. Challenges include inherent differences in data collection and reporting systems between countries, as well as assumptions that have to be made during the calculation process.</div

GATHER checklist.

IntroductionThe COVID-19 pandemic has had an extensive impact on public health worldwide. However, in many countries burden of disease indicators for COVID-19 have not yet been calculated or used for monitoring. The present study protocol describes an approach developed in the project “The Burden of Disease due to COVID-19. Towards a harmonization of population health metrics for the surveillance of dynamic outbreaks” (BoCO-19). The process of data collection and aggregation across 14 different countries and sub-national regions in Southern and Eastern Europe and Central Asia is described, as well as the methodological approaches used.Materials and methodsThe study implemented in BoCO-19 is a secondary data analysis, using information from national surveillance systems as part of mandatory reporting on notifiable diseases. A customized data collection template is used to gather aggregated data on population size as well as COVID-19 cases and deaths. Years of life lost (YLL), as one component of the number of Disability Adjusted Life Years (DALY), are calculated as described in a recently proposed COVID-19 disease model (the ‘Burden-EU’ model) for the calculation of DALY. All-cause mortality data are collected for excess mortality sensitivity analyses. For the calculation of Years lived with disability (YLD), the Burden-EU model is adapted based on recent evidence. Because Covid-19 cases vary in terms of disease severity, the possibility and suitability of applying a uniform severity distribution of cases across all countries and sub-national regions will be explored. An approach recently developed for the Global Burden of Disease Study, that considers post-acute consequences of COVID-19, is likely to be adopted. Findings will be compared to explore the quality and usability of the existing data, to identify trends across age-groups and sexes and to formulate recommendations concerning potential improvements in data availability and quality.DiscussionBoCO-19 serves as a collaborative platform in order to build international capacity for the calculation of burden of disease indicators, and to support national experts in the analysis and interpretation of country-specific data, including their strengths and weaknesses. Challenges include inherent differences in data collection and reporting systems between countries, as well as assumptions that have to be made during the calculation process.</div