BackgroundThe aim of our study was to describe variability in process quality in family medicine among 31 European countries plus Australia, New Zealand, and Canada. The quality of family medicine was measured in terms of continuity, coordination, community orientation, and comprehensiveness of care.MethodsThe QUALICOPC study (Quality and Costs of Primary Care in Europe) was carried out among family physicians in 31 European countries (the EU 27 except for France, plus Macedonia, Iceland, Norway, Switzerland, and Turkey) and three non-European countries (Australia, Canada, and New Zealand). We used random sampling when national registers of practitioners were available. Regional registers or lists of facilities were used for some countries.A standardized questionnaire was distributed to the physicians, resulting in a sample of 6734 participants. Data collection took place between October 2011 and December 2013. Based on completed questionnaires, a three-dimensional framework was established to measure continuity, coordination, community orientation, and comprehensiveness of care. Multilevel linear regression analysis was performed to evaluate the variation of quality attributable to the family physician level and the country level.ResultsNone of the 34 countries in this study consistently scored the best or worst in all categories. Continuity of care was perceived by family physicians as the most important dimension of quality. Some components of comprehensiveness of care, including medical technical procedures, preventive care and health care promotion, varied substantially between countries. Coordination of care was identified as the weakest part of quality. We found that physician-level characteristics contributed to the majority of variation.ConclusionsA comparison of process quality indicators in family medicine revealed similarities and differences within and between countries. The researchers found that the major proportion of variation can be explained by physicians’ characteristics.Electronic supplementary materialThe online version of this article (doi:10.1186/s12875-015-0386-7) contains supplementary material, which is available to authorized users.

AimWe sought to examine strength of primary care service delivery as measured by selected process indicators by general practitioners from 31 European countries plus Australia, Canada, and New Zealand. We explored the relation between strength of service delivery and healthcare expenditures.BackgroundThe strength of a country’s primary care is determined by the degree of development of a combination of core primary care dimensions in the context of its healthcare system. This study analyses the strength of service delivery in primary care as measured through process indicators in 31 European countries plus Australia, New Zealand, and Canada.MethodsA comparative cross-sectional study design was applied using the QUALICOPC GP database. Data on the strength of primary healthcare were collected using a standardized GP questionnaire, which included 60 questions divided into 10 dimensions related to process, structure, and outcomes. A total of 6734 general practitioners participated. Data on healthcare expenditure were obtained from World Bank statistics. We conducted a correlation analysis to analyse the relationship between strength and healthcare expenditures.FindingsOur findings show that the strength of service delivery parameters is less than optimal in some countries, and there are substantial variations among countries. Continuity and comprehensiveness of care are significantly positively related to national healthcare expenditures; however, coordination of care is not.

IntroductionPrimary care (PC) is the provision of universally accessible, integrated, person-centred, comprehensive health and community services. Professionals active in primary care teams include family physicians and general practitioners (FP/GPs). There is concern in Slovenia that the current economic crisis might change the nature of PC services. Access, one of the most basic requirements of general practice, is universal in Slovenia, which is one of the smallest European countries; under national law, compulsory health insurance is mandatory for its citizens. Our study examined access to PC in Slovenia during a time of economic crisis as experienced and perceived by patients between 2011 and 2012, and investigated socio-demographic factors affecting access to PC in Slovenia.MethodsData were collected as a part of a larger international study entitled Quality and Costs of Primary Care in Europe (QUALICOPC) that took place during a period of eight months in 2011 and 2012. 219 general practices were included; in each, the aim was to evaluate 10 patients. Dependent variables covered five aspects of access to PC: communicational, cultural, financial, geographical and organizational. 15 socio-demographic factors were investigated as independent variables. Descriptive statistics, factor analysis and multilevel analysis were applied.ResultsThere were 1,962 patients in the final sample, with a response rate of 89.6%. The factors with the most positive effect on access to PC were financial and cultural; the most negative effects were caused by organizational problems. Financial difficulties were not a significant socio-demographic factor. Greater frequency of visits improves patients’ perception of communicational and cultural access. Deteriorating health conditions are expected to lower perceived geographical access. Patients born outside Slovenia perceived better organizational access than patients born in Slovenia.ConclusionsUniversal medical insurance in Slovenia protects most patients from PC inaccessibility. However, problems perceived by patients may indicate the need for changes in the organization of PC.Electronic supplementary materialThe online version of this article (doi:10.1186/s12939-015-0166-y) contains supplementary material, which is available to authorized users.

Introduction: Slovenia has a high level of alcohol consumption. Comparisons of the alcohol drinking habits of the Roma and non-Roma population have yielded conflicting results. The aim of this research was to compare alcohol consumption habits between Roma and non-Roma in a sample population in Northeastern Slovenia. Methods: We conducted a cross-sectional study in which we included 100 representatives of Roma and 100 representatives of non-Roma population, aged 18 to 65 years. The questionnaire used included demographic data (gender, age, marital status, education, and employment) and the AUDIT (Alcohol Use Disorders Identification Test) questionnaire. Two logistic regression models (teetotallers/drinkers and non-hazardous drinkers/other drinkers) were used for the comparison of drinking habits. Results: Roma scored lower on overall AUDIT score (4.51) than non-Roma (4.56). Roma and non-Roma differ significantly regarding teetotallers (39.0% vs. 16.0%) and non-hazardous drinkers (38.0% vs. 64.0%). Ethnicity was identified to have a statistically significant impact on the studied drinking behaviour: teetotallers (p < 0.001) and non-hazardous drinkers (p = 0.015). Discussion and conclusion: Our aim was to look at the differences between the two groups rather than obtain representative data on the population. Our research also casts a doubt on whether the AUDIT scale is suitable for measuring alcohol abuse.

Discriminant analysis is a widely used multivariate technique with Fisher's discriminant analysis (FDA) being its most venerable form. FDA assumes equality of population covariance matrices, but does not require multivariate normality. Nevertheless, the latter is desirable for optimal classification. To test FDA's performance under non-normality caused by skewness the method was assessed with simulation based on a skew-curved normal (SCN) distribution belonging to the family of skew-generalised normal distributions; additionally, effects of sample size and rotation were evaluated. Apparent error rate (APER) was used as the measure of classification performance. The analysis was performed using ANOVA with (transformed) mean APER as the dependent variable. Results show the FDA to be highly robust to skewness introduced into the model via the SCN distributed simulated data.