Determinants associated with deprivation in multimorbid patients in primary care-A cross-sectional study in Switzerland

Deprivation usually encompasses material, social, and health components. It has been shown to be associated with greater risks of developing chronic health conditions and of worse outcome in multimorbidity. The DipCare questionnaire, an instrument developed and validated in Switzerland for use in primary care, identifies patients subject to potentially higher levels of deprivation. To identifying determinants of the material, social, and health profiles associated with deprivation in a sample of multimorbid, primary care patients, and thus set priorities in screening for deprivation in this population. Secondary analysis from a nationwide cross-sectional study in Switzerland. A random sample of 886 adult patients suffering from at least three chronic health conditions. The outcomes of interest were the patients' levels of deprivation as measured using the DipCare questionnaire. Classification And Regression Tree analysis identified the independent variables that separated the examined population into groups with increasing deprivation scores. Finally, a sensitivity analysis (multivariate regression) confirmed the robustness of our results. Being aged under 64 years old was associated with higher overall, material, and health deprivation; being aged over 77 years old was associated with higher social deprivation. Other variables associated with deprivation were the level of education, marital status, and the presence of depression or chronic pain. Specific profiles, such as being younger, were associated with higher levels of overall, material, and health deprivation in multimorbid patients. In contrast, patients over 77 years old reported higher levels of social deprivation. Furthermore, chronic pain and depression added to the score for health deprivation. It is important that GPs consider the possibility of deprivation in these multimorbid patients and are able to identify it, both in order to encourage treatment adherence and limit any forgoing of care for financial reasons

Multimorbidity: can general practitioners identify the health conditions most important to their patients? Results from a national cross-sectional study in Switzerland

Faced with patients suffering from more than one chronic condition, or multimorbidity, general practitioners (GPs) must establish diagnostic and treatment priorities. Patients also set their own priorities to handle the everyday burdens associated with their multimorbidity and these may be different from the priorities established by their GP. A shared patient-GP agenda, driven by knowledge of each other's priorities, would seem central to managing patients with multimorbidity. We evaluated GPs' ability to identify the health condition most important to their patients. Data on 888 patients were collected as part of a cross-sectional Swiss study on multimorbidity in family medicine. For the main analyses on patients-GP agreement, data from 572 of these patients could be included. GPs were asked to identify the two conditions which their patient considered most important, and we tested whether either of them agreed with the condition mentioned as most important by the patient. In the main analysis, we studied the agreement rate between GPs and patients by grouping items medically-related into 46 groups of conditions. Socio-demographic and clinical variables were fitted into univariate and multivariate models. In 54.9% of cases, GPs were able to identify the health condition most important to the patient. In the multivariate model, the only variable significantly associated with patient-GP agreement was the number of chronic conditions: the higher the number of conditions, the less likely the agreement. GPs were able to correctly identify the health condition most important to their patients in half of the cases. It therefore seems important that GPs learn how to better adapt treatment targets and priorities by taking patients' perspectives into account

Measles in Democratic Republic of Congo: an outbreak description from Katanga, 2010--2011

BACKGROUND: The Democratic Republic of Congo experiences regular measles outbreaks. From September 2010, the number of suspected measles cases increased, especially in Katanga province, where Medecins sans Frontieres supported the Ministry of Health in responding to the outbreak by providing free treatment, reinforcing surveillance and implementing non-selective mass vaccination campaigns. Here, we describe the measles outbreak in Katanga province in 2010--2011 and the results of vaccine coverage surveys conducted after the mass campaigns. METHODS: The surveillance system was strengthened in 28 of the 67 health zones of the province and we conducted seven vaccination coverage surveys in 2011. RESULTS: The overall cumulative attack rate was 0.71% and the case fatality ratio was 1.40%.The attack rate was higher in children under 4 and decreased with age. This pattern was consistent across districts and time. The number of cases aged 10 years and older barely increased during the outbreak. CONCLUSIONS: Early investigation of the age distribution of cases is a key to understanding the epidemic, and should guide the vaccination of priority age groups

Community-based measles mortality surveillance in two districts of Katanga Province, Democratic Republic of Congo

Mortality due to measles is often under-reported. Traditional methods of measuring mortality can be time and resource-intensive. We describe the implementation of a community-based method to monitor measles mortality

Univariate subgroup comparisons in the sample of multimorbid patients.

<p>N = 888.</p

Distributions of the EQ-5D-3L (EQ-5D items and visual analog scale) among multimorbid patients.

<p>N = 888.</p

Observed and predicted mean health utility and VAS, and the differences between them in 888 multimorbid patients.

<p>Observed and predicted mean health utility and VAS, and the differences between them in 888 multimorbid patients.</p

Most frequently reported EQ-5D health states and distributions of corresponding mean HU and mean VAS values among a sample of multimorbid patients.

<p>N = 888.</p

Multimorbidity: can general practitioners identify the health conditions most important to their patients? Results from a national cross-sectional study in Switzerland

Abstract Background Faced with patients suffering from more than one chronic condition, or multimorbidity, general practitioners (GPs) must establish diagnostic and treatment priorities. Patients also set their own priorities to handle the everyday burdens associated with their multimorbidity and these may be different from the priorities established by their GP. A shared patient–GP agenda, driven by knowledge of each other’s priorities, would seem central to managing patients with multimorbidity. We evaluated GPs’ ability to identify the health condition most important to their patients. Methods Data on 888 patients were collected as part of a cross-sectional Swiss study on multimorbidity in family medicine. For the main analyses on patients-GP agreement, data from 572 of these patients could be included. GPs were asked to identify the two conditions which their patient considered most important, and we tested whether either of them agreed with the condition mentioned as most important by the patient. In the main analysis, we studied the agreement rate between GPs and patients by grouping items medically-related into 46 groups of conditions. Socio-demographic and clinical variables were fitted into univariate and multivariate models. Results In 54.9% of cases, GPs were able to identify the health condition most important to the patient. In the multivariate model, the only variable significantly associated with patient–GP agreement was the number of chronic conditions: the higher the number of conditions, the less likely the agreement. Conclusion GPs were able to correctly identify the health condition most important to their patients in half of the cases. It therefore seems important that GPs learn how to better adapt treatment targets and priorities by taking patients’ perspectives into account