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

Additional file 5: of Impact of HPV vaccination with Gardasil® in Switzerland

Segmented logistic regression analysis of the evolution of the yearly proportion of vaccine-type HPV (vHPV) among all HPV in sub-study-2 outpatients. (DOCX 27 kb

Additional file 1: of Impact of HPV vaccination with Gardasil® in Switzerland

Sub-study-1 flowchart and questionnaire results. (PDF 418 kb

Additional file 3: of Impact of HPV vaccination with Gardasil® in Switzerland

R script used to graph the yearly evolution of the vaccine-type HPV proportion recorded in the Additional file 2. It can be renamed “HPV_1999–2015_evolution.R”. (R 3 kb

Table1_Determinants of COVID-19 Vaccine Hesitancy During the Pandemic: A Cross-Sectional Survey in the Canton of Vaud, Switzerland.docx

Objectives: COVID-19 vaccine hesitancy is a major obstacle in the fight against the pandemic. This study aimed to identify the local determinants of vaccine hesitancy in the context of COVID-19 to better inform future immunization campaigns.Methods: The study, conducted in February 2021, included 1,189 randomly selected inhabitants of the canton of Vaud, Switzerland. Online questionnaires investigated determinants of the intention to vaccinate. Previously validated scores (Cronbach’s alphas >0.70) were applied to our data for inclusion in the ordinal logistic regression model.Results: Individuals were more likely to vaccinate if they were 40 years or older, wealthy, reported a high educational attainment, or reported comorbidities. Doubts regarding vaccine safety and efficacy, mistrust in authorities and a propensity for natural immunity were identified as the main local hindrances to the COVID-19 vaccination.Conclusion: Outreach to people at risk of severe COVID-19 is particularly relevant in the pandemic context to help mitigate vaccine hesitancy in the canton of Vaud, and should take into consideration the level of education. Further investigation is needed to better understand reasons for mistrust in authorities.</p

Results DipCare-q.

<p>Results DipCare-q.</p

CART analysis.

<p>Classification And Regression Tree analysis of variables separating the examined population into subgroups with increasing overall (a.), material (b.), social (c.) and health (d.) deprivation scores.</p

Additional file 2: of Multimorbidity: can general practitioners identify the health conditions most important to their patients? Results from a national cross-sectional study in Switzerland

Table S2. a Agreement as per the 46 groups of conditions (N = 572). Table S2. b Agreement as per the chapters of the ICPC-2 classification (N = 585). (DOCX 20 kb

Additional file 1: of Multimorbidity: can general practitioners identify the health conditions most important to their patients? Results from a national cross-sectional study in Switzerland

Table S1. Classification of items of the ICPC-2 into 46 categories adapted from van den Bussche et al. (DOCX 25 kb