Screening primary-care patients forgoing health care for economic reasons.

BACKGROUND: Growing social inequities have made it important for general practitioners to verify if patients can afford treatment and procedures. Incorporating social conditions into clinical decision-making allows general practitioners to address mismatches between patients' health-care needs and financial resources. OBJECTIVES: Identify a screening question to, indirectly, rule out patients' social risk of forgoing health care for economic reasons, and estimate prevalence of forgoing health care and the influence of physicians' attitudes toward deprivation. DESIGN: Multicenter cross-sectional survey. PARTICIPANTS: Forty-seven general practitioners working in the French-speaking part of Switzerland enrolled a random sample of patients attending their private practices. MAIN MEASURES: Patients who had forgone health care were defined as those reporting a household member (including themselves) having forgone treatment for economic reasons during the previous 12 months, through a self-administered questionnaire. Patients were also asked about education and income levels, self-perceived social position, and deprivation levels. KEY RESULTS: Overall, 2,026 patients were included in the analysis; 10.7% (CI95% 9.4-12.1) reported a member of their household to have forgone health care during the 12 previous months. The question "Did you have difficulties paying your household bills during the last 12 months" performed better in identifying patients at risk of forgoing health care than a combination of four objective measures of socio-economic status (gender, age, education level, and income) (R(2) = 0.184 vs. 0.083). This question effectively ruled out that patients had forgone health care, with a negative predictive value of 96%. Furthermore, for physicians who felt powerless in the face of deprivation, we observed an increase in the odds of patients forgoing health care of 1.5 times. CONCLUSION: General practitioners should systematically evaluate the socio-economic status of their patients. Asking patients whether they experience any difficulties in paying their bills is an effective means of identifying patients who might forgo health care.

Using information from telephone panel surveys to predict reasons for refusal

One of the key problems in conducting surveys is convincing people to participate.¦However, it is often difficult or impossible to determine why people refuse. Panel surveys¦provide information from previous waves that can offer valuable clues as to why people¦refuse to participate. If we are able to anticipate the reasons for refusal, then we¦may be able to take appropriate measures to encourage potential respondents to participate¦in the survey. For example, special training could be provided for interviewers¦on how to convince potential participants to participate.¦This study examines different influences, as determined from the previous wave,¦on refusal reasons that were given by the respondents in the subsequent wave of the¦telephone Swiss Household Panel. These influences include socio-demography, social¦inclusion, answer quality, and interviewer assessment of question understanding and¦of future participation. Generally, coefficients are similar across reasons, and¦between-respondents effects rather than within-respondents effects are significant.¦While 'No interest' reasons are easier to predict, the other reasons are more situational. Survey-specific issues are able to distinguish¦different reasons to some extent.

Hazardous substances in frequently used professional cleaning products.

A growing number of studies have identified cleaners as a group at risk for adverse health effects of the skin and the respiratory tract. Chemical substances present in cleaning products could be responsible for these effects. Currently, only limited information is available about irritant and health hazardous chemical substances found in cleaning products. We hypothesized that chemical substances present in cleaning products are known health hazardous substances that might be involved in adverse health effects of the skin and the respiratory tract. We performed a systematic review of cleaning products used in the Swiss cleaning sector. We surveyed Swiss professional cleaning companies (n = 1476) to identify the most used products (n = 105) for inclusion. Safety data sheets (SDSs) were reviewed and hazardous substances present in cleaning products were tabulated with current European and global harmonized system hazard labels. Professional cleaning products are mixtures of substances (arithmetic mean 3.5 +/- 2.8), and more than 132 different chemical substances were identified in 105 products. The main groups of chemicals were fragrances, glycol ethers, surfactants, solvents; and to a lesser extent, phosphates, salts, detergents, pH-stabilizers, acids, and bases. Up to 75% of products contained irritant (Xi), 64% harmful (Xn) and 28% corrosive (C) labeled substances. Hazards for eyes (59%) and skin (50%), and hazards by ingestion (60%) were the most reported. Cleaning products potentially give rise to simultaneous exposures to different chemical substances. As professional cleaners represent a large workforce, and cleaning products are widely used, it is a major public health issue to better understand these exposures. The list of substances provided in this study contains important information for future occupational exposure assessment studies.

The determinants of sport participation in Switzerland

This paper aims at investigating the socio-cultural factors that affect leisure-time sport participation in Switzerland. Data drawn from 8 waves of the Swiss Household Panel is used to evaluate a probit model with random effects, that takes into account the socioeconomic and demographic characteristics of the respondents. In line with existing literature, findings from the multivariate analysis show inequalities in sport involvement in Switzerland. These are significantly related to age, income, education, citizenship and cultural aspects. Appropriate and targeted policies promoting participation in sports among the community can be found on the basis of the critical modifiers in the model and their impact.

Characterizing the vulnerability of frequent emergency department users by applying a conceptual framework: a controlled, cross-sectional study.

BACKGROUND: Frequent emergency department (ED) users meet several of the criteria of vulnerability, but this needs to be further examined taking into consideration all vulnerability's different dimensions. This study aimed to characterize frequent ED users and to define risk factors of frequent ED use within a universal health care coverage system, applying a conceptual framework of vulnerability. METHODS: A controlled, cross-sectional study comparing frequent ED users to a control group of non-frequent users was conducted at the Lausanne University Hospital, Switzerland. Frequent users were defined as patients with five or more visits to the ED in the previous 12 months. The two groups were compared using validated scales for each one of the five dimensions of an innovative conceptual framework: socio-demographic characteristics; somatic, mental, and risk-behavior indicators; and use of health care services. Independent t-tests, Wilcoxon rank-sum tests, Pearson's Chi-squared test and Fisher's exact test were used for the comparison. To examine the -related to vulnerability- risk factors for being a frequent ED user, univariate and multivariate logistic regression models were used. RESULTS: We compared 226 frequent users and 173 controls. Frequent users had more vulnerabilities in all five dimensions of the conceptual framework. They were younger, and more often immigrants from low/middle-income countries or unemployed, had more somatic and psychiatric comorbidities, were more often tobacco users, and had more primary care physician (PCP) visits. The most significant frequent ED use risk factors were a history of more than three hospital admissions in the previous 12 months (adj OR:23.2, 95%CI = 9.1-59.2), the absence of a PCP (adj OR:8.4, 95%CI = 2.1-32.7), living less than 5 km from an ED (adj OR:4.4, 95%CI = 2.1-9.0), and household income lower than USD 2,800/month (adj OR:4.3, 95%CI = 2.0-9.2). CONCLUSIONS: Frequent ED users within a universal health coverage system form a highly vulnerable population, when taking into account all five dimensions of a conceptual framework of vulnerability. The predictive factors identified could be useful in the early detection of future frequent users, in order to address their specific needs and decrease vulnerability, a key priority for health care policy makers. Application of the conceptual framework in future research is warranted.