Employment Situation of Parents of Long-Term Childhood Cancer Survivors.

BACKGROUND Taking care of children diagnosed with cancer affects parents' professional life. The impact in the long-term however, is not clear. We aimed to compare the employment situation of parents of long-term childhood cancer survivors with control parents of the general population, and to identify clinical and socio-demographic factors associated with parental employment. METHODS As part of the Swiss Childhood Cancer Survivor Study, we sent a questionnaire to parents of survivors aged 5-15 years, who survived ≥5 years after diagnosis. Information on control parents of the general population came from the Swiss Health Survey (restricted to men and women with ≥1 child aged 5-15 years). Employment was categorized as not employed, part-time, and full-time employed. We used generalized ordered logistic regression to determine associations with clinical and socio-demographic factors. Clinical data was available from the Swiss Childhood Cancer Registry. RESULTS We included 394 parent-couples of survivors and 3'341 control parents (1'731 mothers; 1'610 fathers). Mothers of survivors were more often not employed (29% versus 22%; ptrend = 0.007). However, no differences between mothers were found in multivariable analysis. Fathers of survivors were more often employed full-time (93% versus 87%; ptrend = 0.002), which remained significant in multivariable analysis. Among parents of survivors, mothers with tertiary education (OR = 2.40, CI:1.14-5.07) were more likely to be employed. Having a migration background (OR = 3.63, CI: 1.71-7.71) increased the likelihood of being full-time employed in mothers of survivors. Less likely to be employed were mothers of survivors diagnosed with lymphoma (OR = 0.31, CI:0.13-0.73) and >2 children (OR = 0.48, CI:0.30-0.75); and fathers of survivors who had had a relapse (OR = 0.13, CI:0.04-0.36). CONCLUSION Employment situation of parents of long-term survivors reflected the more traditional parenting roles. Specific support for parents with low education, additional children, and whose child had a more severe cancer disease could improve their long-term employment situation.

Frequency of and predictors for patient-reported medical and medication errors in Switzerland

OBJECTIVES: To analyse the frequency of and identify risk factors for patient-reported medical errors in Switzerland. The joint effect of risk factors on error-reporting probability was modelled for hypothetical patients. METHODS: A representative population sample of Swiss citizens (n = 1306) was surveyed as part of the Commonwealth Fund’s 2010 lnternational Survey of the General Public’s Views of their Health Care System’s Performance in Eleven Countries. Data on personal background, utilisation of health care, coordination of care problems and reported errors were assessed. Logistic regression analysis was conducted to identify risk factors for patients’ reports of medical mistakes and medication errors. RESULTS: 11.4% of participants reported at least one error in their care in the previous two years (8% medical errors, 5.3% medication errors). Poor coordination of care experiences was frequent. 7.8% experienced that test results or medical records were not available, 17.2% received conflicting information from care providers and 11.5% reported that tests were ordered although they had been done before. Age (OR = 0.98, p = 0.014), poor health (OR = 2.95, p = 0.007), utilisation of emergency care (OR = 2.45, p = 0.003), inpatient-stay (OR = 2.31, p = 0.010) and poor care coordination (OR = 5.43, p <0.001) are important predictors for reporting error. For high utilisers of care that unify multiple risk factors the probability that errors are reported rises up to p = 0.8. CONCLUSIONS: Patient safety remains a major challenge for the Swiss health care system. Despite the health related and economic burden associated with it, the widespread experience of medical error in some subpopulations also has the potential to erode trust in the health care system as a whole.

On Graphically Checking Goodness-of-fit of Binary Logistic Regression Models

OBJECTIVES: This paper is concerned with checking goodness-of-fit of binary logistic regression models. For the practitioners of data analysis, the broad classes of procedures for checking goodness-of-fit available in the literature are described. The challenges of model checking in the context of binary logistic regression are reviewed. As a viable solution, a simple graphical procedure for checking goodness-of-fit is proposed. METHODS: The graphical procedure proposed relies on pieces of information available from any logistic analysis; the focus is on combining and presenting these in an informative way. RESULTS: The information gained using this approach is presented with three examples. In the discussion, the proposed method is put into context and compared with other graphical procedures for checking goodness-of-fit of binary logistic models available in the literature. CONCLUSION: A simple graphical method can significantly improve the understanding of any logistic regression analysis and help to prevent faulty conclusions.