The aim of this study is to determine if there has been a true, absolute, or apparent relative increase in congenital diaphragmatic hernia (CDH) survival for the last 2 decades.
All neonatal Bochdalek CDH patients admitted to an Ontario pediatric surgical hospital during the period when significant improvements in CDH survival was reported (from January 1, 1992, to December 31, 1999) were analyzed. Patient characteristics were assessed for CDH population homogeneity and differences between institutional and vital statistics-based population survival outcomes. SAS 9.1 (SAS Institute, Cary, NC) was used for analysis.
Of 198 cohorts, demographic parameters including birth weight, gestational age, Apgar scores, sex, and associated congenital anomalies did not change significantly. Preoperative survival was 149 (75.2%) of 198, whereas postoperative survival was 133 (89.3%) of 149, and overall institutional survival was 133 (67.2%) of 198. Comparison of institution and population-based mortality (n = 65 vs 96) during the period yielded 32% of CDH deaths unaccounted for by institutions. Yearly analysis of hidden mortality consistently showed a significantly lower mortality in institution-based reporting than population.
A hidden mortality exists for institutionally reported CDH survival rates. Careful interpretation of research findings and more comprehensive population-based tools are needed for reliable counseling and evaluation of current and future treatments.
A common objective of epidemiological surveys is to provide population-level estimates of health indicators. Survey results tend to be biased under selective non-participation. One approach to bias reduction is to collect information about non-participants by contacting them again and asking them to fill in a questionnaire. This information is called re-contact data, and it allows to adjust the estimates for non-participation.
We analyse data from the FINRISK 2012 survey, where re-contact data were collected. We assume that the respondents of the re-contact survey are similar to the remaining non-participants with respect to the health given their available background information. Validity of this assumption is evaluated based on the hospitalisation data obtained through record linkage of survey data to the administrative registers. Using this assumption and multiple imputation, we estimate the prevalences of daily smoking and heavy alcohol consumption and compare them to estimates obtained with a commonly used assumption that the participants represent the entire target group.
When adjusting for non-participation using re-contact data, higher prevalence estimates were observed compared to prevalence estimates based on participants only. Among men, the smoking prevalence estimate was 28.5% (23.2% for participants) and heavy alcohol consumption prevalence was 9.4% (6.8% for participants). Among women, smoking prevalence was 19% (16.5% for participants) and heavy alcohol consumption was 4.8% (3% for participants).
The utilisation of re-contact data is a useful method to adjust for non-participation bias on population estimates in epidemiological surveys.
BACKGROUND: It is unclear if objective selection of employees, for an intervention to prevent sickness absence, is more effective than subjective 'personal enlistment'. We hypothesize that objectively selected employees are 'at risk' for sickness absence and eligible to participate in the intervention program. METHODS: The dispatch of 8603 screening instruments forms the starting point of the objective selection process. Different stages of this process, throughout which employees either dropped out or were excluded, were described and compared with the subjective selection process. Characteristics of ineligible and ultimately selected employees, for a randomized trial, were described and quantified using sickness absence data. RESULTS: Overall response rate on the screening instrument was 42.0%. Response bias was found for the parameters sex and age, but not for sickness absence. Sickness absence was higher in the 'at risk' (N = 212) group (42%) compared to the 'not at risk' (N = 2503) group (25%) (OR 2.17 CI 1.63-2.89; p = 0.000). The selection process ended with the successful inclusion of 151 eligible, i.e. 2% of the approached employees in the trial. CONCLUSION: The study shows that objective selection of employees for early intervention is effective. Despite methodological and practical problems, selected employees are actually those at risk for sickness absence, who will probably benefit more from the intervention program than others.
There is little agreement on the philosophy of measuring clinical quality in health care. How data should be analyzed and transformed to healthcare information is an ongoing discussion. To accept a difference in quality between health departments as a real difference, one should consider to which extent the selection of patients, random variation, confounding and inconsistency may have influenced results. The aim of this article is to summarize aspects of clinical healthcare data analyses provided from the national clinical quality databases and to show how data may be presented in a way which is understandable to readers without specialised knowledge of statistics.
This study examined potential self-selection bias in a large pregnancy cohort by comparing exposure-outcome associations from the cohort to similar associations obtained from nationwide registry data. The outcome under study was specialist-confirmed diagnosis of autism spectrum disorders (ASDs).
The cohort sample (n = 89 836) was derived from the population-based prospective Norwegian Mother and Child Cohort Study and its substudy of ASDs, the Autism Birth Cohort (ABC) study. The nationwide registry data were derived from the Medical Birth Registry of Norway (n = 507 856). The children were born in 1999–2007, and seven prenatal and perinatal exposures were selected for analyses.
ASDs were reported for 234 (0.26%) children in the cohort and 2072 (0.41%) in the nationwide population. Compared with the nationwide population, the cohort had an under-representation of the youngest women (
A sensitivity analysis was conducted to determine the impact on measures of effect of a suspected differential participation response rate between hormone replacement therapy (HRT) users and nonusers, among controls recruited to a population-based case-control study of breast cancer. The age-specific prevalence of current HRT use among controls was compared to data from the 1996 Canadian National Population Health Survey (NPHS). Control women identified as current HRT users were randomly re-sampled to replicate the prevalence of HRT use reported by the NPHS. Unconditional logistic regression was conducted to estimate odds ratios (OR) and 95 percent confidence intervals (CI) for the use of HRT and breast cancer risk before and after re-sampling. Multivariate adjusted ORs for breast cancer and estrogen-only and estrogen-progestin formulations were 0.76 (0.53-1.10) and 0.94 (95% CI: 0.64 - 1.38), respectively, using the original case-control controls and 0.99 (0.77-1.27) and 1.57 (95% CI: 1.02 - 2.40), respectively, following re-sampling of the controls. This sensitivity analysis illustrates the extent to which differential participation rates between HRT users and nonusers may affect estimates of measures of effect.
Evidence informed decision making in health policy development and clinical practice depends on the availability of valid and reliable data. The introduction of interRAI assessment systems in many countries has provided valuable new information that can be used to support case mix based payment systems, quality monitoring, outcome measurement and care planning. The Continuing Care Reporting System (CCRS) managed by the Canadian Institute for Health Information has served as a data repository supporting national implementation of the Resident Assessment Instrument (RAI 2.0) in Canada for more than 15 years. The present paper aims to evaluate data quality for the CCRS using an approach that may be generalizable to comparable data holdings internationally.
Data from the RAI 2.0 implementation in Complex Continuing Care (CCC) hospitals/units and Long Term Care (LTC) homes in Ontario were analyzed using various statistical techniques that provide evidence for trends in validity, reliability, and population attributes. Time series comparisons included evaluations of scale reliability, patterns of associations between items and scales that provide evidence about convergent validity, and measures of changes in population characteristics over time.
Data quality with respect to reliability, validity, completeness and freedom from logical coding errors was consistently high for the CCRS in both CCC and LTC settings. The addition of logic checks further improved data quality in both settings. The only notable change of concern was a substantial inflation in the percentage of long term care home residents qualifying for the Special Rehabilitation level of the Resource Utilization Groups (RUG-III) case mix system after the adoption of that system as part of the payment system for LTC.
The CCRS provides a robust, high quality data source that may be used to inform policy, clinical practice and service delivery in Ontario. Only one area of concern was noted, and the statistical techniques employed here may be readily used to target organizations with data quality problems in that (or any other) area. There was also evidence that data quality was good in both CCC and LTC settings from the outset of implementation, meaning data may be used from the entire time series. The methods employed here may continue to be used to monitor data quality in this province over time and they provide a benchmark for comparisons with other jurisdictions implementing the RAI 2.0 in similar populations.
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Breast cancer and its treatment have been associated with psychological morbidity. In this study our aim was to quantify the excess anxiety and depression resulting from breast cancer. We compared 538 newly diagnosed breast cancer patients at low risk of recurrence (87.0% responded) to 872 women randomly selected from the Danish general population (69.7% responded) using the Hospital Anxiety and Depression Scale (HADS). Contrary to expectations, the proportions classified as "cases" of anxiety and depression were not significantly different in the two groups. The breast cancer patients' mean HADS scores were significantly lower than those in the general population sample (anxiety, P = 0.021; depression, P
A health survey was performed in 2007-2008 in the IDEFICS/Sweden study (Identification and prevention of dietary- and lifestyle-induced health effects in children and infants) in children aged 2-9 years. We hypothesized that families with disadvantageous socioeconomic and -demographic backgrounds and children with overweight and obesity were underrepresented.
In a cross-sectional study, we compared Swedish IDEFICS participants (N=1,825) with referent children (N=1,825) using data from Statistics Sweden population registers. IDEFICS participants were matched for age and gender with a referent child living in the same municipality. Longitudinal weight and height data from birth to 8 years was collected for both populations (n=3,650) from the children's local health services. Outcome measures included the family's socioeconomic and demographic characteristics, maternal body mass index (BMI) and smoking habits before pregnancy, the children's BMI standard deviation score (SDS) at the age of inclusion in the IDEFICS study (BMISDS-index), and the children's BMI-categories during the age-span. Comparisons between groups were done and a multiple logistic regression analysis for the study of determinants of participation in the IDEFICS study was performed.
Compared with IDEFICS participants, referent families were more likely to have lower education and income, foreign backgrounds, be single parents, and have mothers who smoked before pregnancy. Maternal BMI before pregnancy and child's BMISDS-index did not differ between groups. Comparing the longitudinal data-set, the prevalence of obesity was significantly different at age 8 years n= 45 (4.5%) versus n= 31 (2.9%) in the referent and IDEFICS populations, respectively. In the multivariable adjusted model, the strongest significant association with IDEFICS study participation was parental Swedish background (odds ratio (OR) = 1.91, 95% confidence interval (CI) (1.48-2.47) followed by parents having high education OR 1.80, 95% CI (1.02-3.16) and being married or co-habiting OR 1.75 95% CI (1.38-2.23).
Families with single parenthood, foreign background, low education and income were underrepresented in the IDEFICS Sweden study. BMI at inclusion had no selection effect, but developing obesity was significantly greater among referents.