Bart J. Harvey

Evaluating the cost-effectiveness of breast cancer screening requires estimates of the absolute risk of breast cancer, which is modified by various risk factors. Breast cancer incidence, and thus mortality, is altered by the occurrence of competing events. More accurate estimates of competing risks should improve the estimation of absolute risk of breast cancer and benefit from breast cancer screening, leading to more effective preventive, diagnostic, and treatment policies. We have previously described the effect of breast cancer risk factors on breast cancer incidence in the presence of competing risks. In this study, we investigate the association of the same risk factors with mortality as a competing event with breast cancer incidence.

Improvements in the quality of health care services are often measured using data present in medical records. Electronic Medical Records (EMRs) contain potentially valuable new sources of health data. However, data quality in EMRs may not be optimal and should be assessed. Data reliability (are the same data elements being measured over time?) is a prerequisite for data validity (are the data accurate?). Our objective was to measure the reliability of data for preventive services in primary care EMRs during the transition to EMR.

In population-based surveys, sample lists are often out of date by the time data collection begins. Consequently, response rates, and the perceived validity of the survey, may be compromised by the unknowing inclusion of ineligible subjects. A strategy to address this issue is ascertainment of survey nonrespondents’ eligibility status, enabling post hoc adjustment of response rates. In 1995–1996, population surveys were carried out in two Ontario, Canada, communities. Despite intensive follow-up, the status of 8,949 (18.6%) of the 48,218 potential subjects in these surveys remained unknown. In response, 500 “unknowns” from each community were randomly selected for tracing by using publicly available telephone directories and, where applicable, city directories. These tracing efforts classified persons into one of three groups: “ineligible” (moved before the mailing), “true nonresponder” (present when the survey was mailed), and “remains unknown” (no directory listing found). Publicly available directories clarified the status of 76.0% of potential participants, reducing the proportion of “unknowns” from 18.6% to 4.6%. Applying the estimated proportions of “ineligibles” from each area resulted in response rates adjusted from 63.8% to 71.2% and from 72.8% to 74.9% in the survey areas. Publicly available directories were used to successfully trace the majority of survey nonresponders, thus strengthening confidence in the survey’s results.