14 research outputs found
The Use of High Dose Letrozole in Ovulation Induction and Controlled Ovarian Hyperstimulation
Letrozole, an aromatase inhibitor, has been demonstrated to be effective as an ovulation induction and controlled ovarian hyperstimulation agent. However, dose administration has generally been limited to 5 days at 2.5 to 7.5 mg daily. We undertook a retrospective review of over 900 treatment cycles using letrozole in doses as high as 12.5 mg per day. Results indicate that such doses do indeed offer benefit to patients; in that there is increased follicular growth and a higher number of predicted ovulations with higher doses of the drug. However, increasing doses does not produce a detrimental effect upon endometrial thickness. High-dose letrozole may be of value in women who fail to respond adequately to lower doses. Furthermore, randomized trials are needed to determine whether high-dose letrozole might actually be optimal as a starting dose for certain treatment groups
The re-identification risk of Canadians from longitudinal demographics
<p>Abstract</p> <p>Background</p> <p>The public is less willing to allow their personal health information to be disclosed for research purposes if they do not trust researchers and how researchers manage their data. However, the public is more comfortable with their data being used for research if the risk of re-identification is low. There are few studies on the risk of re-identification of Canadians from their basic demographics, and no studies on their risk from their longitudinal data. Our objective was to estimate the risk of re-identification from the basic cross-sectional and longitudinal demographics of Canadians.</p> <p>Methods</p> <p>Uniqueness is a common measure of re-identification risk. Demographic data on a 25% random sample of the population of Montreal were analyzed to estimate population uniqueness on postal code, date of birth, and gender as well as their generalizations, for periods ranging from 1 year to 11 years.</p> <p>Results</p> <p>Almost 98% of the population was unique on full postal code, date of birth and gender: these three variables are effectively a unique identifier for Montrealers. Uniqueness increased for longitudinal data. Considerable generalization was required to reach acceptably low uniqueness levels, especially for longitudinal data. Detailed guidelines and disclosure policies on how to ensure that the re-identification risk is low are provided.</p> <p>Conclusions</p> <p>A large percentage of Montreal residents are unique on basic demographics. For non-longitudinal data sets, the three character postal code, gender, and month/year of birth represent sufficiently low re-identification risk. Data custodians need to generalize their demographic information further for longitudinal data sets.</p
Physician privacy concerns when disclosing patient data for public health purposes during a pandemic influenza outbreak
Background: Privacy concerns by providers have been a barrier to disclosing patient information for public health\ud
purposes. This is the case even for mandated notifiable disease reporting. In the context of a pandemic it has been\ud
argued that the public good should supersede an individual’s right to privacy. The precise nature of these provider\ud
privacy concerns, and whether they are diluted in the context of a pandemic are not known. Our objective was to\ud
understand the privacy barriers which could potentially influence family physicians’ reporting of patient-level\ud
surveillance data to public health agencies during the Fall 2009 pandemic H1N1 influenza outbreak.\ud
Methods: Thirty seven family doctors participated in a series of five focus groups between October 29-31 2009.\ud
They also completed a survey about the data they were willing to disclose to public health units. Descriptive\ud
statistics were used to summarize the amount of patient detail the participants were willing to disclose, factors that\ud
would facilitate data disclosure, and the consensus on those factors. The analysis of the qualitative data was based\ud
on grounded theory.\ud
Results: The family doctors were reluctant to disclose patient data to public health units. This was due to concerns\ud
about the extent to which public health agencies are dependable to protect health information (trusting beliefs),\ud
and the possibility of loss due to disclosing health information (risk beliefs). We identified six specific actions that\ud
public health units can take which would affect these beliefs, and potentially increase the willingness to disclose\ud
patient information for public health purposes.\ud
Conclusions: The uncertainty surrounding a pandemic of a new strain of influenza has not changed the privacy\ud
concerns of physicians about disclosing patient data. It is important to address these concerns to ensure reliable\ud
reporting during future outbreaks.University of Ottawa Open Access Author Fun