45 research outputs found
City-wide Analysis of Electronic Health Records Reveals Gender and Age Biases in the Administration of Known Drug-Drug Interactions
The occurrence of drug-drug-interactions (DDI) from multiple drug
dispensations is a serious problem, both for individuals and health-care
systems, since patients with complications due to DDI are likely to reenter the
system at a costlier level. We present a large-scale longitudinal study (18
months) of the DDI phenomenon at the primary- and secondary-care level using
electronic health records (EHR) from the city of Blumenau in Southern Brazil
(pop. ). We found that 181 distinct drug pairs known to
interact were dispensed concomitantly to 12\% of the patients in the city's
public health-care system. Further, 4\% of the patients were dispensed drug
pairs that are likely to result in major adverse drug reactions (ADR)---with
costs estimated to be much larger than previously reported in smaller studies.
The large-scale analysis reveals that women have a 60\% increased risk of DDI
as compared to men; the increase becomes 90\% when considering only DDI known
to lead to major ADR. Furthermore, DDI risk increases substantially with age;
patients aged 70-79 years have a 34\% risk of DDI when they are dispensed two
or more drugs concomitantly. Interestingly, a statistical null model
demonstrates that age- and female-specific risks from increased polypharmacy
fail by far to explain the observed DDI risks in those populations, suggesting
unknown social or biological causes. We also provide a network visualization of
drugs and demographic factors that characterize the DDI phenomenon and
demonstrate that accurate DDI prediction can be included in healthcare and
public-health management, to reduce DDI-related ADR and costs
An Architecture for Risk Analysis in Cloud
Cloud computing offers benefits in terms of availability and cost, but it transfers the responsibility of information security management to the cloud service provider. Thus, the consumer looses control over the security of their information and services. This factor has prevented the migration to cloud computing in many businesses. This paper proposes a model where the cloud consumer can perform risk analysis on providers before and after contracting the service. The proposed model establishes the responsibilities of three actors: Consumer, Provider and Security Labs. The inclusion of the Security Labs provides more credibility to risk analysis making the results more consistent for the consumer