Privacy Issues with the Electronic Medical Record

Electronic medical records (EMR) all have privacy safeguards in place. Major healthcare institutions have taken steps to prevent employees from looking up information on patients whom they do not treat directly, however numerous potential intrusions into patient privacy are still possible. Centralization of medical records in the increasing number of multi-group practices distributes personal medical data over larger networks and increases the likelihood that personal medical data may be shared or viewed by unauthorized users. This article reviews the benefits of EMRs and the possible mechanisms by which data may be shared without patient knowledge, as well as solutions and safeguards that need to be taken to protect the privacy of patient medical records

Evaluating Workload: A Collaborative Approach between Dean and Department Chair

Faculty workload calculations are complex and an institution’s mission directs the level of faculty participation in each teaching, scholarship and service. The University of Saint Joseph (USJ; West Hartford, Connecticut) transitioned from a college to a university, necessitating reexamination of faculty workload policy. The review was conducted collaboratively between senior administration and key faculty to understand best practices in calculating teaching workload. A review of best practice, evaluation of workload policies at a defined set of peer institutions, and an internal investigation of the types of course offered by USJ faculty was examined

WesScholar Night eating: prevalence and demographic correlates Night Eating: Prevalence and Demographic Correlates

(N ϭ 10,741) . Prevalence estimates were calculated for three commonly used definitions of night eating. Logistic regression was used to examine correlates of night eating: type of day, season, gender, age, race/ethnicity, and BMI or obesity. Results: With few exceptions, findings were similar in the two surveys. Night eating is most common during the weekend; prevalence is greatest among young adults (18 to 30 years of age) and least common among individuals age 65 years or older; and is not associated with BMI or obesity. Gender or ethnicity effects were not found to be stable across surveys. Discussion: Experts need to consider type of day, age group, and possibly gender and race/ethnicity when examining population differences in night eating. Longitudinal studies are needed to further examine the link between night eating and obesity