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Researchers simulate privacy leaks in functional genomics studies

Credit: CC0 Public Domain

The functional genomics field, which looks at the activities of the genome and levels of gene expression rather than particular gene mutations, generally relies on aggregating information from many samples for its statistical power. This means that broadly sharing raw data is vital; however, sharing these data currently is challenging because of the privacy concerns of individuals within those datasets, leading to these data being largely inaccessible behind firewalls. In a study publishing November 12 in the journal Cell, a team of investigators demonstrates that it’s possible to de-identify those data to ensure patient privacy. They also demonstrate how these raw data could be linked back to specific individuals through their gene variants by something as simple as an abandoned coffee cup if these sanitation measures are not put in place.

“The purpose of this study is to come up with practical ways to broadly share the without creating undue concerns,” says senior author Mark Gerstein, a professor of bioinformatics at Yale University.

Functional genomics research is frequently tied to a specific disease. For example, an investigation into a particular psychiatric condition might look at the expression of certain genes in a type of neuron. And, by nature of having their included in such a study, an individual’s medical status with regard to that condition could inadvertently be revealed.

This can happen through what’s known as a quasi-identifier. The way a quasi-identifier works is that if someone has enough individual data points about you, even if those data on their own are not sensitive or unique, they can be combined to create an identifier that is unique to you. In a non-genetic setting, this means if someone has your zip code, birthday, the model of car you drive, and other

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Healthcare – Safe Patient Handling

Safe Patient Handling

One major source of injury to healthcare workers is musculoskeletal disorders (MSDs). In 2017, nursing assistants had the second highest number of cases of MSDs. There were 18,090 days away from work cases, which equates to an incidence rate (IR) of 166.3 per 10,000 workers, more than five times the average for all industries. This compares to the all-worker days-away from work rate of 30.5 per 10,000 workers.

These injuries are due in large part to overexertion related to repeated manual patient handling activities, often involving heavy manual lifting associated with transferring, and repositioning patients and working in extremely awkward postures. Some examples of patient handling tasks that may be identified as high-risk include: transferring from toilet to chair, transferring from chair to bed, transferring from bathtub to chair, repositioning from side to side in bed, lifting a patient in bed, repositioning a patient in chair, or making a bed with a patient in it.

Sprains and strains are the most often reported nature of injuries, and the shoulders and low back are the most affected body parts. The problem of lifting patients is compounded by the increasing weight of patients to be lifted due to the obesity epidemic in the United States and the rapidly increasing number of older people who require assistance with the activities of daily living.

The consequences of work-related musculoskeletal injuries among nurses are substantial. Along with higher employer costs due to medical expenses, disability compensation, and litigation, nurse injuries also are costly in terms of chronic pain and functional disability, absenteeism, and turnover. As many as 20% of nurses who leave direct patient care positions do so because of risks associated with the work. Direct and indirect costs associated with only back injuries in the healthcare industry are estimated to be