This week’s list of data news highlights covers October 4-10 and includes articles about a Centers for Disease Control effort to use cell phone location data to fight Ebola and the perils of under-representing Africans in genetic research.
The Centers for Medicare and Medicaid Services (CMS) announced this week that it would be overhauling its nursing home rating program, a widely used system that has come under fire in recent years for relying on inaccurate and unaudited data. Under the new program, nursing homes will have to report some of their information using an electronic system that can be remotely audited. The agency hopes the higher-quality data will lead to better health outcomes.
Despite the skyrocketing pace of genetic research, less than 10 percent of genetic data available is from African populations, indicating a dangerous gap in the world’s medical knowledge. This indicates not only is life-saving medical research not targeting African health, but that genetic information available to the global medical community suffers a major data quality problem. In fields like genetics, understanding and being able to analyze genetic diversity is crucial to developing personalized medicines and treatments, but currently medical recommendations are influenced by data collected from primarily U.S. or European populations. Over the next few years, the United Genomes Project hopes to close this knowledge gap by compiling the genomes of 1,000 African people into an openly accessible database.
The National Health Service (NHS) announced that the UK population’s medical data will be housed in a network of regional data centers around the country, known as “accredited safe havens.” These data centers will only provide access to records stripped of personally identifiable information. NHS officials have stated that transparency and clear communication of the benefits associated with information sharing are a key part of their approach to creating the data centers.
The Centers for Disease Control and Prevention (CDC) is tracking approximate cell phone locations in West Africa in hopes of predicting and eventually curbing the spread of Ebola. The effort tracks mobile calls to emergency call centers and then aggregates that information by the cellular tower through which the call was routed. CDC officials hope it will provide a better picture of where cases of the disease are located in real time.
Next year, General Electric (GE) plans to offer its big data analytics platform Predix, which until now had been used only in GE devices, to other manufacturers. The platform, which has laid the foundation for the company’s successful Internet of Things efforts, will count Cisco as one of its first customers. GE is also making deals with wireless providers to ensure that devices equipped with the analytics can link up to local networks easily.
The Phoenix Children’s Hospital in Arizona will soon house a supercomputer capable of sequencing and analyzing patient genomes in just seven days. The supercomputer, funded by billionaire doctor Patrick Soon-Shiong, will provide doctors with the necessary information to develop life-saving personalized treatments and build a database of children’s genomes to aid medical research. Applying massive computing power to understanding genetic data is a valuable resource to medical researchers, as their ability to develop treatments is contingent on their ability to quickly sequence and analyze patient genomes.
U.S. Customs and Border Protection is exploring the possibility of equipping its canine team with sensor-laden collars to track the animals’ stress levels. Officials say sensors that can transmit this information in real-time will help handlers identify dangerous situations as quickly as possible. Some of the agency’s dogs are already equipped with GPS trackers, and this could expand to audio and video recording equipment in the future.
A research team from Northwestern University is relying on data analytics to improve course design, medical response, safety, and security issues at the Chicago Marathon, which attracts 45,000 runners and nearly two million spectators each year. Utilizing a visual dashboard, researchers can monitor and analyze data from a variety of sources including the race’s medical tents and the city’s public safety information systems. Professor George Chiampas, medical director of the Chicago Marathon, hopes that using cutting edge technology to inform public safety decisions will raise the bar for other major public events.
Researchers at the Massachusetts Institute of Technology have demonstrated an algorithm that can accurately predict the crime rate of an area using Google Street View data. The project, which used machine learning to identify important features in 8 million images, can also accurately predict the distance to the nearest McDonald’s restaurant. The researchers hope their work will one day be useful to urban planners, who might be able to help cities more efficiently provision public services by pinpointing areas of greatest need.
Data collected through the popular GPS-powered workout app Strava is being used by the Oregon Department of Transportation (ODOT) to better understand the infrastructure needs involved in making bikers safer. Strava provided ODOT with a data set of 17,700 riders and 400,000 bike trips in Portland last year alone, and now ODOT is analyzing this data to see how it can protect the cities bikers. Portland previously collected information on cyclists in a relatively primitive fashion, relying on volunteers to count cyclists at certain intersections. Analysis of Strava’s data by ODOT could mean safer roads for commuters.
Photo: Flickr user Steve Conger