18 février

Think you’ve got a handle on the Internet of Things? Feeling positive about population health management? Got big data in the bag? Good! The healthcare industry is constantly changing, and new technologies, tools, strategies, and initiatives are popping up at a breakneck pace.  You’ve read through our first primer on the most common terms and phrases you’re likely to hear if you spend any time in the big data analytics universe.  Now it’s time to tackle a few...

Big data is in the ascendant in medicine. On this point, there is agreement among industry players and observers. We have increasingly powerful hardware and software, which make it possible to analyse the increasing amounts of data we are getting from billing and treatment records, test results, and most recently, from fitness trackers. For the most part, this data is already in digital form. However, the challenge is not merely to describe this state of affairs; it is to answer the question...

Rachel Emma Silverman reports in The Wall Street Journal, “Employee wellness firms and insurers are working with companies to mine data about the prescription drugs workers use, how they shop and even whether they vote, to predict their individual health needs and recommend treatments...

Truven Health Analytics CEO Mike Boswood, left, and IBM Watson Health General Manager Deborah DiSanzo, as IBM announces plans to acquire Truven for $2.6 billion. IBM Watson Health has fired the latest shot in a budding healthcare Big Data arms race. Big Blue announced Thursday that it would acquire Ann Arbor, Mich.-based Truven Health Analytics for an attention-getting $2.6 billion.  

La nouvelle fait le tour de la presse spécialisée autant que des grands quotidiens, un hôpital de Los Angeles vient de subir une attaque de la part de hackers, qui réclamaient plus de 3M de dollars pour débloquer le SI. Au final, l'établissement affirme avoir déboursé 17 000 dollars pour remettre le SI en services.

More than half of hospital deaths in the United States are related to severe infections, or sepsis. Yale researchers developed a prediction model, drawing on "big data" about local patients and using machine-learning methods, that proved better at identifying at-risk patients than existing clinical practices.

17 février

Employee wellness firms and insurers are working with companies to mine data about the prescription drugs workers use, how they shop and even whether they vote, to predict their individual health needs and recommend treatments. Trying to stem rising health-care costs, some companies, including retailer Wal-Mart Stores Inc., WMT 0.74 % are paying firms like Castlight Healthcare Inc. to collect and crunch employee data to identify, for example, which workers are at risk for diabetes, and target...

C'est l'histoire, encourageante, d'une débâcle, devenue une réussite éclatante grâce au travail de quelques hommes de bonne volonté. "Nous étions nuls, nous sommes devenus excellents !", résume sans ambages Pierre Champsaur, qui vient de...

16 février

La loi adoptée le 17 décembre 2015 au terme d’un long processus représente pour les hébergeurs de données de santé (HDS) une avancée significative, devant leur permettre d’assumer mieux, avec plus de réactivité et de lisibilité leurs missions de protection des données personnelles qui leur sont confiées et de support des pratiques coopératives de soins. Toutefois, ce texte dense et éclectique ne pouvait aller dans un niveau de détail suffisant pour comprendre le cadre exact dans lequel...

During Australian Healthcare Week on March 15-17, I will be delivering two keynotes on the future of healthcare, at the Health Facilities Design & Development conference and the Healthcare Efficiency Through Technology conference. In the lead-up to the conference, an article Healthcare 2020: what will the future of healthcare look like in Australia? draws on an interview with me to explore this space. Below are just a few excerpted quotes from the extensive interview with me: On big data...

Every healthcare stakeholder agrees that it’s time for clinical data to get up and running. But just because everyone’s behind an effort certainly doesn’t make it easier. Clinical analytics, at this stage in its evolution, is really a race against time. For provider organizations, the future of value-based care came much faster than expected: Medicare recently announced an ambitious timeline for transitioning to value- and risk-based reimbursement models, and state governments and private...

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