#eHealthPromotion, #SaluteSocial
117.8K views | +2 today
Follow
#eHealthPromotion, #SaluteSocial
E-Health promotion. #web2salute. Health 2.0
Your new post is loading...
Your new post is loading...
Rescooped by Giuseppe Fattori from Digital Disruption in Pharma
Scoop.it!

Big Pharma, Big Data, Big Risks

Big Pharma, Big Data, Big Risks | #eHealthPromotion, #SaluteSocial | Scoop.it

The potential scale of the so-called "Medical Internet of Things" has not been lost on pharmaceutical and tech firms around the world, both big companies hunting growth and smaller ones looking to provide bespoke products and services. 


It has created unlikely alliances. 


Novartis' domestic rival Roche has also teamed up with Qualcomm and Danish diabetes drugmaker Novo Nordisk has partnered with IBM on cloud-linked device projects, for example, while healthcare device maker Medtronic is working with a U.S. data-analytics firm Glooko.


GlaxoSmithKline, meanwhile, is in talks with Qualcomm about a medical technology joint venture potentially worth up to $1 billion, according to people familiar with the matter. 


However, with the opportunity comes risk.


Security experts warn that hacked medical information can be worth more than credit card details on the black market as fraudsters can use it to fake IDs to buy medical equipment or drugs that can be resold, or file bogus insurance claims. 


The U.S. Centers for Disease Control and Prevention estimates there are 35 million U.S. hospital discharges a year, a billion doctor and hospital visits and even more prescriptions, much of which is stored in cloud databases. 


Now the "Medical Internet of Things" is introducing more and more web-connected devices into the equation and pushing even more confidential patient data on to the cloud. 


This is creating potential new opportunities for thieves seeking to penetrate medical companies' security where they may target names, birth dates, policy numbers, billing data and the diagnosis codes needed to obtain drugs, say experts.


"The weakest link tends to be the medical device itself," said Rick Valencia, senior vice president of Qualcomm Life, Qualcomm's four-year-old healthcare unit. "They weren't designed with the idea in mind that they would be going over the network and the information would be residing in cloud infrastructure."


Medtronic, the world's largest standalone medical device maker, said in 2014 it lost patient records in separate cyberattacks at its diabetes business.


Via Pharma Guy
Pharma Guy's curator insight, January 27, 2016 9:54 AM

The U.S. Food and Drug Administration today issued a draft guidance outlining important steps medical device manufacturers should take to continually address cybersecurity risks to keep patients safe and better protect the public health. The draft guidance details the agency’s recommendations for monitoring, identifying and addressing cybersecurity vulnerabilities in medical devices once they have entered the market. The draft guidance is part of the FDA’s ongoing efforts to ensure the safety and effectiveness of medical devices, at all stages in their lifecycle, in the face of potential cyber threats.


For more on that, read: "FDA's Cybersecurity Draft Guidance for Medical Devices"; http://sco.lt/8SkQoT 

Rescooped by Giuseppe Fattori from healthcare technology
Scoop.it!

Can Mobile Technologies and Big Data Improve Health?

Can Mobile Technologies and Big Data Improve Health? | #eHealthPromotion, #SaluteSocial | Scoop.it

After decades as a technological laggard, medicine has entered its data age. Mobile technologies, sensors, genome sequencing, and advances in analytic software now make it possible to capture vast amounts of information about our individual makeup and the environment around us. The sum of this information could transform medicine, turning a field aimed at treating the average patient into one that’s customized to each person while shifting more control and responsibility from doctors to patients.


The question is: can big data make health care better?


“There is a lot of data being gathered. That’s not enough,” says Ed Martin, interim director of the Information Services Unit at the University of California San Francisco School of Medicine. “It’s really about coming up with applications that make data actionable.”


The business opportunity in making sense of that data—potentially $300 billion to $450 billion a year, according to consultants McKinsey & Company—is driving well-established companies like Apple, Qualcomm, and IBM to invest in technologies from data-capturing smartphone apps to billion-dollar analytical systems. It’s feeding the rising enthusiasm for startups as well.


Venture capital firms like Greylock Partners and Kleiner Perkins Caufield & Byers, as well as the corporate venture funds of Google, Samsung, Merck, and others, have invested more than $3 billion in health-care information technology since the beginning of 2013—a rapid acceleration from previous years, according to data from Mercom Capital Group. 


Via nrip
Paul's curator insight, July 24, 2014 12:06 PM

Yes - but bad data/analysis can harm it

Pedro Yiakoumi's curator insight, July 24, 2014 1:48 PM

http://theinnovationenterprise.com/summits/big-data-boston-2014

Vigisys's curator insight, July 27, 2014 4:34 AM

La collecte de données de santé tout azimut, même à l'échelle de big data, et l'analyse de grands sets de données est certainement utile pour formuler des hypothèses de départ qui guideront la recherche. Ou permettront d'optimiser certains processus pour une meilleure efficacité. Mais entre deux, une recherche raisonnée et humaine reste indispensable pour réaliser les "vraies" découvertes. De nombreuses études du passé (bien avant le big data) l'ont démontré...

Rescooped by Giuseppe Fattori from e-Xploration
Scoop.it!

What Will Happen to ‘#BigData’ In Education? | #learning #analytics

What Will Happen to ‘#BigData’ In Education? | #learning #analytics | #eHealthPromotion, #SaluteSocial | Scoop.it
Privacy concerns have put the breaks on many efforts to use "big data" in education. Why are people so skittish of education data when other kinds of digital information are readily accessible?

Via luiy
luiy's curator insight, April 15, 2014 7:50 PM

InBloom’s trajectory has shined a spotlight on the public’s sensitivity around what happens to student data. When it first began as a mammoth ed-tech project in 2011 by the Council of Chief State School Officers, the Bill and Melinda Gates Foundation and the Carnegie Corporation called the Shared Learning Infrastructure, the purpose was to provide open-source software to safely organize, pool, and store student data from multiple states and multiple sources in the cloud. That included everything from demographics to attendance to discipline to grades to the detailed, moment-by-moment, data produced by learning analytics programs like Dreambox and Khan Academy. An API — application programming interface — would allow software developers to connect to that data, creating applications that could, at least in theory, be used by any school in the infrastructure.

Rescooped by Giuseppe Fattori from Pharmaguy's Insights Into Drug Industry News
Scoop.it!

Can Big Data Analytics Help Pharma Deliver "Patient-Centric" Services?

Can Big Data Analytics Help Pharma Deliver "Patient-Centric" Services? | #eHealthPromotion, #SaluteSocial | Scoop.it

The changing economic, regulatory, technological and healthcare environment has given rise to a strategic shift from product and physician-centric strategies to a ‘patient centric’ approach, reflecting how healthcare decision-making has changed in recent years.


In a recent report, Thomson Reuters highlighted that in the pharmaceutical sector, after drug discovery and market knowledge, understanding the patient better is set to be the next big opportunity for big data analytics.


Patients are no longer just passive players in the healthcare system. They are becoming more knowledgeable about their conditions and the medical options available to them, and are taking greater control of their own treatment. This process of empowerment has led to patients developing their own brand and product preferences, and presents pharmaceutical companies with a new audience to cater for. In order to achieve a high level of patient centricity, understanding patients’ needs is fundamental, and this can only be achieved by ‘deep-diving’ into ever-growing amounts of patient data.


The importance of patient centricity

Patient centricity focuses on the understanding of patients’ needs in the context of the state of their condition and experiences within the healthcare system. This means putting the patient at the heart of every business decision in order to develop and provide solutions based on an in-depth, all-round knowledge of the patient.


To implement a truly patient-centric model, it is crucial to understand the complex journey through the healthcare system and explore how patients’ experiences at each stage of this journey can be enhanced. Making this concept a reality is not as hard as it may sound. Every patient interaction generates reams of structured and unstructured data.


With the right combination of big data tools, skills and platforms, pharmaceutical companies can harness this data and generate actionable insights. In turn, these will go a long ways towards identifying patient preferences and formulating future strategies.


Via Pharma Guy
Pharma Guy's curator insight, January 8, 2015 7:04 AM


It is possible to be TOO patient-centric. Let me explain...

Suppose, for example, that a pharmaceutical company has an Rx coupon that reimburses patients for the co-payment made when filling a prescription for their product. This is a common practice. In return, patients provide some personal information -- name, physical address, email address, etc -- when applying for the coupon. With this information -- and permission from the patient -- the pharma company can send the patient notices and further offers via US postal mail or email.

This could be considered patient-centric if it goes above and beyond sending the patient promotional pieces and if social media is brought into the picture.

With the personal information mentioned above, it is possible to find patients on Twitter and Facebook and use technology and Big Data analytics to track their conversations. Patients might even provide their Twitter and Facebook information if asked, making it even easier to track them.


A pharma company may monitor individual patient conversations to determine if a patient is engaging in a lifestyle that counteracts the effect of the company's drug. A Chantix patient, for example, may admit to smoking a cigarette. The pharma company (I won't mention names) could remind the patient -- via private channels such as email, which it collected via the couponing program -- that smoking while on Chantix is not recommended.

Now that would be patient-centric -- maybe TOO patient-centric.


For more on this, read Being Too "Patient-Centric": Spying on Patients on Social Media

Rescooped by Giuseppe Fattori from Digital Data
Scoop.it!

Big Data is the new Artificial Intelligence

Big Data is the new Artificial Intelligence | #eHealthPromotion, #SaluteSocial | Scoop.it

This is the first of a couple columns about a growing trend in Artificial Intelligence (AI) and how it is likely to be integrated in our culture. Computerworld ran an interesting overview article on the subject yesterday that got me thinking not only about where this technology is going but how it is likely to affect us not just as a people. but as individuals. How is AI likely to affect me? The answer is scary.

Robert X. Cringely, 16/04/2014


Via Pierre Tran
Pierre Tran's curator insight, April 18, 2014 12:56 AM

L'intelligence artificielle, telle que conçue dans les années 80 à base d'algorithmes et de puissance informatique, a échoué. Aujourd'hui, les ordinateurs se nourrissent de big data et apprennent par eux-mêmes.

Ceux qui prédisent le futur ont tendance à surestimer le changement à court terme et à sous-estimer celui à long terme. 

Pierre Tran's curator insight, April 18, 2014 12:58 AM

L'intelligence artificielle, telle que conçue dans les années 80 à base d'algorithmes et de puissance informatique, a échoué. Aujourd'hui, les ordinateurs se nourrissent de big data et apprennent par eux-mêmes.

Ceux qui prédisent le futur ont tendance à surestimer le changement à court terme et à sous-estimer celui à long terme. 

Alice Maria Costa's curator insight, April 20, 2014 11:20 AM

Como um afeta AI te?