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This is Healthbook, Apple's major first step into health & fitness tracking

This is Healthbook, Apple's major first step into health & fitness tracking | Clinical Research & Social Media | Scoop.it
Seven years out from the original iPhone’s introduction, and four years past the iPad’s launch, Apple has found its next market ripe for reinvention: the mobile healthcare and fitness-tracking indu...
Ethical GmbH's insight:

Do you really think that this will not impact Clinical research ...someway ? 

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Lea Vainshtein's curator insight, May 3, 2014 5:52 AM

אפל יוצאת עם אפליקציה חדשה בנושא של בריאות ופעילות גופנית

כך שמידע חיוני יהיה זמין איתנו לכל מקום שנלך

Clinical Research & Social Media
Social Media and Social Network for Drug Research, Clinical Trials & Safety Surveillance.
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Instant and complete access to every historical public Tweet | Twitter Blogs

Instant and complete access to every historical public Tweet | Twitter Blogs | Clinical Research & Social Media | Scoop.it
Gnip is releasing a new Full Archive Search API that will allow customers to immediately search for any Tweet in the entire historical archive of public Twitter data.
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An Evaluation of Risk Factors for Major Adverse Cardiovascular Events During Tocilizumab Therapy - Rao - 2015 - Arthritis & Rheumatology - Wiley Online Library

Cases were adjudicated in a blinded manner by an independent cardiologist with experience serving on MACE adjudication panels, who confirmed definite cases of MACE
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Apple launches new research software programme

Apple launches new research software programme | Clinical Research & Social Media | Scoop.it
Tech firm made the announcement during the promotion of its new smart watch
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Ethical PatientFeels ® New Service first presented at i-net ICT & Life Sciences event: «Bits & Bytes in Life Sciences» 25 March 2015 at the the Technologiepark in Basel - Ethical

Ethical PatientFeels ® New Service first presented at i-net ICT & Life Sciences event: «Bits & Bytes in Life Sciences» 25 March 2015 at the the Technologiepark in Basel - Ethical | Clinical Research & Social Media | Scoop.it
PatientFeels® will be presented at i-net ICT & Life Sciences event: «Bits & Bytes in Life Sciences» 25 March 2015 at the the Technologiepark in Basel.
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Can big data help to make clinical trials more efficient ? The short answer is YES!

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Social media for pharma – an expert’s view

Social media for pharma – an expert’s view | Clinical Research & Social Media | Scoop.it
Even with risks and regulations, pharma needs to engage with patients and learn more about them

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Finding psychological insights through social media - Medical Xpress

Finding psychological insights through social media - Medical Xpress | Clinical Research & Social Media | Scoop.it
Social media has opened up a new digital world for psychology research.
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Patient-sourced drug satisfaction data has its own role to play in healthcare

Patient-sourced drug satisfaction data has its own role to play in healthcare | Clinical Research & Social Media | Scoop.it
San Francisco-based Iodine, the startup from former Wired executive editor Thomas Goetz and former Google engineer Matt Mohebbi that launched last fall, is already starting to see some interesting data come out of its crowdsourced medication reviews.
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Mining Social Media for Healthcare

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E-patient Voices Can Inspire Change in Clinical Trials

E-patient Voices Can Inspire Change in Clinical Trials | Clinical Research & Social Media | Scoop.it
“The culture we will live in next month is a direct result of what people like us share today. The things we share and don't share determine what happens next.”  ~ Seth Godin In a recent post on hi...

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How can health-care providers better leverage social media to improve patient ... - Scope (blog)

How can health-care providers better leverage social media to improve patient ...
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Wearing it well: the potential of wearable technology in healthcare

Wearing it well: the potential of wearable technology in healthcare | Clinical Research & Social Media | Scoop.it
For the pharmaceutical industry, the possibilities presented by wearable technology are clearly enormous
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Survey: 75 percent of patients want digital health services

Survey: 75 percent of patients want digital health services | Clinical Research & Social Media | Scoop.it
According to a survey of thousands of patients in Germany, Singapore, and the United Kingdom, the adoption of digital healthcare services remains low because existing services are either low quality or not meeting patients’ needs.
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Study Shows Wikipedia Rx Drug Pages Often Outdated, Inaccurate - iHealthBeat

Study Shows Wikipedia Rx Drug Pages Often Outdated, Inaccurate - iHealthBeat | Clinical Research & Social Media | Scoop.it
A study detailed in a New England Journal of Medicine Perspective finds that less than half of Wikipedia pages on prescription drugs are updated to reflect FDA safety warnings within two weeks of the agency issuing those communications and that more than one-third of those pages do not reflect the warnings within one year of FDA's notices. HealthDay, NEJM.
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Harnessing the cloud of patient experience: using social media to detect poor quality healthcare

ABSTRACT Recent years have seen increasing interest in patientcentred care and calls to focus on improving the patient experience. At the same time, a growing number of patients are using the internet to describe their experiences of healthcare. We believe the increasing availability of patients’ accounts of their care on blogs, social networks, Twitter and hospital review sites presents an intriguing opportunity to advance the patient-centred care agenda and provide novel quality of care data. We describe this concept as a ‘cloud of patient experience’. In this commentary, we outline the ways in which the collection and aggregation of patients’ descriptions of their experiences on the internet could be used to detect poor clinical care. Over time, such an approach could also identify excellence and allow it to be built on. We suggest using the techniques of natural language processing and sentiment analysis to transform unstructured descriptions of patient experience on the internet into usable measures of healthcare performance. We consider the various sources of information that could be used, the limitations of the approach and discuss whether these new techniques could detect poor performance before conventional measures of healthcare quality.


SOCIAL MEDIA, HEALTHCARE QUALITY AND LEARNING FROM OTHER INDUSTRIES Scandals such as the serious failures in standards of care that came to light at Stafford Hospital in the English National Health Service1 show that a new approach is needed to identify services that are delivering unacceptably poor service. The subsequent enquiry into that hospital found that the problems were mostly discovered through post hoc analysis of mortality, process and patient experience data. The advent of social media and new technology potentially opens a door to insights into care (both positive and negative) unfiltered by traditional methods of healthcare data capture and analysis. For the first time, the voice of the patient may be heard with clarity and immediacy. Patients already post information about the quality of healthcare on the internet, whether on Twitter, blogs, rating websites or other social media. We describe this growing body of information on the internet as a ‘cloud of patient experience’. In a world where sharing experience of life and life-events has brought a new dimension to communication and networking and an inherent intolerance of paternalism and secrecy in governments and institutions that serve the public, we argue that capturing patients’ opinions of their healthcare on the internet in real time could act as an early warning of poor clinical care and over time transform the relationship between care provider and recipients of their services. Traditionally, patients’ experience of hospitals has been measured by annual, often paper based, surveys. Data are available infrequently and costly to collect. Capture, automated analysis and aggregation of social media content could happen on a daily basis, at low cost and could provide a tool for continuous service monitoring. Outside the health sphere, information from social media is being used for a wide variety of analytical and signal detection tasks, sometimes characterised as part of a ‘Big Data’ revolution.2 Recent examples include attempts at predicting election results,3 the next Hollywood blockbuster4 or the closing price of the stock market.5 In healthcare, social media data are already used but, to date, have been largely limited to infectious disease surveillance. The use of Google search activity to detect spikes of flu activity6 is one example and, more recently, Twitter analysis has helped to monitor disease frequency in cholera and other disease outbreaks.7 8 This use of digital information to answer health problems has been called ‘infodemiology’ and ‘infoveillance’. 9 There has been little application to quality and patient safety so far but the potential is much greater given the huge volume of healthcare experiences in settings that remain stable for often decades at a time. More and more people are using the internet as a platform to describe their care in both the USA and UK.10 11 In the USA, the public is increasingly willing to engage with their healthcare online. Of the 85% of adults using the internet,12 48% looked at social networking sites daily,12 34% had read about someone else’s health experience on a website and 15% had consulted online reviews of medical facilities.13 Previous studies have found significant associations between ratings left on websites and clinical outcomes, with better rated hospitals having lower mortality and healthcare associated infection rates.14 15 Early research has demonstrated that sentiment analysis of content in patients’ comments about their care on the internet is feasible.16 17 Sentiment analysis involves taking unstructured, often free-text information, and using software to judge whether the information is broadly positive or negative. Alemi and colleagues have called for real time patient satisfaction surveys using these analyses.16 Cambria and others believe that individual experiences could be ‘crowd validated’ by aggregating various sources of unstructured information from patients online.1


The use of social media data to detect the spike of a definite event such as a disease epidemic has been demonstrated across different contexts and shown to be possible. The use of this source of data to track and interpret the subjective nature of patient experience is a more complex task, and has not yet been explored in detail. However, the growing cloud of patient experience, combined with the promise of sentiment analysis techniques developed outside healthcare, presents an exciting opportunity to understand better the quality of health organisations and systems. The most immediate and feasible application of this approach would be in flagging poor performance. There is a parallel with the use of surveillance systems for infectious diseases to detect an ‘outbreak’ or ‘epidemic’ threshold. The consistent appearance of concerns about a hospital captured through social media, when compared with similar hospitals, could indicate problems that official statistics were not yet picking up or indeed were not capable of even recognising. Of course, as with any quality signal, or trigger tool, there would have to be rigorous protocols for further investigation and action that could distinguish the real from the spurious. HOW TO CAPTURE AND USE THE ‘CLOUD OF PATIENT EXPERIENCE’ To build up this social, or soft, intelligence, two technically different and complex tasks are necessary: harvesting data and then processing it into useful information. The harvesting part involves collecting the free text from as many open sources of comment about healthcare providers as possible: social networks, Twitter, discussion fora and rating websites. Anywhere where people talk about their experience of care online is a potential seam of information to mine. The process would involve identification of appropriate websites, and then pulling relevant information off them on a regular, automated basis using specialised software: an information extraction process known in computer science as ‘scraping’. 19 In the data processing part, the patients’ free text descriptions of their care would be converted into a social intelligence dataset by analysing the collected statements for sentiment and reliability, transforming them into an aggregated, quantitative measure of experience for each provider. This applies algorithmic processes (natural language processing) to extract useful information from the data retrieved. Natural language processing has been used in other patient safety contexts, for example, in the automated detection of postoperative complications in an electronic medical record.20 Key themes searched for might be cleanliness or emotions such as anger, joy or sadness. The resulting data could then be used to rate specific aspects of care at each hospital, such as the hospital environment and the quality of their interactions with staff. This information, taken together with traditional patient surveys, could then be used by health system regulators to identify poor performance, when a certain warning threshold is crossed, and by managers and clinicians to address areas for improvement. LIMITATIONS There are substantial technical and logistic problems in any sensing system. There is potential for selection bias as patients who choose to talk about their care online may not be representative of those attending healthcare facilities. Use of rating websites and Twitter tends to be associated with higher socio-economic status and younger age groups.21 22 Hospitals serving certain populations may receive less attention on social media than others. Some sources of data lend themselves better to automatic processing than others. The comments left on ratings websites, and those posted on patient discussion fora, are often rich in material directly relevant to their healthcare, but tend to appear infrequently. By contrast, Tweets are necessarily brief, containing less contextual information about healthcare and have their own grammar and syntax. These characteristics present real challenges for processing but the growing popularity of Twitter means that it should be seen as an opportunity for healthcare, not a threat. New methods will need to be developed to capture information on healthcare from this source. The autocatalytic quality of some social media, where ideas are repeated on the basis of their popularity, reinforcing views, rather than providing new information, is another trap for the unwary in interpreting findings. We have listed potential data sources and their relative merits and drawbacks in table 1. The analytic component is also a technical challenge: machines struggle to read and understand comments accurately; software finds comments preceded by negatives difficult to interpret. Sarcasm and irony, a feature of the British and US cultures, are almost impossible to process. Even if the sentiment within messages could be collected and interpreted perfectly, it is inevitable that there will be some gaming of the system, involving either inflating a provider’s own service or denigrating a rival’s. There is also a risk that any system like this will throw up false positives. Precautions to prevent wrongful reputational damage will be important. The threshold for an alert may need to be set high initially, or hospitals with sporadic ‘chatter’ about them online may come under the spotlight inappropriately. Experience with methodologies should allow the approach to such matters to be clarified later. Ultimately the challenge will be to pick out signals from the noise.


CONCLUSIONS We doubt that aggregated real time patient feedback would be a perfect test of clinical performance for an organisation. However, considering the lack of engagement with, and the potential inaccuracy of, the current metrics such as standardised mortality ratios, we believe there is a need to explore alternatives. The soft intelligence provided by this proposed approach—capturing and processing the cloud of patient experience—offers another way to look at health quality; and not just clinical quality but areas such as dignity and respect, cleanliness of the care environment, timeliness and efficiency of care, as well as ideas for improvement. At a time where regulatory organisations are stretched and struggling to complete their basic workload,24 the ability to channel the wisdom of patients in real time to create unique insights into the quality and safety of care, without expensive new infrastructure, is appealing. Furthermore, taken in conjunction with measurement of other metrics of patient outcome, it is possible to imagine a national early warning system that would highlight poorly performing hospitals faster than is done at present. Ultimately, this early warning system could become part of a national, real time monitoring tool for hospital performance. Over time, such a system could also pick up positive messages about excellence that could be built on. Social media analytics and Big Data are ideas that have been growing in commercial management in recent years. The quality improvement movement in healthcare has often been at its innovative best when adopting ideas from other industries—be they the safety processes of aviation or the rigour and consistency of manufacturing production lines. Perhaps this field presents another opportunity to borrow and adapt the best ideas from other areas and potentially develop a system to make the current wave of quality and regulatory failures less likely in the future.


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«Social media channels make it possible to learn from the real world» - Blog | i-net

«Social media channels make it possible to learn from the real world» - Blog | i-net | Clinical Research & Social Media | Scoop.it
The pharma industry is searching for approaches beyond pills; big data, social media and an ever increasing computing power are shaping a new innovation landscape. This was reason enough for the i-net technology fields ICT and Life Sciences to jointly organise an event titled «Bits & Bytes in Life Sciences». On 25th March 2015, some …
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Beat Widler (Ethical GmbH) speaks about Big Data & Clinical Trials.

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Can Apple's ResearchKit Really Change Medical Research? | WIRED

Can Apple's ResearchKit Really Change Medical Research? | WIRED | Clinical Research & Social Media | Scoop.it
Apple's ResearchKit aims to solve the data collection problem in medical research. But gathering data isn't the same as understanding it.

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Pacific Cove's curator insight, March 11, 7:50 PM

...apps represent the future of medicine. Apps that motivate people to change their behavior—to eat better and to exercise more, say—may still have a huge impact, Patel says. #HealthCare 

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Preventing Chronic Disease | Social Media in Communicating Health Information: An Analysis of Facebook Groups Related to Hypertension - CDC

We studied Facebook groups related to hypertension to characterize their objectives, subject matter, member sizes, geographical boundaries, level of activity, and user-generated content.
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In-Depth: Anticipating FDA Regulation of Pharmaceutical Apps

In-Depth: Anticipating FDA Regulation of Pharmaceutical Apps | Clinical Research & Social Media | Scoop.it
By Bradley Merrill Thompson Over the last couple years, FDA has clarified the scope of its regulation over mobile health. In the agency’s September 2013 guidance, FDA spelled out its oversight for some of the most common mobile medical apps.
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The Rise Of Digiceuticals – Can You Afford To Not Get Involved? - Life Science Leader Magazine

The Rise Of Digiceuticals – Can You Afford To Not Get Involved? - Life Science Leader Magazine | Clinical Research & Social Media | Scoop.it
When Heather Bell hears the term digiceuticals, she can’t help but think about transformation. “I think that mobile health [the use of...
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Searching social networks to detect adverse reactions

Searching social networks to detect adverse reactions | Clinical Research & Social Media | Scoop.it
Regulators and pharmaceutical companies are monitoring social media posts for potential adverse drug reaction signals.

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gapsos's curator insight, February 3, 2:05 AM
Global Allied Pharmaceuticals (GAP) is one of the supportive care units for cancer patients. GAP has advanced treatment based on immunotherapy and immune oncology for complete treatment. We provided all suitable services to our patients on the basis of their disease condition.http://www.gapsos.com/immuno-oncology.php
Lisa Fernbach's curator insight, February 4, 4:50 PM

ajouter votre aperçu ...

Cosmic Micro System PVT LTD's curator insight, February 19, 4:12 AM

www.cosmicups.net

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Understanding the patient journey with strategic social intelligence

Understanding the patient journey with strategic social intelligence | Clinical Research & Social Media | Scoop.it
The age of patient-centricity and participatory medicine is fully underway; while debate continues as to what exactly patient-centricity constitutes, social media is helping patients play a much more active role in their healthcare than in the...
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Using Twitter to study pharmaceutical drug side effects - iMedicalApps

Using Twitter to study pharmaceutical drug side effects - iMedicalApps | Clinical Research & Social Media | Scoop.it
How twitter is being used to study drug side effects
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"FDA Guidance Limits Flexibility in Social Media Promotional Communications" | JD Supra

Three recently issued draft guidance documents (Draft Guidances) from the U.S. Food and Drug Administration (FDA or Agency) are designed to assist manufacturers in product...
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Survey: 80 percent of smartphone users want to interact with doctors on mobile devices

Survey: 80 percent of smartphone users want to interact with doctors on mobile devices | Clinical Research & Social Media | Scoop.it
Eighty percent of smartphone users are interested in using their smartphones to interact with health care providers, according to a FICO survey of 2,239 adult smartphone users from the UK, Australia, Brazil, China, France, Germany, India, Italy,...
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How reliable is the drug info you find online?

How reliable is the drug info you find online? | Clinical Research & Social Media | Scoop.it
By Saarik Gupta, Special to CNN When people want to learn more about a new drug warning, they turn to the internet -- that’s no surprise. But is the information they find there accurate and up-to-date? Not always, according to a
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