Category Archives: Healthcare Industry

Posts about the healthcare industry.

MeaningCloud Sponsors PharmaForce 2017

PharmaForce 2017

MeaningCloud sponsors PharmaForce 2017

At MeaningCloud, we are proud to sponsor the PharmaForce 2017 Conference. PharmaForce is an interactive conference for marketing and sales leaders from pharmaceutical companies to be held on September 18-20, 2017, in Austin, TX.

PharmaForce is the event for Pharma commercial innovators.

Who should attend:

  • Marketing:
    Consumer/HCP/Payer Marketing, Managed Markets, Marketing, Social Media Strategist, Commercial Marketing, Multichannel Marketing, Digital Marketing/Digital Strategy
  • Sales:
    Field Force/Sales Force Effectiveness, Sales Training & Development, Commercial/Sales Operations, Field/Regional/Account Manager, Market Access
  • Brand & Commercial Strategy:
    Commercial Innovation, Brand Management/Strategy, Brand Marketing, Disease, Drug, and Therapy Area Heads

Now in its 11th year, PharmaForce is the only life sciences event that addresses both marketing and sales strategies to achieve commercial success.

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Voice of the Patient Analysis in Forums

Voice of the Patient Analysis

In a previous post (Listening to the Voice of the Patient), we made an account of ongoing initiatives by public administration, hospitals and pharma companies intended to listen, understand and engage patients in the whole healthcare system. We also provided evidence that forums are a paramount source of information when talking about the Voice of the Patient Analysis.

As it was already shown, the Voice of the Patient (VoP) can be analyzed from multiple perspectives. In this post, we cover the point of view of the Pharma Industry.

Pharma Market Intelligence - Voice of the Patient

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Listening to the Voice of the Patient

Voice of the Patient and Patient-Centered Health Care

National Library of Medicine

The modern definition of “patient centered health care” was stated in the National Library of Medicine’s MED-LINE subject heading (MeSH), introduced in 1995, which reads, “Design of patient care wherein institutional resources and personnel are organized around patients rather than around specialized departments.”

Following this design criterion, patients’ safety and well-being are the priority for all the agents involved in this industry: caregivers, pharmaceutical companies, medical device manufacturers, health insurers, and government agencies. And, being the center of our health systems, listening and engaging patients becomes the cornerstone of any quality improvement initiative. That’s why the so called “Voice of the Patient” is getting an increasing attention by all the stakeholders involved.

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Real World Evidence Definition

Real World Evidence Definition

Real World Evidence is information on health care that is derived from multiple sources outside typical clinical research settings, including electronic health records (EHRs), claims and billing data, product and disease registries, and data gathered through personal devices and health applications.

The most quoted definition of Real World Data comes from the area of pharmacoeconomics. The ISPOR (International Society for Pharmacoeconomics and Outcomes Research) defines Real World Data as:

“Data used for decision making that are not collected in conventional randomized controlled trials (RCTs)”

Other definitions of Real World Data, Real World Evidence and Evidence from Clinical Experience can be found in the following figure, taken from a working paper of the Margolis Center for Health Policy, Duke University (see References below).

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MeaningCloud Sponsors the Real World Evidence Forum 2017

Real World Evidence Forum

Real-World Evidence Forum

Real-World Evidence Forum Philadelphia, July 17-18

At MeaningCloud, we are proud to sponsor the Real World Evidence Forum. The RWE Forum, taking place on July 17-18, 2017 in Philadelphia, will bring together clinical health professionals to address:

  • How to operationalize the process of collecting real-world data.
  • How to utilize real-world evidence to demonstrate both the clinical effectiveness and cost-effectiveness of drugs.

Attendees will gain a better understanding of how electronic data sources are changing the way real-world data is being collected. This conference will offer attendees insight into how real-world evidence will help decrease costs, define innovative outcomes and minimize the number of patients exposed to potentially harmful medications.

Text Analytics and Real World Evidence

MeaningCloud, as a Text Analytics provider, has evolved a highly specialized offering for the Health and Pharma industries. We count among our clients some the largest companies in the Pharmaceutical industry.

Join us in Philadelphia. If you are interested in attending the Real World Evidence Forum next July 17-18, just drop us a line to info@meaningcloud.com. We have a surprise for you!

Stay tuned to access our presentation at the conference, that we will publish on this blog. In the meanwhile, if you are curious about how our technology works in the health area, just take a look at our Text Analytics Health Demo.

Looking forward to seeing you at the Real-World Evidence Forum!

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New health demo: tagging drug names, symptoms, diseases, and adverse drug reactions

Documents in the health domain show specific vocabulary and linguistic structure. If you take a look at clinical Records or Electronic Health Records (EHR), you will see that it is also made up of unstructured data (that is, free text). This free text contains weird names of drugs and diseases that are even difficult to read. For all these reasons, text analytics techniques must be adapted to the health domain.

We have put together a number of resources in a demo that shows how MeaningCloud can tag drug names, symptoms, diseases, procedures, and so on.

See the free demo: https://www.meaningcloud.com/demos/health-text-analytics-demo

Health text tagging demo picture

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What is Real World Evidence and why does it matter?

Real World Evidence. Blurred image of a hospital

Real World Evidence (AKA “Real World Data”) is a worldwide trend in Health and Life Sciences. New kinds of data, such as electronic health records and data mining tools are now available and allow us to extract information and knowledge. We can detect medical treatment costs, treatment efficiency (cost, benefits, and risks), references to drugs, side effects, or long-term results.  Text analytics is an essential component of this area of knowledge.

Austerity measures and related price cuts have put unprecedented pressure on the pharmaceutical industry. Manufacturers are being asked to provide information related not only to safety, appropriate use, and effectiveness but also to clinical and economic value. Although randomized clinical trials (RCTs) remain the gold standard of clinical tests, factors such as varying responses to a drug in real life, not completing the course of prescriptions, or using unauthorized medication before or during the trial limit the generalizability of results from randomized clinical trials.
Real World Evidence (also called “Real World Data”)  has been fueled by new data technologies that leverage the valuable information contained in electronic medical records and personal information repositories. This post is a review of those Real World Evidence sources and of the benefits that Pharmaceutical and Life Science companies can derive from them.

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Could Antidepressants Be the Cause of Birth Defects?

We agree that it is not typical at all for an Information Technology company to talk about antidepressants and pregnancy in its own blog. But here at MeaningCloud we have realized that health issues have a great impact on social networks, and the companies from that industry, including pharmas, should try to understand the conversation which arises around them. How? Through text analysis technology, as discussed below.

Looking at the data collected by our prototype for monitoring health issues in social media, we were surprised by the sudden increase in mentions of the term ‘pregnancy’ on July 10. In order to understand the reason of this fact, we analyzed the tweets related to pregnancy and childbearing. It turned out that the same day a piece of news on a study issued by the British Medical Journal about the harmful effects that antidepressants can have on the fetus had been published.
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Exploring Social Media for Healthcare Data

People enjoy sharing information through social media, including healthcare data. Yeah, it is true! And it constitutes the starting point of the research work titled ‘Exploring Spanish health social media for detecting drug effects’, which aims at following social media conversations to identify how people talk about their relation with drug consumption. This allows identifying possible adverse effects previously unknown related to these drugs. Although there is a protocol to communicate to the authorities the identification of a drug adverse effect, only a 5 – 20% of them are reported. Besides, conversations around drugs, symptoms, conditions and diseases can be analyzed to learn more about them. For example, it is possible to see how people search for specific drugs using social media, while others sell them, perhaps illegally. Many others talk about mixing alcohol with drugs or other illegal substances. Of course, one cannot believe everything that appears on the Internet this is another issue—, but it can highlight some hypothesis for further research.

drugs

Some researchers from the Advanced Databases Group at Carlos III University of Madrid have carried out the mentioned study, designing hybrid models to capture the needed knowledge to identify adverse effects. The Natural Language Processing platform which supports the implementation of the analysis process based on such models is MeaningCloud. The customization capabilities provided by the platform have been decisive to include specific vocabulary and medical domain knowledge. As we know, the names of drugs and symptoms might be complex and, in some cases, difficult to write properly. The algorithm’s results are promising, with a 10% increase in recall when compared to other known algorithms. You can find further details in the scientific paper published by the BMC Medical Informatics and Decision Making Journal.

These developments have been part of the TrendMiner project, and are now available in the prototype website TrendMiner Health Analytics Dashboard, which shows people’s comments about antidepressants gathered from social media. The console displays the mentions of antidepressants and related symptoms and, by clicking on any of them, their evolution over time. Moreover, the source texts analyzed to compute those mentions are shown at the bottom, with labels highlighting the names of drugs, symptoms or diseases, and any relations among them. Such relations might say if a drug is indicated for a symptom or if a disease is an adverse effect of the mentioned drug. The prototype also allows searching by the ATC code (Anatomical Therapeutic Chemical Classification System) and the corresponding level according to this classification scheme. So, if you mark the ‘By Active Substance’ selector, you are searching any drug containing the active substance of the product you inserted in the search box. Furthermore, the predictive search functionality makes easier to find the right expression for a drug or disease. Please, have a look at the prototype and tell us what you think about it. If you find a chart useful, you can even tweet it from there! Any comment is more than welcome.