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Posts from the ‘Data’ Category

The Guide to the Future of Medicine: Download the White Paper with Infographic

Being a medical futurist means I work on bringing disruptive technologies to medicine & healthcare; assisting medical professionals and students in using these in an efficient and secure way; and educating e-patients about how to become equal partners with their caregivers.

Based on what we see in other industries, this is going to be an exploding series of changes and while redesigning healthcare takes a lot of time and efforts, the best we can do is to prepare all stakeholders for what is coming next. That was the reason behind creating The Guide to the Future of Medicine white paper which you can download for free.


Please use the Twitter hashtag #MedicalFuture for giving feedback.

In the white paper, there is an infographic featuring the main trends that shape the future of medicine visualized from 3 perspectives:

  1. Which stage of the delivery of healthcare and the practice of medicine is affected by that (Prevent & Prepare; Data Input & Diagnostics; Therapy & Follow-up; and Outcomes & Consequences);
  2. Whether it affects patients or healthcare professionals;
  3. The practicability of it (already available – green boxes; in progress – orange boxes; and still needs time – red boxes)

Click here to see the infographic in the original size.

Guide to the Future of Medicine Infographic

I hope you will find the guide useful in your work or in preparing your company and colleagues for the future of medicine.

Data in Diabetes

As a physician and genomics researcher, I’m a man of data so I loved to see the approach of Dan Hon regarding type 2 diabetes and the data he acquired every day about himself which helped him get better.

He resolved to do something about it. Being a geek, he decided to measure and quantify the health factors (weight, body fat, activity, blood sugar) that contribute to diabetes. He’s lost 30 lbs since the new year, and has gotten pretty far into reversing his diabetes. He’s detailed his experience with various kinds of monitoring tools, and written a bit of a rant about what needs to be fixed in order to make this easy for anyone with a diabetes diagnosis to follow in his footsteps.

From Watson to Wikis and Virtual Patients

Here are a few articles and news I particularly found interesting this week:

 Haifa, Israel has developed a new clinical decision support tool that correlates a patients’ unique disease profile against various clinical guidelines and a wide range of previously acquired clinical data from a multitude of patients. The tool, called Clinical Genomics (Cli-G), is designed to provide clinicians with actionable results that outline how to address individual patients’ conditions.

Symcat is a versatile and also very powerful tech solution that combines aggregated data from patient health records with user symptoms and demographics to inform diagnoses.

His research has found that a wiki – a website developed collaboratively by a community of users, allowing any user to add and edit content – can be an innovative new tool for developing individual asthma action plans.

  • A medBoardis an online advisory board for pharmaceutical companies to easily get expert advice. Advice that helps develop better medicines and shape commercial strategy.

Researchers at the Institute for Biomedical Imaging and Modelling (INSIGNEO) in Sheffield are developing digital models of different parts of the human body that will ultimately build into a complete digital replica of a patient.

ER Advisor was created by an epidemiologist (Mike Hartmann, BSc, MPH) and a web developer who wanted to help ease the burden on hospitals. Too many people go to the ER when the medical attention they need can be provided elsewhere. We consulted with nurses, doctors and other epidemiologists to come up with an idea: get people to enter their symptoms online and we can suggest whether it is an emergency or not.


Should patients access data of medical devices or softwares?

This is an absolutely timely topic and I’ve just recently come across pretty relevant news and articles focusing on whether patients should get access to source codes and data provided by their implantable devices. A few examples:

Hugo Campos has a small computer buried in his chest to help keep him alive. But he has no idea what it says about his faulty heart.

All the raw data it collects, especially any erratic rhythms it controls with shocks, goes directly to the manufacturer. And some of it later gets sent to his doctor.

Lawyer Karen Sandler’s heart condition means she needs a pacemaker-defibrillator to avoid sudden death, so she has one simple question: what software does it run?

Yet it turns out that it’s impossible for her to see and understand the technology that’s being installed into her own body and upon which her life depends. Regulatory authorities don’t see or review the software either.

My two cents here? They DO have access to any kind of data related to their health. But what do you think?

Hans Rosling Brings Humor to Global Health Statistics

Hans Rosling public health guru and data enthusiast shines again:

The Quantified Self Movement

I’m a big fan of the quantified self movement. As a supporter of the approach of tracking our health-related data and as a scientist who loves working with any kind of data, the Quantified Self is just the perfect project for me. Myself, I use a Striiv.

Recently, I’ve seen a video in which Melanie Swan described Genomic Self-Hacking:

Fenn Lipkowitz talked about his amazing lifelog:

And here is the quantified pregnancy project:

Linked electronic medical records for genomic research

I’ve just come across an interesting study on BMC Medical Genomics. Authors aim at linking electronic medical records and genomic data which is I believe a very promising approach. The Personal Genome Project did something similar but only with 10 participants.

The eMERGE (electronic MEdical Records and GEnomics) Network is an NHGRI-supported consortium of five institutions to explore the utility of DNA repositories coupled to Electronic Medical Record (EMR) systems for advancing discovery in genome science. eMERGE also includes a special emphasis on the ethical, legal and social issues related to these endeavors.

Current progress: The primary site-specific phenotypes for which samples have undergone genome-wide association study (GWAS) genotyping are cataract and HDL, dementia, electrocardiographic QRS duration, peripheral arterial disease, and type 2 diabetes. A GWAS is also being undertaken for resistant hypertension in 2,000 additional samples identified across the network sites, to be added to data available for samples already genotyped.

Results are being posted in dbGaP. Other key eMERGE activities include evaluation of the issues associated with cross-site deployment of common algorithms to identify cases and controls in EMRs, data privacy of genomic and clinically-derived data, developing approaches for large-scale meta-analysis of GWAS data across five sites, and a community consultation and consent initiative at each site. Future activities: Plans are underway to expand the network in diversity of populations and incorporation of GWAS findings into clinical care.

Newistic: Mining Social Media

I’ve recently come across Newistic as I was about to meet the co-founder, Horatiu Mocian, but we couldn’t make it. The service sounds intereting and timely to me.

Newistic offers a customizable web dashboard used for monitoring and analyzing social media for the pharma and healthcare industries. It enables persons or companies interested in the healthcare vertical to get a social media overview for any drug, disease, pharma company, or any other keyword. The features that set Newistic apart from other social media monitoring systems are:

  • Monitoring patient communities
  • Discovering diseases and symptoms that are associated with any search
  • The possibility of searching all or some of the brand names of a generic drug

To demonstrate its real power, here is a recent analysis they performed following a double blow that Roche’s Avastin cancer drug suffered, in the European and US markets, regarding its use for breast cancer. For example, here are the top symptoms and diseases related to Avastin in social media after news hit the media:

If you want to hear more details about the service, let me know and I will schedule an interview with the founders.

200 Healthcare Systems in 4 Minutes

Hans Rosling, director of the Gapminder Foundation, just released another spectacular video featuring 200 years of 200 healthcare system with 12,000 numbers in 4 minutes. Enjoy:

Twitter Diet: The New York Times Story

Here is a recent piece in the New York Times about a reporter who decided to lose weight by 1) getting support from fellow Twitterers, and 2) by tweeting everything he eats throughout the day.

I knew that I could not diet alone; I needed the help of a cheering section. But rather than write a blog, keep a diary or join Weight Watchers, I decided to use Twitter. I thought it would make me more accountable, because I could record everything I ate instantly. And because Twitter posts are automatically pushed to each person who subscribes to them, an audience — of friends or strangers — can follow along.

What is surprising is that Brian Stelter didn’t start using some kind of a data collecting application. I reported about one a few days ago.

On, you can collect your life data through a few simple steps on Twitter. One data point per tweet!

Without using data analytics softwares and sites, it’s still easy to collect your blood sugar or blood pressure levels. FlowingData lets you visualize and analyze data as well.


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