An interesting article was published on Business Insider. I’m not saying it’s technically impossible for an algorithm to become better at making diagnoses than a human, but it certainly should not be the ultimate goal in medicine. This is why I’m writing now my new book, The Guide to the Future of Medicine, to underscore this notion with stories and practical examples.
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:
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);
Whether it affects patients or healthcare professionals;
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.
I hope you will find the guide useful in your work or in preparing your company and colleagues for the future of medicine.
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.
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.
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.
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:
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.
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.
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.
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.