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How Precision Medicine Can Save More Lives and Waste Less Money (Part 1 of 2)

Posted on August 9, 2016 I Written By

Andy Oram is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. An employee of the company since 1992, Andy currently specializes in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. His articles have appeared often on EMR & EHR and other blogs in the health IT space. Andy also writes often for O'Reilly's Radar site (http://oreilly.com/) and other publications on policy issues related to the Internet and on trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business. Conferences where he has presented talks include O'Reilly's Open Source Convention, FISL (Brazil), FOSDEM, and DebConf.

We all have by now seen the hype around the Obama Administration’s high-profile Precision Medicine Initiative and the related Cancer Moonshot, both of which plan to cull behavioral and genomic data on huge numbers of people in a secure manner for health research. Major companies have rushed to take advantage of the funds and spotlight what these initiatives offer. I think they’re a good idea so long as they focus on behavioral and environmental factors. (Scandalously, the Moonshot avoids environmental factors, which are probably the strongest contributors to cancer) . What I see is an unadvised over-emphasis on the genetic aspect of health analytics. This can be seen in announcements health IT vendors, incubators, and the trade press.

I can see why the big analytics firms are excited about increasing the health care field’s reliance on genomics: that’s where the big bucks are. Sequencing (especially full sequencing) is still expensive, despite dramatic cost reductions over the past decade. And after sequencing, analysis requires highly specialized expertise that relatively few firms possess. I wouldn’t say that genomics is the F-35 of health care, but is definitely an expensive path to our ultimate goals: reducing the incidence of disease and improving life quality.

Genomics offer incredible promise, but we’re still waiting to see just how it will help us. The problems that testing turns up, such as Huntington’s, usually lack solutions. One study states, “Despite the success of genome-wide association and whole-exome and whole-genome sequencing (WES/WGS) studies in revealing the DNA variants that underlie the genetic basis of disease, the development of effective treatments for most diseases has remained a challenge.” Another says, “Despite much progress in defining the genetic basis of asthma and atopy [predisposition to getting asthma] in the last decade, further research is required.”

When we think about the value of knowing a gene or a genetic deviation, we are asking: “How much does this help predict the likelihood that I’ll get the disease, or that a particular treatment will work on me?” The most impressive “yes” is probably in this regard to the famous BRCA1 and BRCA2 genes. If you are unlucky enough to have certain mutations of these gene, you have a 70% lifetime risk for developing breast or ovarian cancer. This is why testing for the gene is so popular (as well as contentious from an intellectual property standpoint), and why so may women act on the results.

However–this is my key point–only a small percentage of women who get these cancers have these genetic mutations. Most are not helped by testing for the genes, and a negative result on such a test gives them only a slight extra feeling of relief that they might not get cancer. Still, because the incidence of cancer is so high among the unfortunate women with the mutations, testing is worthwhile. Most of the time, though, testing is not worth much, because the genetic component of the disease is small in relation to lifestyle choices, environmental factors, or other things we might know nothing about.

So, although it’s hard enough already to say with any assurance that a particular gene or combination of genes is associated with a disease, it’s even harder to say that testing will make a big difference. Maybe, as with breast or ovarian cancer, a lot of people will get the disease for reasons unrelated to the gene.

In short, several factors go into determining the value of testing: how often a positive test guarantees a result, how often a negative test guarantees a result, how common the disease is, and more. Is there some way to wrap all these factors up into a single number? Yes, there is: it’s called the odds ratio. The higher an odds ratio, the more helpful (using all the criteria I mentioned) an association is between gene and disease, or gene and treatment. For instance, one study found that certain genes have a significant association with asthma. But the odds ratios were modest: 3.203 and 5.328. One would want something an order of magnitude higher to show running a test for the genes would have a really strong value.

This reality check can explain why doctors don’t tend to recommend genetic testing. Many sense that the tests can’t help or aren’t good at predicting most things.

The next section of this article will turn to behavioral and environmental factors.

How Tech Companies are Changing Our Healthcare Infographic

Posted on January 19, 2016 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

UIC’s Masters in Health Informatics has put out a great infographic that looks at how tech companies are changing our healthcare system. However, what struck me most about the infographic was that it focuses on how medicine is going to become (some might say becoming) far more personalized. I’ve always been struck by the fact that many of the advancements in healthcare that we dream about are only possible through the use of technology. Many of the personalize medicine initiatives aren’t even in the realm of thinking in a paper world. That’s a powerful idea.

I’m sure that many out there might read this and argue that the addition of computers is causing a de-personalization of health care. I’d argue that it all depends on how the tech is implemented. In many cases today, healthcare technology has de-personalized the care that’s provided. However, that doesn’t have to be the case. Technology should be a tool that makes the care a doctor provides extremely personalized. That’s true from a data and patient-physician interaction perspective.

Take a look at the infographic and be sure to share your thoughts in the comments:
How Tech Companies are Changing our Healthcare Infographic

EHR Helps Researchers Find Genetic Connections To Disease

Posted on December 5, 2013 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

A group of researchers have completed a study which found new links between patients’ genetic profile and specific diseases by mining EMR data, reports a story in iHealthBeat.

The research, which was conducted by the Electronic Medical Records and Genomics Network, a consortium of medical research institutions including the Mayo Clinic and Vanderbilt University School of Medicine, analyzed data from about 13,000 of EMRs.

The participants then grouped about 15,000 billing codes contained in the EMRs into 1,600 disease categories. Next, they looked for links to diseases in EMRs which contained DNA data.

The researchers, whose study was published in the journal Nature Biotechnology, found  63 new genetic links to diseases, ranging from skin cancer to anemia, iHealthBeat said.

The EMR study method, which is known as a phenome-wide association study, is a departure from the 13-year old genome-wide association model, which has been used to search for common mutations in the DNA of patients of people with the same diseases.

Co-author Joshua Denny, a biomedical informatics researcher at Vanderbilt, says that the newer method can help link seemingly unrelated symptoms, detect potentially harmful side effects of a drug, and help find new uses for drugs.

This is just the tip of the iceberg where translation medicine and EMRs are concerned. Using EMRs to conduct genomic research is becoming an increasingly popular exercise, cutting across a wide range of clinical disciplines.

And it’s not just institutional academic research houses getting into the act. For example, this summer a large northern Virginia hospital announced that it had struck a deal with a Massachusetts analytics firm to see if data mined from EMRs can better predict the risk of preterm live birth.

Now, genomics research is not for just any hospital — it’s obviously a major undertaking — but I think it’s likely more hospitals will get into the game. By this time next year I think there will be a crop of interesting new genomics projects mining EMRs. Although, it will be interesting to see how the 23andMe FDA battle impacts this as well.

Will an EMR’s Quality Metrics Differentiate it from Other EMRs?

Posted on April 11, 2013 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

In the emerging consumer-centered, value-driven U.S. healthcare marketplace, the EHR vendors that survive and thrive will need to differentiate their brand by successfully competing on the value (quality/price) their product actually delivers to its end users.

Bob Coi, MD

This is a fascinating look at EMRs and future differentiation in the EHR market. There’s little doubt we could use some EMR differentiation with so many EMR companies still out there. I’m just not sure that the quality of care that an EMR provides is going to be why a doctor selects one EMR over another EMR.

Every doctor I know wants to provide great care to their patients. Every patient I know wants to go to the doctor who provides them the best care. The problem is that most doctors don’t see a direct correlation between EMR use and the quality of care given. Patients don’t either, and the other challenge is that patients have no way to measure the quality of care they’re given anyway. The closest we come to knowing if the doctor provided quality care is that as a patient I know I’m sick and then I get better. I guess if I got better, then the doctor must have provided me quality care.

With this said, I think there’s the possibility that an EMR discovers a way to clearly show that something they do improves the care of the patient. The incremental document management and simple alert notifications that we see from EMR’s today won’t show that clear improvement in care.

No, we have to think much bigger to clearly show that the care provided was better because of the EMR and that the improved care wouldn’t have been possible without the EMR. An example of this would be integrating genomic data into the care provided. What if genomic data influenced which drugs you prescribed so that the drug was perfectly tailored to the patient? This is a great example where it would literally improve the care you provide a patient and it would be impossible without the technology to do the analysis. Assuming this technology was integrated with the EMR, it would be impossible for doctors not to use the EMR.

This is just one example. I’m sure creative entrepreneurs will come up with many more. Showing that EMR improves quality of care is a really high barrier. Plus, changing physicians perceptions on EMR is going to be really hard even if an EMR system does indeed improve the quality of care. Some company will do it and then Dr. Coi will be right that an EMR’s quality metrics will differentiate it from other EMR companies.

The “Smart EMR” Differentiator

Posted on October 25, 2011 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

As I’ve been able to talk to more and more EMR companies I’ve been trying to figure out a way to differentiate the various EHR software. In fact, when I meet with EHR software companies I suggest that instead of them showing me a full demo of their EHR software, I ask them to show me the feature(s) that set their EHR apart from the other 300+ EHR companies out there. I must admit that it’s always interesting to see what they show me. Sometimes because what they show me isn’t that interesting or different. Many of my EMR company specific posts come from these experiences.

Today at MGMA as I went from one EHR company to another I started to get an idea for what might be the future differentiation between EHR companies. I’m calling it: “Smart EMR.”

You can be sure that I’ll be writing about my thoughts on Smart EMR software many more times in the future. However, the basic idea is that far too many EHR software are just basic translations from paper to electronic. Sure, some of them do a pretty good job of capturing the data in granular data elements (something not possible on paper), but that’s far from my idea of what a future Smart EMR software will need to accomplish.

I’m sure that many of those that are reading this post immediately started to think about the idea of clinical decision support. Certainly clinical decision support will be one important element of a Smart EMR, but I think that’s barely even the beginning of how a Smart EMR will need to work in the future. However, clinical decision support as it’s been described to date focuses far too much on how a clinician’s discretely entered data elements can support the care they provide. That’s far too narrow of a view of how an EMR will improve the patient-doctor interaction.

Without going into all the detail, EHR software is going to have to learn to accept and process a number of interesting and external data sources. One example could be all the data that a patient has in the PHR. Another could be patient data that was collected using personal various medical devices like a blood pressure cuff, an EKG, and blood glucose meters. Not to mention more consumer centric data devices and apps such as RunKeeper, Fitbit, sleep tracking, mood tracking, etc etc etc.

Another example of an external source could be access to some community health data repository. Why shouldn’t community trends in healthcare be part of the patient care process? None of this is far reaching since we’re collecting this data today and it will become more and more mainstream over time. Something we can’t do today, but likely will in the future is things like genomics. Imagine how personalized healthcare will change when an EHR will need to know and be able to process your genome in order to provide proper care.

I don’t claim to know all the sources, but I think that gives you a flavor of what a Smart EMR will have to process in the future. I’ll be interested to see which EHR software companies see this change and are able to execute on it. Many of the current innovations in EHR have been pretty academic. The Smart EMR I describe above will be much more complicated and require some specific skills and resources to do it right.