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Doctors, Data, Diagnoses, and Discussions: Achieving Successful and Sustainable Personalized/Precision Medicine

Posted on January 10, 2018 I Written By

The following is a guest blog post by Drew Furst, M.D., Vice President Clinical Consultants at Elsevier Clinical Solutions.

Personalized/precision medicine is a growing field and that trend shows no sign of slowing down.

In fact, a 2016 Grand View Research report estimated the global personalized medicine market was worth $1,007.88 billion in 2014, with projected growth to reach $2,452.50 billion by 2022.

As these areas of medicine become more commonplace, understanding the interactions between biological factors with a range of personal, environmental and social impacts on health is a vital step towards achieving sustainable success.

A better understanding begins with answering important questions such as whether the focus should be precision population medicine (based on disease) or precision patient-specific medicine (based on the individual).

Specificity in terminology is needed. The traditional term of “personalized medicine” has evolved into the term “precision medicine,” but this new usage requires a more detailed look into the precise science of genetic, environmental and lifestyle factors that influence any approach to treatment.

Comprehending the interactions between biological factors with a range of personal, environmental, and social impacts on health can provide insights into success and we’ve learned that some areas of precision medicine are more effective than others.

Through pharmacogenomics – the study of understanding how a patient’s genetic make-up affects the response to a particular drug – we have identified key enzymes in cancer formation and cancer treatment, which aids in the customization of drugs.

Research shows us that drug-metabolizing enzyme activity is one of many factors that impact a patient’s response to medication. We also know that human cytochrome P450 (CYP) plays an important role in the metabolism of drugs and environmental chemicals.

Therapies that incorporate drug-specific pharmacogenomics are a boon to oncology treatments and a vast improvement over the “shotgun therapy” approach of the past. Today, treatments can be targeted to enzymes and receptors that vary from person to person.

In traditional chemotherapy, a drug developed to kill rapidly growing cancer cells will indiscriminately target other rapidly growing cells such as hair cells, hence the often-observed hair loss. However, a targeted drug and delivery method aimed at only the receptive cells can be a much more effective approach and treatment, while minimizing collateral damage.

Recently, the journal Nature published a study showing the promise this method holds.  In the pilot study, scientists led by Dr. Catherine Wu of Dana-Farber Cancer Institute in Boston gave six melanoma patients an experimental, custom-made vaccine and, two years later, all were tumor-free following treatment.

Looking Beyond Genetics

Precision medicine needs to include more than just genetics.

Factors such as environment and socio-economic status also must be included when approaching disease states and we must undertake a comprehensive overview of a patient’s situation, including, but not limited to, family history.

Cultural dietary traditions can play into disease susceptibility. As an example, the frequent consumption of smoked fish in some Asian cultures increases their risk of gastric (stomach) cancers. Lower socioeconomic status can force acceptance of substandard and overcrowded housing with increased risk of illness ranging from lead toxicity, asbestosis, and Hantavirus to name a just a few.

A patient with a genetic propensity for lung cancer who also smokes cigarettes and has high radon levels in their home is increasing the odds of developing disease due to these combined genetic, behavioral, and environmental factors.

Patient-derived Data and the Diagnosis

In addition to the information now available through state-of-the-art medical testing, patient-derived information from wearables, biometrics, and direct-to-consumer health testing kits, presents patients and physicians alike with new opportunities and challenges.

Armed with newly discovered health data, patients may present it to their doctors with a request that it be included in their health record. Many patients expect an interpretation of that data when they visit their doctor and an explanation of what it means for their present (and future) healthcare.

Doctors can be overwhelmed when unfiltered information is thrown at them. Doctors are not prepared and research has yet to offer definitive support for interpretation of patient-derived data.

Studying hereditary traits can offer some insights from generation to generation. By delving into genomics of individual patients, we get a clearer picture into a person’s risk factor for a certain disease, but often this information provides no immediate solutions. Discovering a genetic indicator for Alzheimer’s, may reflect a higher propensity for the disease, but symptoms may be decades away, if they appear at all.

Pitfalls and Possibilities

There are many concerns about genomic data collection, one of which is whether policies can keep pace with patient privacy and the related ethical questions that inevitably ensue. These questions are consistently surfacing and there is no clear direction on the best course of action.

Clearer policies are needed to delineate who has access to a patient’s genetic records and whether third parties, such as health or life insurance companies, can deny coverage or care based on genomics.

In addition, one cannot ignore the psychological burden associated with knowing your “potential” for a disease, based solely on your genetic testing, when it may never come to fruition. Not to mention, its effect on planning for one’s future decisions relative to career, residence, and relationship commitments.

Even some physicians are reticent to undergo genetic testing for fear of who might gain access to the information and the consequences thereof.

Physicians face an additional conundrum in dealing with patient-supplied information: How to counsel patients when, in some cases, the task should be the responsibility of a community resources representative? In addition, patients who request that certain information not be included in their personal health record, present a problem for a physician justifying a test or a procedure to a payer.

The consumerization of healthcare and patient engagement strategies employed to deliver better outcomes are driving the healthcare industry to open conversations that elevate the level of care delivered to patients. In addition, physicians need to demand more direction and initiate more discussions on how to deal with the opportunities and challenges presented in the era of patient-derived and pharmacogenomics data.

While improving patient-physician communication should always be a priority, discussing how and when to use genetic and patient-derived information is still a work in progress.

Dr. Furst is Vice President Clinical Consultants at Elsevier Clinical Solutions.

Key Articles in Health IT from 2017 (Part 2 of 2)

Posted on January 4, 2018 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.

The first part of this article set a general context for health IT in 2017 and started through the year with a review of interesting articles and studies. We’ll finish the review here.

A thoughtful article suggests a positive approach toward health care quality. The author stresses the value of organic change, although using data for accountability has value too.

An article extolling digital payments actually said more about the out-of-control complexity of the US reimbursement system. It may or not be coincidental that her article appeared one day after the CommonWell Health Alliance announced an API whose main purpose seems to be to facilitate payment and other data exchanges related to law and regulation.

A survey by KLAS asked health care providers what they want in connected apps. Most apps currently just display data from a health record.

A controlled study revived the concept of Health Information Exchanges as stand-alone institutions, examining the effects of emergency departments using one HIE in New York State.

In contrast to many leaders in the new Administration, Dr. Donald Rucker received positive comments upon acceding to the position of National Coordinator. More alarm was raised about the appointment of Scott Gottlieb as head of the FDA, but a later assessment gave him high marks for his first few months.

Before Dr. Gottlieb got there, the FDA was already loosening up. The 21st Century Cures Act instructed it to keep its hands off many health-related digital technologies. After kneecapping consumer access to genetic testing and then allowing it back into the ring in 2015, the FDA advanced consumer genetics another step this year with approval for 23andMe tests about risks for seven diseases. A close look at another DNA site’s privacy policy, meanwhile, warns that their use of data exploits loopholes in the laws and could end up hurting consumers. Another critique of the Genetic Information Nondiscrimination Act has been written by Dr. Deborah Peel of Patient Privacy Rights.

Little noticed was a bill authorizing the FDA to be more flexible in its regulation of digital apps. Shortly after, the FDA announced its principles for approving digital apps, stressing good software development practices over clinical trials.

No improvement has been seen in the regard clinicians have for electronic records. Subjective reports condemned the notorious number of clicks required. A study showed they spend as much time on computer work as they do seeing patients. Another study found the ratio to be even worse. Shoving the job onto scribes may introduce inaccuracies.

The time spent might actually pay off if the resulting data could generate new treatments, increase personalized care, and lower costs. But the analytics that are critical to these advances have stumbled in health care institutions, in large part because of the perennial barrier of interoperability. But analytics are showing scattered successes, being used to:

Deloitte published a guide to implementing health care analytics. And finally, a clarion signal that analytics in health care has arrived: WIRED covers it.

A government cybersecurity report warns that health technology will likely soon contribute to the stream of breaches in health care.

Dr. Joseph Kvedar identified fruitful areas for applying digital technology to clinical research.

The Government Accountability Office, terror of many US bureaucracies, cam out with a report criticizing the sloppiness of quality measures at the VA.

A report by leaders of the SMART platform listed barriers to interoperability and the use of analytics to change health care.

To improve the lower outcomes seen by marginalized communities, the NIH is recruiting people from those populations to trust the government with their health data. A policy analyst calls on digital health companies to diversify their staff as well. Google’s parent company, Alphabet, is also getting into the act.

Specific technologies

Digital apps are part of most modern health efforts, of course. A few articles focused on the apps themselves. One study found that digital apps can improve depression. Another found that an app can improve ADHD.

Lots of intriguing devices are being developed:

Remote monitoring and telehealth have also been in the news.

Natural language processing and voice interfaces are becoming a critical part of spreading health care:

Facial recognition is another potentially useful technology. It can replace passwords or devices to enable quick access to medical records.

Virtual reality and augmented reality seem to have some limited applications to health care. They are useful foremost in education, but also for pain management, physical therapy, and relaxation.

A number of articles hold out the tantalizing promise that interoperability headaches can be cured through blockchain, the newest hot application of cryptography. But one analysis warned that blockchain will be difficult and expensive to adopt.

3D printing can be used to produce models for training purposes as well as surgical tools and implants customized to the patient.

A number of other interesting companies in digital health can be found in a Fortune article.

We’ll end the year with a news item similar to one that began the article: serious good news about the ability of Accountable Care Organizations (ACOs) to save money. I would also like to mention three major articles of my own:

I hope this review of the year’s articles and studies in health IT has helped you recall key advances or challenges, and perhaps flagged some valuable topics for you to follow. 2018 will continue to be a year of adjustment to new reimbursement realities touched off by the tax bill, so health IT may once again languish somewhat.

MindCrowd Memory Test

Posted on April 19, 2017 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.

This week I was the moderator at the DellEMC #TranformHIT Healthcare Think Tank event. It was a great event and if you missed it, you can search the #TranformHIT on Twitter or find the recording in the embedded video at the bottom of this post.

One of the highlights of the event for me was meeting Dr. Jeff Trent From TGen, a nonprofit institute focused on translating genomic research into life-changing results. The work they’re doing is really quite incredible and Dr. Trent offered some great insights at the Think Tank.

One of the research projects at TGen is called Mind Crowd. This research looks at memory and other brain related diseases. As part of the study, they’re trying to get 1 million people to participate in a fun, but simple mind test on their site. The test takes about 10 minutes, but try it out and see how you do.

What’s fascinating about the results they’ve already seen from the 74k+ people who have taken the test to date is that women of all ages actually have better memory than men. There are outliers, but across the data it’s very clear that in this test women remember things better than men.

To add to these findings, there’s also an interesting thing that happens when women approach the age of menopause. Women at that age seem to actually get an increase in their memory. It’s not clear why this is the case, but the data shows an uptick in memory about the time most women hit menopause.

Tgen is also taking the outliers and working with them to study why their memory is so much better or worse (ie. an older person with an incredible memory or a younger person with a poor memory). I’m interested to see what comes from these studies.

If you want to contribute to their research, take 10 minutes and go and participate in their Mind Test.
Read more..

23andMe Gets FDA Authorization for Consumer Genetic Health Risk Reports

Posted on April 11, 2017 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.

The big news about 23andMe’s FDA approval came out last week when I was holed up at a conference.

That’s right. 23andMe can now directly offer consumers a genetic health risk report that’s FDA approved. This is a big step for 23andMe when you consider that they’d previously gotten their hand slapped by the FDA.

23andMe got what’s called a de novo authorization from the FDA. This is something we’re likely to see more of and something that I’m sure many people aren’t familiar with. Here’s a description of what a de novo authorization is from the 23andMe announcement:

What does it mean to be granted a de novo authorization?
The Food and Drug Administration Modernization Act of 1997 (FDAMA) added the de novo classification option, which provides an alternate pathway to classify novel devices of low to moderate risk. The de novo process is used by the FDA to grant marketing authorization for devices that are new and unlike any other on the market. In addition de novo marketing authorization means that 23andMe met the FDA’s premarket requirements to demonstrate the following: accuracy, validity and user comprehension.

I’m glad that the FDA has created this new form of authorization for companies like 23andMe. This story also stands in stark contrast to other FDA related stories like Theranos. I’m sure that 23andMe would hate the comparison. However, there are some similarities. They both got slapped by the FDA. However, their response to the FDA’s notices was completely different. That’s why 23andMe seems to still be thriving and now have FDA approval. Theranos is floundering with reports that their founder now owes the company $25 million.

Needless to say, if you’re a healthcare startup, make sure you know the FDA regulations that apply to your startup.

Genomics as the Next “Information Technology” Investment Category

Posted on January 4, 2017 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.

Many of you know that I read various venture capital blogs as my hobby. My favorite is Fred Wilson’s blog. I’ve gleaned so much from his blog that’s helped me personally and professionally. When I know I have some blogs from Fred in my feed reader (which I usually do since he blogs every day), it’s like anticipating a delicious dessert since I know reading his blogs will be a fun experience (yes, I’m a nerd like that).

My Fred Wilson fandom aside, I was fascinated by Fred’s 2017 predictions including this one about genomics:

Tech investors will start to adopt genomics as an additional “information technology” investment category, blurring the distinction between life science and tech investors that has existed in the VC sector for the past thirty years. This will lead to a funding frenzy and many investments will go badly. But there will be big winners to be had in this sector and it will be an important category for VCs for the foreseeable future.

The timing for this is interesting since this week is CES. Last year at CES I moderated a panel on genomics. I led off the panel by saying, “Thanks for coming in from looking at all the iPhone cases to talk about something a little more substantial.” Needless to say, I’m quite bullish on what’s going to be possible with genomics. Although, I think Fred might be a little ahead of the curve on when tech and genomics will merge.

What’s interesting is that there should be an overlap in tech and genomics. How is creating some sort of healthcare analytics any different than doing the same with genomic data? Certainly, you could argue that genomic data is much more challenging and complex, but at the end of the day it’s still about culling through and understanding the data. For some reason though when we say genomics we think that it’s a unique class of investment. In most cases, it’s shouldn’t be all that different.

I do think Fred is spot on when he talks about many genomic investments going badly and many of them being big winners. In that way, it kind of feels more like pharma investment than it does technology. Maybe that’s why people feel like genomic medicine investments aren’t technology investments.

It’s going to be fun to see the genomic market play out. I’m also interested in the companies that are going to make our efforts available to a much broader group of people. I imagine that’s the type of investments that Fred Wilson and USV would like to make. They aren’t likely as interested in investing in the genomic findings, but the genomic tools that will empower anyone to make a genomic discovery. Or possibly the platform that will share and commercialize genomic findings. Those are both really interesting areas that I bet hits Fred’s investment themes well.