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Supercharged Wearables Are On The Horizon

Posted on January 3, 2018 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Over the last several years, the healthcare industry has been engaged in a rollicking debate over the value of patient-generated health data. Critics say that it’s too soon to decide whether such tools can really add value to medical care, while fans suggest it’s high time to make use of this information.

That’s all fine, but to me, this discussion no longer matters. We are past the question of whether consumer wearables data helps clinicians, which, in their current state, are under-regulated and underpowered. We’re moving on to profoundly more-capable devices that will make the current generation look like toys.

Today, tech giants are working on next-generation devices which will perform more sophisticated tracking and solve more targeted problems. Clinicians, take note of the following news items, which come from The New York Times:

  • Amazon recently invested in Grail, a cancer-detection start-up which raised more than $900 million
  • Apple acquired Beddit, which makes sleep-tracking technology
  • Alphabet acquired Senosis Health, which develops apps that use smartphone sensors to monitor health signals

And the action isn’t limited to acquisitions — tech giants are also getting serious about creating their own products internally. For example, Alphabet’s research unit, Verily Life Sciences, is developing new tools to collect and analyze health data.

Recently, it introduced a health research device, the Verily Study Watch, which has sensors that can collect data on heart rate, gait and skin temperature. That might not be so exciting on its own, but the associated research program is intriguing.

Verily is using the watch to conduct a study called Project Baseline. The study will follow about 10,000 volunteers, who will also be asked to use sleep sensors at night, and also agreed to blood, genetic and mental health tests. Verily will use data analytics and machine learning to gather a more-detailed picture of how cancer progresses.

I could go on, but I’m sure you get the point. We are not looking at your father’s wearables anymore — we’re looking at devices that can change how disease is detected and perhaps even treated dramatically.

Sure, the Fitbits of the world aren’t likely to go away, and some organizations will remain interested in integrating such data into the big data stores. But given what the tech giants are doing, the first generation of plain-vanilla devices will soon end up in the junk heap of medical history.

Capturing Unstructured Data for Better Patient Care

Posted on October 9, 2014 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 following is a guest blog post by Dr. Chris Tackaberry, CEO of Clinithink.
Clinithink_Chris Tackaberry_CEO and Founder
There is a veritable gold mine of high value data locked inside the free text fields of all EHR systems, as well as in the free text of other sources of clinical documentation such as progress notes, discharge summaries, consult requests and diagnostic reports. In all of these sources, rich, actionable patient data is trapped in unstructured text—stored side by side with more easily accessible structured data.

Take echocardiography reports, for example. The data contained within them—specifically ejection fraction, for instance—are crucial to the management of heart failure as outlined within NQMC core measures for this serious chronic condition. Yet seldom is an ejection fraction captured as structured data. Instead, it is usually documented as free text.

Since narrative has been an inherent part of clinical workflow for many years, HIT software vendors have reasonably added free text fields to their applications. While there is clearly value in driving insights from structured data captured in such systems, the unstructured piece in free text fields remains untapped. This represents a source of potentially significant additional value that can be gleaned from EHR and other clinical documentation sources. However, conventional structured data tools do not support the ability to exploit it for use in clinical decision making.

Unlocking the clinical value in unstructured data

In the days of paper charts, highly experienced physicians were able to quickly scan large charts to find information such as allergies, medications, family history, past and current symptoms, social history, and other background detail that provided the context so critically important to any clinical encounter. This information was usually summarized in documents (discharge summaries, referrals, etc.). Ironically, such information is now more difficult to find when stored electronically.

If the existence of unstructured narrative data were known, discoverable, searchable and actionable for every patient—across any EMR or other health IT systems—the currently hidden additional diagnostic and clinical data could further increase the efficiency and quality of care. Clinical Natural Language Processing (CNLP) is a technology that enables access to unstructured narrative data which can be used to unlock this additional value. Using narrative data found in reports, web pages, transcribed output, EMRs, and other electronic sources of free text at the point of care can expand our knowledge of the patient beyond the information obtained from structured data.

Recently, the AMA issued a report in conjunction with the RAND Corporation on the need for EHR vendors to improve the software solutions they are delivering to better meet the needs of physicians. Utilizing CNLP technology to access the clinical value inherent in unstructured EHR data would allow vendors to begin addressing some of the potential improvements.

As we move from a world in which healthcare is delivered on an episodic basis retrospectively to one where care is delivered almost continuously and prospectively, CNLP increases the opportunity to deliver rich, actionable and meaningful clinical content to help improve decision-making for more accurate, evidence-based and effective care.

Dr. Chris Tackaberry is the CEO of Clinithink.

Will Texans Own Their DNA? Greg Abbott, Candidate for Governor, Thinks They Should

Posted on November 26, 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.

The following is a guest post by Dr. Deborah Peel, Founder of Patient Privacy Rights.

On November 12th, Abbott released his “We the People Plan” for Texas. Clearly he’s heard from Texans who want tough new health data privacy protections.

Topping his list are four terrific privacy recommendations for health and genetic data:

  • “Recognize a property right in one’s own DNA.”
  • “Make state agencies, before selling database information, acquire the consent of any individual whose data is to be released.”
  • “Prohibit data resale and anonymous purchasing by third parties.”
  • “Prohibit the use of cross referencing techniques to identify individuals whose data is used as a larger set of information in an online data base.”

The federal Omnibus Privacy Rule operationalized the technology section of the stimulus bill. It also clarified that state legislatures can pass data privacy laws that are stronger than HIPAA (which is a very weak floor for data protections).

Texans would overwhelmingly support the new state data protection laws Abbott recommends . If elected, hopefully Abbott would also include strong enforcement and penalties for violations. Contracts don’t enforce themselves. External auditing and proof of trustworthy practices should be required.

Is this the beginning of a national trend?  I think so. The more people know about today’s health IT, the more they will reject electronic systems and data exchanges designed for the hidden use and sale of sensitive personal health data.

Show Me the Data Video

Posted on May 6, 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.

Paul Levy blogged about Eric Topol’s move to be editor-in-chief at Medscape. It’s an interesting move for Dr. Topol and it will be interesting to see how Medscape does with Dr. Topol at the helm. However, even more entertaining is the video that Paul Levy embedded in his post. A nice rework of the popular scene from Jerry Maguire. Many of my readers will really appreciate it. I guess Dr. Topol uses this video in the lectures he does to explain why patients need their data. Enjoy!

The Body as a Source of Big Data Infographic

Posted on March 1, 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.

NetApp recently put out an Infographic that depicts the body as a source of big data. It’s a pretty cool representation of the power of data in healthcare. In my HIMSS 2013 preview video, I suggested that HIMSS 2013 might be the year of Healthcare Big Data at HIMSS. This infographic displays many of the opportunities.
The Power of Healthcare Data