Google And Fitbit’s Alliance Is A Bit Risky

Alliance Between Google And Fitbit Is A Bit Risky

Fitbit’s health alliance with Google could be a risky experiment.  These two companies introduced a new partnership on healthcare.  Fitbit will expand shopper and endeavor well being answers that can use Google’s new Cloud Healthcare software programming interface.

Fitbit will additionally transfer to the Google Cloud Platform to innovate and advance its services. The Transfer will permit Fitbit to leverage Google Cloud’s infrastructure and security measures.  This is in addition to Google’s synthetic intelligence and device studying functions, and its new predictive analytic algorithms.

Cloud Healthcare API

Google and Fitbit are exploring the development of consumer and enterprise health solutions.  Fitbit intends to use Google’s new Cloud Healthcare API.  This is to help the company integrate further into the healthcare system.  This may include connecting user data with electronic medical records (EMR).  This will provide the patients and clinicians a more comprehensive view of the patient profile, which will lead to more personalized care.

The companies will also look into help better manage chronic conditions like hypertension and diabetes.  This may be done by using Fitbit’s  recently acquired Twine Health.  Using Google’s Cloud Healthcare API, Twine can make it easier for clinicians and patients to collaborate on care, helping lead to better health outcomes and positive returns.

With this innovation by the two companies, they will have the opportunity to deliver up-to-date information to providers, enhancing their ability to follow and manage the health of their patients and guide their treatment.

Why The Alliance Between Google And Fitbit May Be Risky

There are two drawbacks to this deal.  First, Fitbit customers will have privacy concerns.  The partnership with Google increases the anxiety around that.  Second, Google’s history with wearables is not exactly positive.

Healthcare is a sensitive topic.  The potential opposite of health is death.

Amazing Advances in Neonatal Care

It is difficult to overstate the pace of technological advancement in the twenty-first century. Most of us are old enough to remember the days before the internet, before smartphones, before IMDB and Wikipedia gave us instant answers to all of life’s questions, and before Netflix replaced our shelves upon shelves of VHS tapes. But something we don’t think about quite as much is the application of developed technology to healthcare.

There are few things as important to us as our children. The plight of newborn babies tugs at the heartstrings of even the most callous among us. And our collective investment in improving techniques and technologies to improve healthcare outcomes for these tiny treasures reflects this priority. These are just a few developing devices and amazing advances in neonatal care.


Pulmonary Function Tests

One of the most challenging elements of neonatal care is the infant’s lung capacity and function. Early detection of lung problems could save many lives. Current methodology for testing lung function is improving by leaps and bounds, leading to earlier detection and better diagnoses for infants with pulmonary disorders such as apnea or hypoxemia.


Artificial Wombs

Last year, Children’s Hospital of Philadelphia doctors reported a surprisingly successful experiment. According to a Wall Street Journal article, “they kept premature lambs alive in a bag of fluid for longer and with better health outcomes than in previous artificial-womb experiments.” While the technology still needs some improvements before wide-scale deployment for human children, the concept is promising. These fluid-filled bags, complete with an artificial placenta, will effectively allow doctors to treat premies as a fetus, rather than a newborn – potentially saving the lives of infants with underdeveloped lungs.


Predictive Monitoring

The implications of Big Data on modern society are still not totally obvious. Mankind has amassed more information in the past thirty years than all previous generations combined. As you read this, data scientists are analyzing millions of records and looking for predictive trends in complex systems such as weather patterns, the stock market, and in the human body.

One of the many interesting applications of predictive analytics is the ability to analyze infant vital metrics in real time and predict illnesses and detect injuries faster and earlier, leading to lower infant mortality. According to a paper published in Frontiers in Pediatrics, “The high volume of data generated in an NICU with a velocity of hundreds of data points per patient-minute can be used for predictive monitoring. This involves analyzing physiological data to identify infants at high risk and detect illness in an early stage”


Extracorporeal Membrane Oxygenation Machine

This device can be thought of as an artificial lung that operates outside the infant’s body. It’s very similar to a heart-lung machine. Blood from the infant is circulated into the machine, cleaned of carbon dioxide, enriched with fresh oxygen, and circulated back into the baby’s bloodstream.


We all care deeply about the rising generation. Luckily for those of us in developed nations, the best minds on the planet are dedicated to improving the quality of care and developing innovations that will reduce infant mortality by leaps and bounds.

Image Credit: Guardian Angel Adoptions



Why Medical Data Systems are Crumbling

If you’ve ever spent time working with medical data systems, you know that they’re not great. They’re slow, they’re complex, and they feel like they came out of another decade. In fact, many did come out of another decade, and they’ve been making miserable the lives of techs and nurses ever since. In short, they suck. There are a few reasons for this, though, which can help you understand why the systems are in such a poor state.


Lowest Bidder Problems

Let us begin with a simple truth – these systems frequently aren’t top of the line. In most cases, the lowest bidder builds medical information technology. It’s one of the few places in which a hospital or practice can feel comfortable saving money, so it never pursues the top of the line. Instead, you’ll always be stuck with the discount version of a much better program. If you’re lucky, you’ll get something with support. If not, you’ll get a custom program that was built cheaply and must be worked around to function.


Old Data, Big Problems

Medical data persists for a very long time. The good news is that many hospitals were quick to start digitizing data. The bad news is that all of that data has to stick around. Unfortunately, that means that expert IT professionals must waste their time maintaining these ancient databases. According to Harmony, legacy data systems are difficult to migrate, so you’ll either be stuck with the original system or with an unwieldy half-solution. Everyone knows that this is not a very good fix, but everyone also knows that it would cost too much money and require too much time for anyone to actually fix the problem.


Not Patient-Facing

Perhaps the major reason that medical data systems remain so awful is that they aren’t patient-facing. While everything else in a medical practice or hospital needs to convince patients that they are in good hands, the IT system is only used by the employees. If the assumption remains that the patient’s experience is paramount, something will eventually have to give. Given budgetary restraints and the fact that most medical personnel are adept at working around the problems of the systems, there seems no chance that most medical systems will be updated.


In short, medical data systems suck because they’re too expensive and too difficult to change. Overhauling the system would take money away from patient care, even if only briefly. It might be short-term thinking to keep the data systems as they are, but the truth is that they will continue to suck as long as they continue to function.

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