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Modern Day Healthcare Tools and Solutions Can Enhance Your Brand Integrity and Patient Experience

Posted on August 11, 2016 I Written By

The following is a guest blog post by Chelsea Kimbrough, a copywriter for Stericycle Communication Solutions as part of the Communication Solutions Series of blog posts. Follow and engage with them on Twitter: @StericycleComms
Chelsea Kimbrough
Digitally speaking, the healthcare market is more crowded than ever – and finding the perfect provider, practice, or physician online can quickly become an arduous task for even the most tech-savvy patient. But healthcare organizations that dedicate the time, effort, and resources to create a unique digital presence, enhance their search engine optimization (SEO), and reinforce their brand integrity can cut through oversaturated search results to acquire and retain more patients.

In today’s consumer-driven world, shopping for the ideal healthcare organization is quickly becoming the norm. More and more frequently, patients are turning toward the internet during their hunt. In fact, 50 percent of millennials and Gen-Xers used online reviews while last shopping for a healthcare provider. And with 85 percent of adults using the internet and 67 percent using smartphones, accessing this sort of information is easier than ever before.

This ease of access has led patients to adopt more consumer-like behaviors and expectations, such as valuing quality and convenience. Healthcare organizations that proactively ensure their brand image, digital presence, and patient experience cater to these new expectations could be best positioned to thrive. By providing convenient, patient-centric healthcare tools and services, organizations can help facilitate this effort throughout every step of the patient journey.

One such tool is real-time, online appointment self-scheduling, which 77 percent of patients think is important. In addition to adding a degree of convenience for digitally-inclined patients, online self-scheduling tools can support your healthcare organizations’ key initiatives – including driving new, commercially insured patient growth. By using an intuitive way to quickly schedule an appointment, potential patients’ shopping process can be halted in its tracks, ensuring more patients choose your organization over a competitor’s. And with the right tool, your search rankings and discoverability, or SEO, could be significantly enhanced.

Reaching patients where they are most likely to be reached is another way to improve your brand experience. Like consumers, patients are often connected to their phones – so much so that text messages have a 98 percent open rate. Organizations that leverage automated text, email, and voice reminders can successfully communicate important messages, boost patients’ overall satisfaction and health, and improve appointment and follow-up adherence – ultimately setting themselves apart from competitors.

Other digital tools, technologies, and communication strategies can help fortify your brand’s digital standing and patients’ satisfaction, including social media outreach, useful email campaigns, and more. Whatever method – or methods – best serve your organization, it’s important they help improve your SEO, enhance patients’ overall accessibility and experience, and support your brand values and initiatives.

The Communication Solutions Series of blog posts is sponsored by Stericycle Communication Solutions, a leading provider of high quality telephone answering, appointment scheduling, and automated communication services. Stericycle Communication Solutions combines a human touch with innovative technology to deliver best-in-class communication services.  Connect with Stericycle Communication Solutions on social media:  @StericycleComms

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

Posted on August 10, 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.

The previous section of this article looked at how little help we get from genetic testing. Admittedly, when treatments have been associated with genetic factors, testing has often been the difference between life and death. Sometimes doctors can hone in with laser accuracy on a treatment that works for someone because a genetic test shows that he or she will respond to that treatment. Hopefully, the number of treatments that we can associate with tests will grow over time.

So genetics holds promise, but behavioral and environmental data are what we can use right now. One sees stories in the trade press all the time such as these:

These studies usually depend on straightforward combinations of data that are easy to get, either from the health care system (clinical or billing data) or from the patient (reports of medication adherence, pain level, etc.).

And we’ve only scratched the surface of the data available to us. Fitness devices, sensors in our neighborhoods, and other input will give us much more. We can also find new applications for data: for instance, to determine whether one institution is overprescribing certain high-cost drugs, or whether an asthma victim is using an inhaler too often, meaning the medication isn’t strong enough. We know that social factors, notably poverty (LGBTQ status is not mentioned in the article, but is another a huge contributor to negative health outcomes, due to discrimination and clinician ignorance) must be incorporated into models for diagnosis, prediction, and care.

President Obama promises that Precision Medicine features both genetics and personal information. One million volunteers are sought for DNA samples and information on age, race, income, education, sexual orientation, and gender identity.

There are other issues that critics have brought up with the Precision Medicine initiative. For instance, its focus on cure instead of prevention weakens its value for long-term public health improvements. We must also remember the large chasm between knowing what’s good for you and doing it. People don’t change notoriously unhealthy behaviors, such as smoking, even when told they are at increased risk. Some experts think people shouldn’t be told their DNA results.

Meanwhile, those genetic database can be used against you. But let’s consider our context, once again, in order to assess the situation responsibly. The data is being mined by police, but it’s probably not very useful because the DNA segments collected are different from what the police are looking for. Behavioral data, if abused, is probably more damning than genetic data.

Just as there are powerful economic forces biasing us toward genetics, social and political considerations weigh against behavioral and environmental data. We all know the weaknesses in the government’s dietary guidelines, heavily skewed by the food industry. And the water disaster in Flint, Michigan showed how cowardice and resistance by the guardians of public health to admitting changes raised the costs in public health measures. Industry lobbying and bureaucratic inertia work together to undermine the simplest and most effective ways of improving health. But let’s get behavioral and environmental measures on the right track before splurging on genetic testing.

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.

If MACRA Fails, It Will Be a Failure of IT, Not Doctors or Regulators

Posted on August 8, 2016 I Written By

The following is a guest blog by Steve Daniels, president of Able Health.

There has been a whole lot of mudslinging over the last month between regulators and healthcare providers over MACRA, which shifts Medicare payments further toward pay-for-performance starting January 1. On the one hand, CMS Acting Administrator Andy Slavitt is clear that CMS is ready for change. “We need to get out of the mode of paying physicians just to run tests and prescribe medicines,” he told a Senate Finance Committee hearing. Meanwhile, Dr. Thomas Eppes of the American Medical Association has called MACRA a “quantum shift” and pushed for a delay.

Yes, the Medicare Quality Payment Program instituted by MACRA should—and will—evolve based on comments made on the proposed rule. But the reality is the program provides enormous opportunity for providers to increase bonus payments, while streamlining reporting requirements across a patchwork of outdated and duplicative programs. And it’s worth noting that the potential penalties under the Merit-Based Incentive Payment System (MIPS) over the next four years are actually lower than the sum of the penalties of the programs it is replacing.

To meet MACRA goals, it will take a well-prepared team of providers and administrators—empowered by data and well-designed tools. Doctors can’t be solely responsible for achieving patient outcomes, reducing costs and documenting it all for CMS as they go. Unfortunately, the history of health IT has not been kind—or affordable—to doctors. And today, the health IT stack has a new challenge—keeping pace with the proliferation of value-based programs, from accessing data all the way through enabling new clinical practice.

We must move from a mindset of meeting Meaningful Use checkboxes toward supporting a more effective way of operating. And in the modern world of software-as-as-service, there’s no good reason left that IT needs to cost providers millions of dollars. We can do better. As things stand, if MACRA fails, it will be a failure of IT, not doctors or regulators.

Gathering all the data

For value-based care to work, patient data needs to be made available for providers to coordinate with each other, as well as to payers, to properly evaluate performance based on all known information. Those still blocking or jacking up prices for data access are complicit in obstructing the vision of a learning value-based system.

It is time to remove technical barriers through modern and open data standards like FHIR, as well as rules and unreasonable fees that prevent parties from accessing data when they need it. Thankfully, the Advancing Care Information performance category will reflect the emphasis on information exchange set forth in Meaningful Use Stage 3.

Calculating performance flexibly

The new era of performance-based pay requires continuous monitoring of quality and cost, with the ability to track progress across multiple programs on an ongoing basis. To measure quality today, we often use static algorithms hard-coded by EHRs vendors and health system IT departments, conforming to standards set by NCQA or CMS.

But providers need tools that are tailored not just to one or two programs like Meaningful Use and PQRS, but across the organization’s full range of value-based programs as these program continue to expand, evolve, and proliferate. With efforts to standardize IT for quality measures stalling, vendors need to focus less on one-size-fits-all quality measure calculations and more on flexible systems that enable measures to be rapidly constructed and customized to move with the trends. Expect change to be the norm.

Informing new behaviors

With so many health IT professionals focused on gathering and reporting data, it is not surprising that design has taken a back seat so far. But this year, not a single population health vendor earned an “A” rating from Chilmark, due to poor user engagement and clinical workflow. This is no longer acceptable. The challenge of enabling the new clinical and administrative behaviors associated with value-based care is too vast. User experience must be top of mind for any IT implementation, with representative users involved from the start. We have seen the impact of poor user experience in the fee-for-service system, from frustrated clinicians to alarming patient safety issues.

Design is even more important when the challenge is not just documenting billing codes but also achieving health outcomes for patients across a care team. Don’t bombard clinicians with notifications and force clumsy form-filling. Instead, employ best practices from cognitive psychology to inform professionals with lightweight and intelligent touchpoints. Automate documentation and interpretation of data wherever possible.

A new era of health IT

Whether or not it’s delayed, the Quality Payment Program is coming. And the healthcare industry is moving inexorably toward value-based care. Will health IT step up to the challenge of building toward a value-based future that is accessible to all providers? Or will we sit back and wait for the next list of requirements?

About Steve Daniels
Steve Daniels is the President of Able Health, which helps providers succeed under MACRA and value-based programs. Formerly the design lead for IBM Watson for healthcare and a lifelong patient advocate, he is passionate about the role of open data exchange and intuitive experience design in fostering a continuously improving healthcare system. Find him on Twitter and LinkedIn.

ZDoggMD Sings 7 Years (A Life In Medicine) – The Path to Health 3.0

Posted on August 5, 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.

Rather than try to explain this ZDoggMD video, I thought this comment from Riley Mcnamara on ZDoggMD’s latest video described it best:

I’m dealing with a lot of crap right now in the clinic, we’re over booked with patients, EHR headaches, and a never ending stream of useless bureaucracy. It’s been one of those weeks that made me question if I can do this. This made me feel better even if it’s just for a little bit! It’s not easy, but I’d never dream of doing anything else! Thanks man!

There truly is a battle going on for the future of healthcare and it’s a battle worth fighting. Thanks for the excellent work ZDoggMD! Shout out to HealthISPrimary.org as well. Check out the video below:

The Value of Machine Learning in Value-based Care

Posted on August 4, 2016 I Written By

The following is a guest blog post by Mary Hardy, Vice President of Healthcare for Ayasdi.

Variation is a natural element in most healthcare delivery. After all, every patient is unique. But unwarranted clinical variation—the kind that results from a lack of systems and collaboration or the inappropriate use of care and services—is another issue altogether.

Healthcare industry thought leaders have called for the reduction of such unwarranted variation as the key to improving the quality and decreasing the cost of care. They have declared, quite rightly, that the quality of care an individual receives should not depend on geography. In response, hospitals throughout the United States are taking on the significant challenge of understanding and managing this variation.

Most hospitals recognize that the ability to distill the right insights from patient data is the catalyst for eliminating unwarranted clinical variation and is essential to implementing care models based on value. However, the complexity of patient data—a complexity that will only increase with the impending onslaught of data from biometric and personal fitness devices—can be overwhelming to even the most advanced organizations. There aren’t enough data scientists or analysts to make sense of the exponentially growing data sets within each organization.

Enter machine learning. Machine learning applications combine algorithms from computational biology and other disciplines to find patterns within billions of data points. The power of these algorithms enables organizations to uncover the evidence-based insights required for success in the value-based care environment.

Machine Learning and the Evolutionary Leap in Clinical Pathway Development
Since the 1990s, provider organizations have attempted to curb unwarranted variation by developing clinical pathways. A multi-disciplinary team of providers use peer-reviewed literature and patient population data to develop and validate best-practice protocols and guidance for specific conditions, treatments, and outcomes.

However, the process is burdened by significant limitations. Pathways often require months or years to research, build, and validate. Additionally, today’s clinical pathways are typically one-size-fits-all. Health systems that have the resources to do so often employ their own experts, who review research, pull data, run tables and come to a consensus on the ideal clinical pathway, but are still constrained by the experts’ inability to make sense of billions of data points.

Additionally, once the clinical pathway has been established, hospitals have few resources for tracking the care team’s adherence to the agreed-upon protocol. This alone is enough to derail years of efforts to reduce unwarranted variation.

Machine learning is the evolutionary leap in clinical pathway development and adherence. Acceleration is certainly a positive. High-performance machines and algorithms can examine complex continuously growing data elements far faster and capture insights more comprehensively than traditional or homegrown analytics tools. (Imagine reducing the development of a clinical pathway from months or years to weeks or days.)

But the true value of machine learning is enabling provider organizations to leverage patient population data from their own systems of record to develop clinical pathways that are customized to the organization’s processes, demographics, and clinicians.

Additionally, machine learning applications empower organizations to precisely track care team adherence, improving communication and organization effectiveness. By guiding clinicians to follow best practices through each step of care delivery, clinical pathways that are rooted in machine learning ensure that all patients receive the same level of high-quality care at the lowest possible cost.

Machine Learning Proves its Value
St. Louis-based Mercy, one of the most innovative health systems in the world, used a machine-learning application to recreate and improve upon a clinical pathway for total knee replacement surgery.

Drawing from Mercy’s integrated electronic medical record (EMR), the application grouped data from a highly complex series of events related to the procedure and segmented it. It was then possible to adapt other methods from biology and signals processing to the problem of determining the optimal way to perform the procedure—which drugs, tests, implants and other processes contribute to that optimal outcome. It also was possible to link predictive machine learning methods like regression or classification to perform real-time pathway editing.

The application revealed that Mercy’s patients naturally divided into clusters or groups with similar outcomes. The primary metric of interest to Mercy as an indicator of high quality was length of stay (LOS). The system highlighted clusters of patients with the shortest LOS and quickly discerned what distinguished this cluster from patients with the longest LOS.

What this analysis revealed was an unforeseen and groundbreaking care pathway for high-quality total knee replacement. The common denominator between all patients with the shortest LOS and best outcomes was administration of pregabalin—a drug generally prescribed for shingles. A group of four physicians had seen something in the medical literature that led them to believe that administering the drug prior to surgery would inhibit postoperative pain, reduce opiate usage and produce faster ambulation. It did.

This innovation was happening in Mercy’s own backyard, and it was undeniably a best practice—the data revealed that each of the best outcomes included administration of this drug. Using traditional approaches, it is highly unlikely that Mercy would have asked the question, “What if we use a shingles drug to improve total knee replacement?” The superior outcomes of four physicians would have remained hidden in a sea of complex data.

This single procedure was worth over $1 million per year for Mercy in direct costs.

What Mercy’s experience demonstrates is that the most difficult, persistent and complex problems in healthcare can resolve themselves through data. The key lies in having the right tools to navigate that data’s complexity. The ability to determine at a glance what differentiates good outcomes from bad outcomes is incredibly powerful—and will transform care delivery.

Mary Hardy is the Vice President of Healthcare for Ayasdi, a developer of machine intelligent applications for health systems and payer organizations.

ONC Announces Winners Of FHIR App Challenge

Posted on August 3, 2016 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.

The ONC has announced the first wave of winners of two app challenges, both of which called for competitors to use FHIR standards and open APIs.

As I’ve noted previously, I’m skeptical that market forces can solve our industry’s broad interoperability problems, even if they’re supported and channeled by a neutral intermediary like ONC. But there’s little doubt that FHIR has the potential to provide some of the benefits of interoperability, as we’ll see below.

Winners of Phase 1 of the agency’s Consumer Health Data Aggregator Challenge, each of whom will receive a $15,000 award, included the following:

  • Green Circle Health’s platform is designed to provide a comprehensive family health dashboard covering the Common Clinical Data Set, using FHIR to transfer patient information. This app will also integrate patient-generated health data from connected devices such as wearables and sensors.
  • The Prevvy Family Health Assistant by HealthCentrix offers tools for managing a family’s health and wellness, as well as targeted data exchange. Prevvy uses both FHIR and Direct messaging with EMRs certified for Meaningful Use Stage 2.
  • Medyear’s mobile app uses FHIR to merge patient records from multiple sources, making them accessible through a single interface. It displays real-time EMR updates via a social media-style feed, as well as functions intended to make it simple to message or call clinicians.
  • The Locket app by MetroStar Systems pulls patient data from different EMRs together onto a single mobile device. Other Locket capabilities include paper-free check in and appointment scheduling and reminders.

ONC also announced winners of the Provider User Experience Challenge, each of whom will also get a $15,000 award. This part of the contest was dedicated to promoting the use of FHIR as well, but participants were asked to show how they could enhance providers’ EMR experience, specifically by making clinical workflows more intuitive, specific to clinical specialty and actionable, by making data accessible to apps through APIs. Winners include the following:

  • The Herald platform by Herald Health uses FHIR to highlight patient information most needed by clinicians. By integrating FHIT, Herald will offer alerts based on real-time EMR data.
  • PHRASE (Population Health Risk Assessment Support Engine) Health is creating a clinical decision support platform designed to better manage emerging illnesses, integrating more external data sources into the process of identifying at-risk patients and enabling the two-way exchange of information between providers and public health entities.
  • A partnership between the University of Utah Health Care, Intermountain Healthcare and Duke Health System is providing clinical decision support for timely diagnosis and management of newborn bilirubin according to evidence-based practice. The partners will integrate the app across each member’s EMR.
  • WellSheet has created a web application using machine learning and natural language processing to prioritize important information during a patient visit. Its algorithm simplifies workflows incorporating multiple data sources, including those enabled by FHIR. It then presents information in a single screen.

As I see it, the two contests don’t necessarily need to be run on separate tracks. After all, providers need aggregate data and consumers need prioritized, easy-to-navigate platforms. But either way, this effort seems to have been productive. I’m eager to see the winners of the next phase.

Theranos “Punks” the Scientific Community In First Public Presentation at AACC

Posted on August 2, 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.

Elizabeth Holmes made her first public appearance at #AACC2016 where most thought that she would address the concerns (I’m being nice) around the Theranos products and practices. While most believed that Holmes would not go into much detail, I didn’t see anyone predict that she would not only avoid the controversy, but she also decided to launch a new product. I use the phrase “new product” lightly since it’s similar to lab equipment on the market today, but smaller.

I think this image and tweet describes most people’s reaction to this bait and switch by Theranos and Holmes:
Theranos Punks AACC in First Public Appearance

It’s too bad she chose not to address the controversy before trying to sell another product. Are there any labs out there that will buy this new product until they do address the controversy? I’d hope not. Theranos will have to address it, but for some reason they’re putting it off.

This tweets seems to have captured the sentiment that most will likely feel about any product that Theranos tries to deliver:

E-Patient Update: Is It Appropriate to Trash “Dr. Google”?

Posted on August 1, 2016 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.

Apparently, a lot of professionals have gotten a bit defensive about working with Google-using customers. In fact, when I searched Google recently for the phrase “Don’t confuse your Google search with my” it returned results that finished the phrase with “law degree,” “veterinary degree,” “nursing degree” and even “library degree.” And as you might guess, it also included “medical degree” among its list of professions with a Google grudge.

I first ran across this anti-Dr.-Google sentiment about a year ago, when a physician posted a picture of a coffee mug bearing this slogan on LinkedIn. He defended having the mug on his desk as a joke. But honestly, doc, I don’t think it’s funny. Let me explain.

First, I want to concede a couple of points. Yes, humor means different things to different people, and a joke doesn’t necessarily define a doctor’s character. And to be as fair as possible, I’m sure there are patients who use Web-based materials as an excuse to second-guess medical judgment in ways which are counterproductive and even inappropriate. Knowledge is a good thing, but not everyone has good knowledge filters in place.

That being said, I have, hmmm, perhaps a few questions for clinicians who are amused by this “joke,” including:

  • Wouldn’t people’s health improve if they considered themselves responsible for learning as much as possible about health trends, wellness and/or any conditions they might have?
  • Don’t we want patients to be as engaged as possible when they are talking with their doctors (as well as other clinicians)? And doesn’t that mean being informed about key issues?
  • Does this slogan suggest that patients shouldn’t challenge physicians to explain discrepancies between what they read and what they’re being told?
  • Does this attitude bleed over to a dislike of all consumer-generated health data, even if it’s being generated by an FDA-approved device? If so, have you got a nuanced understanding of these technologies and a well-informed opinion on their merits?

Please understand, I am in no way anti-doctor. The truth is, I trust, admire and rely upon the clinicians who keep my chronic illnesses at bay. I have a sense of the pressures they confront, and have immense respect for their dedication and empathy.

That being said, I need clinicians to collaborate with me and help me learn what I need to know, not discourage and mock my efforts. And I need them to be open to the benefits of new technologies – be they the web-based medical content that didn’t exist when you were in med school, remote monitoring, wearables, sensor-laden t-shirts, mobile apps, artificial intelligence or flying cars.

So, I hope you understand now why I’m offended by that coffee mug. If a doctor dislikes something so elementary as a desire to learn, I doubt we’ll get along.

Do We Underestimate the Power of Smart Phones in Healthcare? – Fun Friday

Posted on July 29, 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.

Smart phones have become a serious societal addiction. In some ways that is bad and no doubt there are plenty of studies that will come out about the negative impacts from cell phone addiction. However, the fact that people always have their cell phone is also a tremendous opportunity for healthcare to really engage their patient. This is what came to mind when I saw these funny cartoons about our addiction to our cell phones.

Cell Phone Addiction - Social Science Research Cartoon

Cell Phone Addiction Cartoon

Thanks Eric Topol for sharing these cartoons.