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Big Data and the Social Good: The Value for Healthcare Organizations

Posted on May 22, 2017 I Written By

The following is a guest blog post by Mike Serrano from NETSCOUT.

It’s a well-known fact that Facebook, Google, and our phone companies collect a lot of information about each of us. This has been the case for a long time, and more often than not it’s to improve the user experience of the services we rely on. If data is shared outside the organization, it’s anonymized to prevent the usage of any one individual from being identified. But it’s understandable while this practice has still sparked a passionate and longstanding debate about privacy and ‘big brother’-style snooping.

What is often forgotten, however, or more likely drowned out by the inevitably growing chorus of privacy concerns, is the opportunity within the big data community for this valuable information to be used for social good. The potential is already there. The question, though, is how different organizations, and particularly the healthcare sector, can take advantage of anonymized user data to benefit society and improve the human condition.

When it comes to healthcare, data from mobile networks holds the biggest opportunity for the patient experience to be dramatically improved. To truly understand how real-time traffic and big data, in the form of historical network usage and traffic patterns, can be used for social good, let’s look at a few possible scenarios – two of which can be accomplished without needing to disclose individual user information at all.

Public health – Getting ahead of an outbreak

What a decade ago would have seemed impossible is very much a reality today. The pervasiveness of the smartphone and how people are using it has fundamentally changed our ability to leverage real-time communications data to the benefit of our society. For many people, smartphones have replaced computers as the primary device to search for information. This has value in itself, as when people use a smartphone it’s possible to place them in context of their community and travel patterns.

Zika is a recent example of a parasite spread by mosquitos that produces flu-like symptoms and can have grave consequences on a developing fetus, causing microcephaly. To control the mosquito population, local vector control agencies place field traps to capture mosquitos and periodically test the mosquitos they collect. This approach has value, but it’s slow and reactive.

What we have learned from flu epidemics is there’s typically an increase in Google searches of “flu symptoms” that emerge just before or at the same time as an outbreak of influenza. Since Zika is a mosquito-born pathogen, it will occur outside of times of the normal spread of influenza, but the initial symptoms are very similar to the common flu.

By monitoring mobile searches for any of a number of unique search terms, it is possible to quickly identify real-time locations where outbreaks may be occurring; thus allowing for a more targeted response by both vector control and public health agencies. In addition, it’s then possible to identify the extent to which migration through the area has occurred, and to where that population has traveled.

When merged with environmental data such as wind patterns, temperature, and precipitation, public health agencies can be extremely targeted about where to deploy resources and the nature of those resources to deploy. Such a targeted and immediate response is only available through the use of real-time network traffic data.

Public safety and medical deployments – disaster response

Recent earthquakes have emphasized the potential death and destruction that natural disasters can create. When buildings collapse first responders’ rush in to look for survivors, putting themselves in harms way as a series of aftershocks could cause additional damage to already weakened structures. But it’s a calculated risk. The search for life must happen quickly, which often means first responders are operating with no knowledge of the potential number of causalities within a building.

To ensure the appropriate allocation of response teams, public safety agencies working in tandem with healthcare organizations could leverage mobile network data. When a mobile phone is turned on, it automatically registers to the mobile network. At this point, the operator knows the number of devices in a certain area based on the placement of the cell tower and the parameters of that tower.

By comparing the last known number of registrants against historical network usage, the operator could guide public safety and relief agencies by understanding the number of known mobile phones in an impacted area. If needed, the operator could also assist in the identification of precisely who may still be in a damaged structure, should that level of detail be required.

Pandemic control – removing the guesswork

All major health organizations understand the next major pandemic is only a plane ride away from arriving on their doorstep. For example, when an international flight lands from a country that’s had a recent outbreak of flu or disease, there could potentially be hundreds of infected passengers on board. Those passengers will exit the plane, grab their luggage, and quickly head into the community – travelling far from the airport and growing the transmission radius significantly.

In a situation such as this, the challenge of containing or managing an outbreak is intrinsically tied to knowing where those passengers end up. How far have they travelled, how did they diffuse into the existing population, and how many circles of control need to be established in order to mitigate the risk?

Big data can address this issue. By working with mobile network operators the local healthcare community can quickly react, taking advantage of big data to deploy public health resources more effectively than they could otherwise. Operators already have access to this information, including where subscribers join the network and their current location, and this data is tremendously valuable when placed in the hands of healthcare professionals looking to stem a viral outbreak. The airline involved could also assist by providing any the phone numbers of passengers once the risk was identified.

The future of big data analysis for healthcare

Understanding human movement and social activity, powered by big data pulled from mobile networks, will have a fundamental role to play in more efficient healthcare response in the future. National, state, and local public health officials should all look to implement initiatives based on the use of big data for social good.

When you compare the use of big data against the current approach – where patient zero arrives at hospital and the local healthcare body has to try and identify who else is at risk based on the patient’s travel patterns and limited information they can provide – the benefits of this new approach are obvious.

As the conversation around the use of big data for healthcare purposes evolves, there will inevitably be new questions over individual privacy. While the examples outlined above do take advantage of subscriber behavior and individual insights – be that search terms of location information – the purpose is to understand populations or communities, not to identify any one subscriber. With this in mind, it is easy to mask subscriber identifiers while preserving the information about the population. Ultimately, the goal is to provide a more efficient utilization and allocation of society’s resources as we work to improve the human condition, not to undermine any one person’s right to privacy.

About Mike Serrano
Mike has over 20 years of experience in the communications industry. He is currently responsible for Service Provider Marketing at NETSCOUT. He began his career at PacBell (now part of at&t) where he designed service plans for the business market and where he was responsible for demand analysis and modeling. His career continued with Lucent technologies where he brought to market the first mobile data service technology. At Alloptic, he was responsible for marketing the industry’s first EPON access solution and bringing to market the first RFOG solution. At O3B Networks, Mike headed up marketing bringing to market the first MEO based constellation of satellites for serving internet service to the Other 3 Billion on the planet. Mike’s work continued at Cisco where he helped to define MediaNet (Videoscape) and the network technology transformation for cable operators. Mike holds a B.S. in Information Resource Management from San Jose State University and an MBA from Santa Clara University

E-Patient Update:  Changing The Patient Data Sharing Culture

Posted on May 19, 2017 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.

I’ve been fighting for what I believe in for most of my life, and that includes getting access to my digital health information. I’ve pleaded with medical practice front-desk staff, gently threatened hospital HIT departments and gotten in the faces of doctors, none of whom ever seem to get why I need all of my data.

I guess you could say that I’m no shrinking violet, and that I don’t give up easily. But lately I’ve gotten a bit, let me say, discouraged when it comes to bringing together all of the data I generate. It doesn’t help that I have a few chronic illnesses, but it’s not easy even for patients with no major issues.

Some these health professionals know something about how EMRs work, how accurate, complete health records facilitate care and how big data analysis can improve population health. But when it comes to helping humble patients participate in this process, they seem to draw a blank.

The bias against sharing patient records with the patients seems to run deep. I once called the PR rep at a hospital EMR vendor and complained casually about my situation, in which a hospital told me that it would take three months to send me records printed from their EMR. (If I’d asked them to send me a CCD directly, the lady’s head might have exploded right there on the phone.)

Though I didn’t ask, the vendor rep got on the phone, reached a VP at the hospital and boom, I had my records. It took a week and a half, a vendor and hospital VP just to get one set of records to one patient. And for most of us it isn’t even that easy.

The methods providers have used to discourage my data requests have been varied. They include that I have to pay $X per page, when state law clearly states that (much lower) $Y is all they can charge. I’ve been told I just have to wait as long as it takes for the HIM department to get around to my request, no matter how time-sensitive the issue. I was even told once that Dr. X simply didn’t share patient records, and that’s that. (I didn’t bother to offer her a primer on state and federal medical records laws.) It gets to be kind of amusing over time, though irritating nonetheless.

Some of these skirmishes can be explained by training gaps or ignorance, certainly. What’s more, even if a provider encourages patient record requests there are still security and privacy issues to navigate. But I believe that what truly underlies provider resistance to giving patients their records is a mix of laziness and fear. In the past, few patients pushed the records issue, so hospitals and medical groups got lazy. Now, patients are getting assertive, and they fear what will happen.

Of course, we all have a right to our medical records, and if patients persist they will almost always get them. But if my experience is any guide, getting those records will remain difficult if attitudes don’t change. The default cultural setting among providers seems to be discomfort and even rebellion when they’re asked to give consumers their healthcare data. My protests won’t change a thing if people are tuning me out.

There’s many reasons for their reaction, including the rise of challenging, self-propelled patients who don’t assume the doctor knows best in all cases. Also, as in any other modern industry, data is power, and physicians in particular are already feeling almost powerless.

That being said, the healthcare industry isn’t going to meet its broad outcomes and efficiency goals unless patients are confident and comfortable with managing their health. Collecting, amassing and reviewing our health information greatly helps patients like me to stay on top of issues, so encumbering our efforts is counter-productive.

To counter such resistance, we need to transform the patient data sharing culture from resistant to supportive. Many health leaders seem to pine for the days when patients could have the data when and if they felt like it, but those days are past. Participating happily in a patient’s data collection efforts needs to become the norm.

If providers hope to meet the transformational goals they’ve set for themselves, they’ll have to help patients get their data as quickly, cheaply and easily as possible. Failing to do this will block or at least slow the progress of much-needed industry reforms, and they’re already a big stretch. Just give patients their data without a fuss – it’s the right thing to do!

Scenarios for Health Care Reform (Part 2 of 2)

Posted on May 18, 2017 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 suggested two scenarios that could promote health care reform. We’ll finish off the scenarios in this part of the article.

Capitalism Disrupts Health Care

In the third scenario, reform is stimulated by an intrepid data science firm that takes on health care with greater success than most of its predecessors. After assembling an impressive analytics toolkit from open source software components–thus simplifying licensing–it approaches health care providers and offers them a deal they can’t refuse: analytics demonstrated to save them money and support their growth, all delivered for free. The data science firm asks in return only that they let it use deidentified data from their patients and practices to build an enhanced service that it will offer paying customers.

Some health care providers balk at the requirement to share data, but their legal and marketing teams explain that they have been doing it for years already with companies whose motives are less commendable. Increasingly, the providers are won over. The analytics service appeals particularly to small, rural, and safety-net providers. Hammered by payment cuts and growing needs among their populations, they are on the edge of going out of business and grasp the service as their last chance to stay in the black.

Participating in the program requires the extraction of data from electronic health records, and some EHR vendors try to stand in the way in order to protect their own monopoly on the data. Some even point to clauses in their licenses that prohibit the sharing. But they get a rude message in return: so valuable are the analytics that the providers are ready to jettison the vendors in a minute. The vendors ultimately go along and even compete on the basis of their ability to connect to the analytics.

Once stability and survival are established, the providers can use the analytics for more and more sophisticated benefits. Unlike the inadequate quality measures currently in use, the analytics provide a robust framework for assessing risk, stratifying populations, and determining how much a provider should be rewarded for treating each patient. Fee-for-outcome becomes standard.

Providers make deals to sign up patients for long-term relationships. Unlike the weak Medicare ACO model, which punishes a provider for things their patients do outside their relationship, the emerging system requires a commitment from the patient to stick with a provider. However, if the patient can demonstrate that she was neglected or failed to receive standard of care, she can switch to another provider and even require the misbehaving provider to cover costs. To hold up their end of this deal, providers find it necessary to reveal their practices and prices. Physician organizations develop quality-measurement platforms such as the recent PRIME registry in family medicine. A race to the top ensues.

What If Nothing Changes?

I’ll finish this upbeat article with a fourth scenario in which we muddle along as we have for years.

The ONC and Centers for Medicare & Medicaid Services continue to swat at waste in the health care system by pushing accountable care. But their ratings penalize safety-net providers, and payments fail to correlate with costs as hoped.

Fee-for-outcome flounders, so health care costs continue to rise to intolerable levels. Already, in Massachusetts, the US state that leads in universal health coverage, 40% of the state budget goes to Medicaid, where likely federal cuts will make it impossible to keep up coverage. Many other states and countries are witnessing the same pattern of rising costs.

The same pressures ride like a tidal wave through the rest of the health care system. Private insurers continue to withdraw from markets or lose money by staying. So either explicitly or through complex and inscrutable regulatory changes, the government allows insurers to cut sick people from their rolls and raise the cost burdens on patients and their employers. As patient rolls shrink, more hospitals close. Political rancor grows as the public watches employer money go into their health insurance instead of wages, and more of their own stagnant incomes go to health care costs, and government budgets tied up in health care instead of education and other social benefits.

Chronic diseases creep through the population, mocking crippled efforts at public health. Rampant obesity among children leads to more and earlier diabetes. Dementia also rises as the population ages, and climate change scatters its effects across all demographics.

Furthermore, when patients realize the costs they must take on to ask for health care, they delay doctor visits until their symptoms are unbearable. More people become disabled or perish, with negative impacts that spread through the economy. Output decline and more families become trapped in poverty. Self-medication for pain and mental illness becomes more popular, with predictable impacts on the opiate addiction crisis. Even our security is affected: the military finds it hard to recruit find healthy soldiers, and our foreign policy depends increasingly on drone strikes that kill civilians and inflame negative attitudes toward the US.

I think that, after considering this scenario, most of us would prefer one of the previous three I laid out in this article. If health care continues to be a major political issue for the next election, experts should try to direct discussion away from the current unproductive rhetoric toward advocacy for solutions. Some who read this article will hopefully feel impelled to apply themselves to one of the positive scenarios and bring it to fruition.

The EHR Market – #HITsm Chat Topic

Posted on May 17, 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.

Note: We’re sorry to share that Anne Zieger (@annezieger) who was suppose to host this week’s chat had some health issues and so we had to change the topic and host. Anne is doing ok and we’ll be sure to have her back as host of a future chat.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 5/19 at Noon ET (9 AM PT). This week’s chat will be hosted by John Lynn (@hospitalEHR) on the topic of “The EHR Market.”

The EHR market has gotten very mature. Thanks to $36 billion in stimulus money fromt he government, most organizations have adopted an EHR. Depending on who you check for EHR market penetration numbers, in the hospital world EHR adoption looks to be well over 90%. The ambulatory world is further behind, but it’s well over 50% adoption now.

Given the maturity of the EHR market, I thought it would be fun to hold an #HITsm chat to discuss the future of the EHR market. Let’s talk about where it’s at today, where it’s going in the future, and what else we can expect from EHR vendors that will now be working in a largely saturated market. What does this mean for the industry and for you as a customer of these EHR vendors?

Join us on Friday May 19th at 12:00pm ET as we discuss the following questions on #HITsm:

The Questions
T1: How would you describe the state of the EHR market today? (specify ambulatory and/or hospital) #HITsm

T2: In what ways will the EHR market evolve over the next 5, 10, 20 years? #HITsm

T3: How much EHR switching do you expect to see in the future? What will be the impact to vendors and customers? #HITsm

T4: Where will we see EHR vendors expand as the market for EHR sales dries up? #HITsm

T5: What must have products will form alongside the EHR or even replace the EHR? #HITsm

Bonus: Which EHR vendors will be gone (or basically gone) in 10 years? #HITsm

Upcoming #HITsm Chat Schedule
5/26 – How APIs Will Change Health IT
Hosted by Chad Johnson (@OchoTex)

6/2 – TBD
Hosted by TBD

6/9 – TBD
Hosted by TBD

6/16 – TBD
Hosted by Danielle Siarri (@innonurse)

6/16 – TBD
Hosted by Megan Janas (@TextraHealth)

We look forward to learning from the #HITsm community! As always let us know if you’d like to host a future #HITsm chat or if you know someone you think we should invite to host.

If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.

Scenarios for Health Care Reform (Part 1 of 2)

Posted on May 16, 2017 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.

All reformers in health care know what the field needs to do; I laid out four years ago the consensus about patient-supplied data, widespread analytics, mHealth, and transparency. Our frustration comes in when trying to crack the current hide-bound system open and create change. Recent interventions by US Republicans to repeal the Affordable Care Act, whatever their effects on costs and insurance coverage, offer no promise to affect workflows or treatment. So this article suggests three potential scenarios where reform could succeed, along with a vision of what will happen if none of them take hold.

Patients Forge Their Own Way Forward

In the first scenario, a tiny group of selfer-trackers, athletes, and empowered patients start a movement that ultimately wins over hundreds of millions of individuals.

These scattered enthusiasts, driven to overcome debilitating health problems or achieve extraordinary athletic feats, start to pursue self-tracking with fanaticism. Consumer or medical-grade devices provide them with ongoing data about their progress, and an open source platform such as HIE of One gives them a personal health record (PHR).

They also take charge of their interactions with the health care system. They find that most primary care providers aren’t interested in the data and concerns they bring, or don’t have time to process those data and concerns in the depth they need, or don’t know how to. Therefore, while preserving standard relationships with primary care providers and specialists where appropriate, the self-trackers seek out doctors and other providers to provide consultation about their personal health programs. A small number of providers recognize an opportunity here and set up practices around these consultations. The interactions look quite different from standard doctor visits. The customers, instead of just submitting themselves to examination and gathering advice, steer the conversation and set the goals.

Power relationships between doctors and customers also start to change. Although traditional patients can (and often do) walk away and effectively boycott a practice with which they’re not comfortable, the new customers use this power to set the agenda and to sort out the health care providers they find beneficial.

The turning point probably comes when someone–probabaly a research facility, because it puts customer needs above business models–invents a cheap, comfortable, and easy-to-use device that meets the basic needs for monitoring and transmitting vital signs. It may rest on the waist or some other place where it can be hidden, so that there is no stigma to wearing it constantly and no reason to reject its use on fashion grounds. A beneficent foundation invests several million dollars to make the device available to schoolchildren or some other needy population, and suddenly the community of empowered patients leaps from a miniscule pool to a mainstream phenomenon.

Researchers join the community in search of subjects for their experiments, and patients offer data to the researchers in the hope of speeding up cures. At all times, the data is under control of the subjects, who help to direct research based on their needs. Analytics start to turn up findings that inform clinical decision support.

I haven’t mentioned the collection of genetic information so far, because it requires more expensive processes, presents numerous privacy risks, and isn’t usually useful–normally it tells you that you have something like a 2% risk of getting a disease instead of the general population’s 1% risk. But where genetic testing is useful, it can definitely fit into this system.

Ultimately, the market for consultants that started out tiny becomes the dominant model for delivering health care. Specialists and hospitals are brought in only when their specific contributions are needed. The savings that result bring down insurance costs for everyone. And chronic disease goes way down as people get quick feedback on their lifestyle choices.

Government Puts Its Foot Down

After a decade of cajoling health care providers to share data and adopt a fee-for-outcome model, only to witness progress at a snail’s pace, the federal government decides to try a totally different tack in this second scenario. As part of the Precision Medicine initiative (which originally planned to sign up one million volunteers), and leveraging the ever-growing database of Medicare data, the Office of the National Coordinator sets up a consortium and runs analytics on top of its data to be shared with all legitimate researchers. The government also promises to share the benefits of the analytics with anyone in the world who adds their data to the database.

The goals of the analytics are multi-faceted, combining fraud checks, a search for cures, and everyday recommendations about improving interventions to save money and treat patients earlier in the disease cycle. The notorious 17-year gap between research findings and widespread implementation shrinks radically. Now, best practices are available to any patient who chooses to participate.

As with the personal health records in the previous scenario, the government database in this scenario creates a research platform of unprecedented size, both in the number of records and the variety of participating researchers.

To further expand the power of the analytics, the government demands exponentially greater transparency not just in medical settings but in all things that make us sick: the food we eat (reversing the rulings that protect manufacturers and restaurants from revealing what they’re putting in our bodies), the air and water that surrounds us, the effects of climate change (a major public health issue, spreading scourges such as mosquito-borne diseases and heat exhaustion), disparities in food and exercise options among neighborhoods, and more. Public awareness leads to improvements in health that lagged for decades.

In the next section of this article, I’ll present a third scenario that achieves reform from a different angle.

Direct, Sequoia Interoperability Projects Continue To Grow

Posted on May 15, 2017 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.

While its fate may still be uncertain – as with any interoperability approach in this day and age – the Direct exchange network seems to be growing at least. At the same time, it looks like the Sequoia Project’s interoperability efforts, including the Carequality Interoperability Framework and its eHealthExchange Network, are also expanding rapidly.

According to a new announcement from DirectTrust, the number of health information service providers who engaged in Direct exchanges increased 63 percent during the first quarter of 2017, to almost 95,000, over the same period in 2016.  And, to put this growth in perspective, there were just 5,627 providers involved in Q1 of 2014.

Meanwhile, the number of trusted Direct addresses which could share PHI grew 21 percent, to 1.4 million, as compared with the same quarter of 2016. Again, for perspective, consider that there were only 182,279 such addresses available three years ago.

In addition, the Trust noted, there were 35.6 million Direct exchange transactions during the quarter, up 76 percent over the same period last year. It expects to see transaction levels hit 140 million by the end of this year.

Also, six organizations joined DirectTrust during the first quarter of 2017, including Sutter Health, the Health Record Banking Alliance, Timmaron Group, Moxe Health, Uticorp and Anne Arundel Medical Center. This brings the total number of members to 124.

Of course, DirectTrust isn’t the only interoperability group throwing numbers around. In fact, Seqouia recently issued a statement touting its growth numbers as well (on the same day as the Direct announcement, natch).

On that day, the Project announced that the Carequality Interoperability Framework had been implemented by more than 19,000 clinics, 800 hospitals and 250,000 providers.

It also noted that its eHealth Exchange Network, a healthcare data sharing network, had grown 35 percent over the past year, connecting participants in 65 percent of all US hospitals, 46 regional and state HIEs, 50,000 medical groups, more than 3,400 dialysis centers and 8,300 pharmacies. This links together more than 109, million patients, Sequoia reported.

So what does all of this mean? At the moment, it’s still hard to tell:

  • While Direct and Sequoia are expanding pretty quickly, there’s few phenomena to which we can compare their growth.
  • Carequality and CommonWell agreed late last year to share data across each others’ networks, so comparing their transaction levels to other entities would probably be deceiving.
  • Though the groups’ lists of participating providers may be accurate, many of those providers could be participating in other efforts and therefore be counted multiple times.
  • We still aren’t sure what metrics really matter when it comes to measuring interoperability success. Is it the number of transactions initiated by a provider? The number of data flows received? The number of docs and facilities who do both and/or incorporate the data into their EMR?

As I see it, the real work going forward will be for industry leaders to decide what kind of performance stats actually equate to interoperability success. Otherwise, we may not just be missing health sharing bullseyes, we may be firing at different targets.

ZDoggMD Talks Suicide

Posted on May 12, 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.

I was looking to do a Fun Friday post this week and so I went over to see if ZDoggMD had a new parody video I could share with the community. Instead of finding a Fun Friday video, I came across this episode of ZDogg’s Incident Report show and podcast that talks about suicide, mental health, and the new Netflix show called 13 Reasons Why.

No doubt this is just the start of the conversation, but I was really glad to see someone with a platform like ZDoggMD talking about mental health and suicide. Check out the conversation below:

I hope that ZDogg covers this topic more in the future and brings on some experts in the area. It’s a hard topic for him since his shows are usually so full of humor and sarcasm, but it’s ok for him to turn that off for a few shows here and there.

On the video, ZDogg talks about one of my friends that committed suicide in downtown vegas. It was a hard experience for many of us who knew him and had had no idea that he was suffering in silence. I know that many readers of this site have their own stories. Of course, I don’t think I need to mention how many doctors are suffering in silence as well. It’s a tragic thing and hopefully shows like the one above will help us talk about it more and find better solutions and support.

MUMPS and Healthcare

Posted on May 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.

Leave it to David Chou to point out how odd it is to work in healthcare IT. What’s shocking about the image David Chou shared above is that there are so many languages listed. However, despite the vast number of languages listed, MUMPS is so far off the radar of most tech people that they literally didn’t care about it enough to add it to the chart. That’s pretty sad for those of us who care about healthcare.

If you want to get another view about the challenge of so much of healthcare being run on MUMPS, check out this MUMPS thread on Hacker News. For those not familiar with Hacker News, it’s a site that was started by YCombinator and has grown into a community of some of the most progressive tech startup people in the world. The Hacker News thread is really long, so for those who don’t want to read it all the message is simple: MUMPS? What’s that? That’s awful!

To be fair, there were a few dissenting voices who commented on the great features of MUMPS. However, I have to admit that these people sound a little bit like those who espouse the benefits of the fax machine. Sure, it has some extremely beneficial features, but it’s downsides far outweigh the benefits described.

The reality is that we’re not going to get away from MUMPS in healthcare. When you realize that Epic, MEDITECH, Vista (VA), and Intersystems all use some form of MUMPS (or M as they prefer to call it now), you can see why MUMPS will be part of healthcare for a long time to come.

What’s more disappointing to me after reading the Hacker News thread was how people described the culture of the EHR vendors that use MUMPS. They really described it as uninterested in even exploring other more modern options that could help them better able to innovate their products and serve their customers.

Plus, it also hurts to hear so many programmers in the thread talk about how they shunned healthcare because they saw working on something like MUMPS as a career killer. I’m sure this is a common refrain for most developers out there. It’s disheartening to think that many EHR vendors will never benefit from the best developers as long as we’re on MUMPS.

I’m sure MUMPS was great in its day. It seems to have been a wise choice by Epic to start using it when I was born back in 1979. However, can you imagine the technical debt that’s accumulated all these years? Is it any wonder that innovation in healthcare works so slow?

What’s a Patient?

Posted on May 10, 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.

For quite a while I’ve been pushing the idea that healthcare needs to move beyond treating patients. Said another way, we need to move beyond just helping people who have health problems which are causing them to complain and move into treating patients that otherwise feel healthy.

Said another way, Wanda Health once told me “The definition of a healthy patient is someone who’s not been studied long enough.”

If you look long enough and hard enough, we all have health issues or we’re at risk for health issues. There’s always something that could be done to help all of us be healthier. That’s a principle that healthcare hasn’t embraced because our reimbursement models are focused on treating a patients’ chief complaint.

In another conversation with NantHealth, they suggested the idea that we should work towards knowing the patient so well that you know the treatment they need before you even physically see the patient.

These two ideas go naturally together and redefine our current definition of patient. In the above context, all of us would be considered patients since I have little doubt that all of us have health issues that could be addressed if we only knew the current state of our health better.

While NantHealth’s taken a number of stock hits lately for overpromising and under delivering, the concept I heard them describe is one that will become a reality. It could be fair to say that their company was too early for such a big vision, but it’s inspiring to think about creating technology and collecting enough data on a patient that you already know how to help the patient before they even come into the office. That would completely change the office visit paradox that we know today.

This is an ambitious vision, but it doesn’t seem like a massive stretch of the imagination either. That’s what makes it so exciting to me. Now imagine trying to do something like this in the previous paper chart world. Yeah, it’s pretty funny to just even think about it. Same goes with what we call clinical decision support today.

Accelerating Decision-Making in Healthcare: How Health Systems Choose Innovative Solutions – #HITsm Chat Topic

Posted on May 9, 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.

We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 5/12 at Noon ET (9 AM PT). This week’s chat will be hosted by Bruce Brandes from Lucro Solutions on the topic of “Accelerating Decision-Making in Healthcare: How Health Systems Choose Innovative Solutions”.

To be competitive in today’s digital healthcare economy, providers, hospitals and health plans need to leverage existing and emerging products offered by a growing base of vendors. But the healthcare market is saturated with products and services with new vendors entering the market seemingly every day. The people involved with identifying and selecting appropriate products and services become overwhelmed by all that’s available. Cutting through the noise and separating the wheat from the chaff often results in scars when vendors oversell their offerings and ultimately under-deliver on their promises.

To be able to execute faster on innovation in healthcare, those charged with identifying, selecting and implementing healthcare products and services must filter the universe of shiny things and make better decisions faster. Mistakes can be costly. In the instance of certain products or services, mistakes could be fatal; literally.

In this tweetchat, we’ll explore topics related to the discovery, organization, collaboration and prioritization of healthcare products and services offered by vendors based on defined strategic initiatives and the healthcare organizations that purchase, implement and use them.

Join us on Friday May 12th at 12:00pm ET as we discuss the following questions on #HITsm:

The Questions
T1: How do you define and align organizational priorities for which you seek #HealthIT solutions? #HITsm

T2: How can you filter the “noise” to discover and evaluate #healthIT vendors relevant to your priorities? #HITsm

T3: What’s more efficient way to collaborate w/ trusted colleagues to support your decisions regarding #HealthIT products/services? #HITsm

T4: How do you leverage the scale and experience of your organization to drive standardization and “de-risk” decisions? #HITsm

T5: What type of vendor content, materials & actions help you reach a decision in the most expedient manner? #HITsm

Bonus: What are the advantages and disadvantages of your RFI / RFP process? #HITsm

Upcoming #HITsm Chat Schedule
5/19 – Patient Education Using Healthcare Social Media
Hosted by Anne Zieger (@annezieger)

5/26 – TBD
Hosted by Chad Johnson (@OchoTex)

We look forward to learning from the #HITsm community! As always let us know if you have ideas for how to make #HITsm better.

If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.