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New Study Suggests That HIEs Deliver Value by Aggregating Patient Data

Posted on March 5, 2018 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.

Historically, I’ve been pretty skeptical about the benefits that HIEs offer, not because the concept was flawed, but that the execution was uncertain. Toss in the fact that few have figured out how to be self-supporting financially, and you have a very shaky business model on your hands. But maybe, at long last, we’re discovering better uses for the vast amount of data HIEs have been trading.

New research by one exchange suggests that some of the key value they offer is aggregating patient data from multiple providers into a longitudinal view of patients. The research, completed by the Kansas Health Information Network and Diameter Health suggests that the Qualified Clinical Data Registries promoted by MACRA/QPP could be a winning approach.

To conduct the research, the partners extracted data from the KHIN exchange on primary care practices in which more than 50,000 patients visited toward 214 care sites in 2016 and 2017. This is certainly interesting, as most of the multi-site studies I’ve seen on this scale are done within a single provider’s network. It’s also notable that the data is relatively fresh, rather than relying on, say, Medicare data which is often several years older.

According to KHIN, using interoperable interfaces to providers and collecting near real-time clinical data makes prompt quality measure calculation possible. According to KHIN executive director Laura McCrary, Ed.D., this marks a significant change from current methods. “This [approach is in stark contrast to the current model which computes quality measures from only the data in the provider’s EHR,” she notes.

FWIW, the two research partners will be delivering a presentation on the research study at the HIMSS18 conference on Friday, March 9, from 12 to 1 PM. I’m betting it will offer some interesting insights.

But even if you can’t make it to this presentation, it’s still worth noting that it emphasizes the increasing importance of the longitudinal patient record. Eventually, under value-based care, it will become critical to have access not only to a single provider’s EHR data, but rather a fuller data set which also includes connected health/wearables data, data from payer claims, overarching population health data and more. And obviously, HIEs play a major role in making this happen.

Like other pundits, I’d go so far to say that without developing this kind of robust longitudinal patient record, which includes virtually every source of relevant patient data, health systems and providers won’t be able to manage patients well enough to meet their individual patient or population health goals.

If HIEs can help us get there, more power to them.

Some Of The Questions I Plan To Ask At #HIMSS18

Posted on February 23, 2018 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.

As always, this year’s HIMSS event will feature enough noise, sound and color to overwhelm your senses for months afterward. And talk about a big space to tread — I’ve come away with blisters more than once after attending.

Nonetheless, in my book it’s always worth attending the show. While no one vendor or session might blow you away, finding out directly what trends and products generated the most buzz is always good. The key is not only to attend the right educational sessions or meet the right people but to figure out how companies are making decisions.

Below, here are some of the questions that I hope to ask (and hopefully find answers) at the show. If you have other questions to suggest I’d love to bring them with me to the show —  the way I see it, the more the merrier!

-Anne

Blockchain

Vendors:  What functions does blockchain perform in your solution and what are the benefits of these additions? What made that blockchain the best technology choice for getting the job done? What challenges have you faced in developing a platform that integrates blockchain technology, and how are you addressing them? Is blockchain the most cost-efficient way of accomplishing the task you have in mind? What problems is blockchain best suited to address?

Providers: Have you rolled out any blockchain-based systems? If you haven’t currently deployed blockchain technology, do you expect to do so the future? When do you think that will happen? How will you know when it’s time to do so? What benefits do you think it will offer to your organization, and why? Do you think blockchain implementations could generate a significant level of additional server infrastructure overhead?

AI

Vendors: What makes your approach to healthcare AI unique and/or beneficial?  What is involved in integrating your AI product or service with existing provider technology, and how long does it usually take? Do providers have to do this themselves or do you help? Did you develop your own algorithms, license your AI engine or partner with someone else deliver it? Can you share any examples of how your customers have benefited by using AI?

Providers: What potential do you think AI has to change the way you deliver care? What specific benefits can AI offer your organization? Do you think healthcare AI applications are maturing, and if not how will you know when they have? What types of AI applications potentially interest you, and are you pilot-testing any of them?

Interoperability

Vendors:  How does your solution overcome barriers still remaining to full health data sharing between all healthcare industry participants? What do you think are the biggest interoperability challenges the industry faces? Does your solution require providers to make any significant changes to their infrastructure or call for advanced integration with existing systems? How long does it typically take for customers to go live with your interoperability solution, and how much does it cost on average? In an ideal world, what would interoperability between health data partners look like?

Providers: Do you consider yourself to have achieved full, partial or little/no health data interoperability between you and your partners? Are you happy with the results you’ve gotten from your interoperability efforts to date? What are the biggest benefits you’ve seen from achieving full or partial interoperability with other providers? Have you experienced any major failures in rolling out interoperability? If so, what damage did they do if any? Do you think interoperability is a prerequisite to delivering value-based care and/or population health management?

What topics are you looking forward to hearing about at #HIMSS18? What questions would you like asked? Share them in the comments and I’ll see what I can do to find answers.

Health IT Leaders Spending On Security, Not AI And Wearables

Posted on December 18, 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 breakout technologies like wearables and AI are hot, health system leaders don’t seem to be that excited about adopting them, according to a new study which reached out to more than 20 US health systems.

Nine out of 10 health systems said they increased their spending on cybersecurity technology, according to research by the Center for Connected Medicine (CCM) in partnership with the Health Management Academy.

However, many other emerging technologies don’t seem to be making the cut. For example, despite the publicity it’s received, two-thirds of health IT leaders said using AI was a low or very low priority. It seems that they don’t see a business model for using it.

The same goes for many other technologies that fascinate analysts and editors. For example, while many observers which expect otherwise, less than a quarter of respondents (17%) were paying much attention to wearables or making any bets on mobile health apps (21%).

When it comes to telemedicine, hospitals and health systems noted that they were in a bind. Less than half said they receive reimbursement for virtual consults (39%) or remote monitoring (46%}. Things may resolve next year, however. Seventy-one percent of those not getting paid right now expect to be reimbursed for such care in 2018.

Despite all of this pessimism about the latest emerging technologies, health IT leaders were somewhat optimistic about the benefits of predictive analytics, with more than half of respondents using or planning to begin using genomic testing for personalized medicine. The study reported that many of these episodes will be focused on oncology, anesthesia and pharmacogenetics.

What should we make of these results? After all, many seem to fly in the face of predictions industry watchers have offered.

Well, for one thing, it’s good to see that hospitals and health systems are engaging in long-overdue beefing up of their security infrastructure. As we’ve noted here in the past, hospital spending on cybersecurity has been meager at best.

Another thing is that while a few innovative hospitals are taking patient-generated health data seriously, many others are taking a rather conservative position here. While nobody seems to disagree that such data will change the business, it seems many hospitals are waiting for somebody else to take the risks inherent in investing in any new data scheme.

Finally, it seems that we are seeing a critical mass of influential hospitals that expect good things from telemedicine going forward. We are already seeing some large, influential academic medical centers treat virtual care as a routine part of their service offerings and a way to minimize gaps in care.

All told, it seems that at the moment, study respondents are less interested in sexy new innovations than the VCs showering them with money. That being said, it looks like many of these emerging strategies might pay off in 2018. It should be an interesting year.

The Future Of Telemedicine Doesn’t Depend On Health Plans Anymore

Posted on December 6, 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.

For as long as I can remember, the growth of telemedicine depended largely on overcoming two obstacles: bandwidth and reimbursement. Now, both are on the verge of melting away.

One, the availability of broadband, has largely been addressed, though there are certainly areas of the US where broadband is harder to get than it should be. Having lived through a time when the very idea of widely available consumer broadband blew our minds, it’s amazing to say this, but we’ve largely solved the problem in the United States.

The other, the willingness of insurers to pay for telemedicine services, is still something of an issue and will be for a while. However, it won’t stay that way for too much longer in my opinion.

Yes, over the short term it still matters whether a telemedicine visit is going to be funded by a payer –after all, if a clinician is going to deliver services somebody has to pay for their time. But there are good reasons why this will not continue to be an issue.

For one thing, as the direct-to-consumer models have demonstrated, patients are increasingly willing to pay for telemedical care out-of-pocket. Customers of sites like HealthTap and Teladoc won’t pay top dollar for such services, but it seems apparent that they’re willing to engage with and stay interested in solving certain problems this way (such as, for example, getting a personal illness triaged and treated without having to skip work the next day).

Another way telemedicine services have changed, from what I can see, is that health systems and hospitals are beginning to integrate it with their other service lines as a routine part of delivering care. Virtual consults are no longer this “weird” thing they do on the side, but a standard approach to addressing common health problems, especially chronic illness.

Then, of course, there’s the most important factor taking control of telemedicine away from health plans: the need to use it to achieve population health management goals. While its use is still a little bit lopsided at present, as healthcare organizations aren’t sure how to optimize telehealth initiatives, eventually they’ll get the formula right, and that will include using it as a way of tying together a seamless value-based delivery network.

In fact, I’d go so far as to say that without the reach, flexibility and low cost of telehealth delivery, building out population health management schemes might be almost impossible in the future. Having specialists available to address urgent matters and say, for example, rural areas will be critical on the one hand, while making specialists need for chronic care (such as endocrinologists) accessible to unwell urban patients with travel concerns.

Despite the growing adoption of telemedicine by providers, it may be 5 to 10 years or so before it has its fullest impact, a period during which health plans gradually accept that the growth of this technology isn’t up to them anymore. But the day will without a doubt arise soon enough that “telemedicine” is just known as medicine.

Health IT Continues To Drive Healthcare Leaders’ Agenda

Posted on October 23, 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.

A new study laying out opportunities, challenges and issues in healthcare likely to emerge in 2018 demonstrates that health IT is very much top of mind for healthcare leaders.

The 2018 HCEG Top 10 list, which is published by the Healthcare Executive Group, was created based on feedback from executives at its 2017 Annual Forum in Nashville, TN. Participants included health plans, health systems and provider organizations.

The top item on the list was “Clinical and Data Analytics,” which the list describes as leveraging big data with clinical evidence to segment populations, manage health and drive decisions. The second-place slot was occupied by “Population Health Services Organizations,” which, it says, operationalize population health strategy and chronic care management, drive clinical innovation and integrate social determinants of health.

The list also included “Harnessing Mobile Health Technology,” which included improving disease management and member engagement in data collection/distribution; “The Engaged Digital Consumer,” which by its definition includes HSAs, member/patient portals and health and wellness education materials; and cybersecurity.

Other hot issues named by the group include value-based payments, cost transparency, total consumer health, healthcare reform and addressing pharmacy costs.

So, readers, do you agree with HCEG’s priorities? Has the list left off any important topics?

In my case, I’d probably add a few items to list. For example, I may be getting ahead of the industry, but I’d argue that healthcare AI-related technologies might belong there. While there’s a whole separate article to be written here, in short, I believe that both AI-driven data analytics and consumer-facing technologies like medical chatbots have tremendous potential.

Also, I was surprised to see that care coordination improvements didn’t top respondents’ list of concerns. Admittedly, some of the list items might involve taking coordination to the next level, but the executives apparently didn’t identify it as a top priority.

Finally, as unsexy as the topic is for most, I would have thought that some form of health IT infrastructure spending or broader IT investment concerns might rise to the top of this list. Even if these executives didn’t discuss it, my sense from looking at multiple information sources is that providers are, and will continue to be, hard-pressed to allocate enough funds for IT.

Of course, if the executives involved can address even a few of their existing top 10 items next year, they’ll be doing pretty well. For example, we all know that providers‘ ability to manage value-based contracting is minimal in many cases, so making progress would be worthwhile. Participants like hospitals and clinics still need time to get their act together on value-based care, and many are unlikely to be on top of things by 2018.

There are also problems, like population health management, which involve processes rather than a destination. Providers will be struggling to address it well beyond 2018. That being said, it’d be great if healthcare execs could improve their results next year.

Nit-picking aside, HCEG’s Top 10 list is largely dead-on. The question is whether will be able to step up and address all of these things. Fingers crossed!

Searching EMR For Risk-Related Words Can Improve Care Coordination

Posted on September 18, 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.

Though healthcare organizations are working on the problem, they’re still not as good at care coordination as they should be. It’s already an issue and will only get worse under value-based care schemes, in which the ability to coordinate care effectively could be a critical issue for providers.

Admittedly, there’s no easy way to solve care coordination problems, but new research suggests that basic health IT tools might be able to help. The researchers found that digging out important words from EMRs can help providers target patients needing extra care management and coordination.

The article, which appears in JMIR Medical Informatics, notes that most care coordination programs have a blind spot when it comes to identifying cases demanding extra coordination. “Care coordination programs have traditionally focused on medically complex patients, identifying patients that qualify by analyzing formatted clinical data and claims data,” the authors wrote. “However, not all clinically relevant data reside in claims and formatted data.”

For example, they say, relying on formatted records may cause providers to miss psychosocial risk factors such as social determinants of health, mental health disorder, and substance abuse disorders. “[This data is] less amenable to rapid and systematic data analyses, as these data are often not collected or stored as formatted data,” the authors note.

To address this issue, the researchers set out to identify psychosocial risk factors buried within a patient’s EHR using word recognition software. They used a tool known as the Queriable Patient Inference Dossier (QPID) to scan EHRs for terms describing high-risk conditions in patients already in care coordination programs.

After going through the review process, the researchers found 22 EHR-available search terms related to psychosocial high-risk status. When they were able to find nine or more of these terms in the patient’s EHR, it predicted that a patient would meet criteria for participation in a care coordination program. Presumably, this approach allowed care managers and clinicians to find patients who hadn’t been identified by existing care coordination outreach efforts.

I think this article is valuable, as it outlines a way to improve care coordination programs without leaping over tall buildings. Obviously, we’re going to see a lot more emphasis on harvesting information from structured data, tools like artificial intelligence, and natural language processing. That makes sense. After all, these technologies allow healthcare organizations to enjoy both the clear organization of structured data and analytical options available when examining pure data sets. You can have your cake and eat it too.

Obviously, we’re going to see a lot more emphasis on harvesting information from structured data, tools like artificial intelligence and natural language processing. That makes sense. After all, these technologies allow healthcare organizations to enjoy both the clear organization of structured data and analytical options available when examining pure data sets. You can have your cake and eat it too.

Still, it’s good to know that you can get meaningful information from EHRs using a comparatively simple tool. In this case, parsing patient medical records for a couple dozen keywords helped the authors find patients that might have otherwise been missed. This can only be good news.

Yes, there’s no doubt we’ll keep on pushing the limits of predictive analytics, healthcare AI, machine learning and other techniques for taming wild databases. In the meantime, it’s good to know that we can make incremental progress in improving care using simpler tools.

Are EMR Vendors Really This Clueless?

Posted on August 24, 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 know that EMR vendors don’t always understand their end-users as well as they should. That’s a shame, but it’s likely to happen given how far apart their day-to-day lives are. Still, I was truly taken aback by the following.

In the introduction to a report on nurse perceptions of EHRs, researchers shared some words on their market research philosophy. I don’t think the writers intended to criticize anyone, but nonetheless, the vendors don’t come out looking very good in the process.

“Some (mainly vendors) have questioned why we conduct research to front-line users of core HIT systems, such as physicians, nurses, billers, schedulers etc.,” they wrote. “They argue that only the high-ranking decision-makers matter when it comes to tracking customer satisfaction (NPS) and winning a greater piece of the market. We’ve had senior leaders among prominent vendors essentially tell us that they don’t care about what frontline users have to say.”

Okay. (Taking a breath, letting out the bad air, taking in the good.) I don’t wanna go off on a rant here, but are those vendors completely stupid?  Are they trying to destroy whatever credibility they have left among end users?  Are they hinting that we should just sell their companies’ stocks short and live in the Bahamas the rest of our days?

To be clear, the researchers actually put a reasonably cheerful spin on all of this. They suggest, ever so politely, that if vendors pay attention to end users, they will “unlock a competitive gold mine.”  “Yes, it would require additional development resources, adjusting some roadmap goals, and resetting internal expectations, but the payoff is a quantifiable Unique Selling Proposition that just doesn’t exist very often in HIT – having a highly-rated platform among users,” they note, quite reasonably.

Being me, however, I’ll be a bit less nice. Vendors, I’m amazed we still have a health IT industry if that’s really how your leaders really think. It takes a uniquely dumb organization to keep selling products the actual users hate, and an even dumber one to ignore user feedback that could fix the problem.

While healthcare organizations may have rammed a jerry-rigged mess down users’ throats for a while, that can’t last forever — in fact, the day of reckoning is coming soon. As EMR users become more confident, wired and demanding, they’ll demand that their systems actually work for them. Imagine that!

This reckoning won’t just impact your future plans, it will come to bite you now.

If you were hoping to turn your multi-year contract into a nice, fat revenue stream, forget it. Users will scream (and inflict some pain) if the EMR is lousy to use. In a population health-based world calling for everyone to be clinical data power users, they’ll have far more clout. You’ll either spend tons of time fixing and updating things or lose your contract if your customer has an out. Either way, you’ve hollowed out your revenue stream. Good luck with that.

Care Coordination Tech Still Needs Work

Posted on July 26, 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.

Virtually all of you would agree that we’ll have to do a better job of care coordination if we hope to meet our patient outcomes goals. And logically enough, most of us are hoping that technology will help us make this happen.  But from what I’ve seen, it isn’t going to happen anytime soon.

Every now and then, I get a press release from a company that says a company’s tech has solved at least some part of the industry’s care coordination problem. Today, the company was featured in a release from Baylor College of Medicine, where a physician has launched a mobile software venture focused on preventing miscommunication between patient care team members.

The company, ConsultLink, has developed a mobile platform that manages patient handoffs, consults and care team collaboration. It was founded by Dr. Alexander Pastuszak, an assistant professor of urology at Baylor, in 2013.

As with every other digital care coordination platform I’ve heard about – and I’ve encountered at least a dozen – the ConsultLink platform seems to have some worthwhile features. I was especially interested in its analytics capability, as well as its partnership with Redox, an EMR integration firm which has gotten a lot of attention of late.

The thing is, I’ve heard all this before, in one form or another. I’m not suggesting that ConsultLink doesn’t have what it takes. However, it’s been my observation if market space attracts dozens of competitors, the very basics of how they should attack the problem are still up for grabs.

As I suspected it would, a casual Google search turned up several other interesting players, including:

  • ChartSpan Medical Technologies: The Greenville, South Carolina-based company has developed a platform which includes practice management software, mobile patient engagement and records management tools. It offers a chronic care management solution which is designed to coordinate care between all providers.
  • MyHealthDirect: Nashville’s MyHealthDirect, a relatively early entrant launched in 2006, describes itself as focusing consumer healthcare access solutions. Its version of digital care coordination includes online scheduling systems, referral management tools and event-driven analytics, which it delivers on behalf of health systems, providers and payers.
  • Spruce Health: Spruce Health, which is based in San Francisco, centralizes care communication around mobile devices. Its platform includes a shared inbox for all patient and team communication, collaborative messaging, telemedicine support and mobile payment options.

No doubt there are dozens more that aren’t as good at SEO. As these vendors compete, the template for a care coordination platform is evolving moment by moment. As with other tech niches, companies are jumping into the fray with technology perhaps designed for other purposes. Others are hoping to set a new standard for how care coordination platforms work. There’s nothing wrong with that, but its likely to keep the core feature set for digital coordination fluid for quite some time.

I don’t doubt among the companies I’ve described, there’s a lot of good and useful ideas. But to me, the fact that so many players are trying to define the concept of digital care coordination suggests that it has some growing up to do.

Tips on Implementing Text Analytics in Healthcare

Posted on July 6, 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.

Most of us would agree that extracting clinical data from unstructured physician notes would be great. At present, few organizations have deployed such tools, nor have EMR vendors come to the rescue en masse, and the conventional wisdom holds that text analytics would be crazy expensive. I’ve always suspected that digging out and analyzing this data may be worth the trouble, however.

That’s why I really dug a recent article from HealthCatalyst’s Eric Just, which seemed to offer some worthwhile ideas on how to use text analytics effectively. Just, who is senior vice president of product development, made a good case for giving this approach a try. (Note: HealthCatalyst and partner Regenstrief Institute offer solutions in this area.)

The article includes an interesting case study explaining how healthcare text analytics performed head-to-head against traditional research methods.

It tells the story of a team of analysts in Indiana that set out to identify peripheral artery disease (PAD) patients across two health systems. At first gasp, things weren’t going well. When researchers looked at EMR and claims data, they found that failed to identify over 75% of patients with this condition, but text analytics improved their results dramatically.

Using ICD and CPT codes for PAD, and standard EMR data searches, team members had identified less than 10,000 patients with the disorder. However, once they developed a natural language processing tool designed to sift through text-based data, they discovered that there were at least 41,000 PAD patients in the population they were studying.

To get this kind of results, Just says, there are three key features a medical text analytics tool should have:

  • The medical text analytics software should tailor results to a given user’s needs. For example, he notes that if the user doesn’t have permission to view PHI, the analytics tool should display only nonprivate data.
  • Medical text analytics tools should integrate medical terminology to improve the scope of searches. For example, when a user does a search on the term “diabetes” the search tool should automatically be capable of displaying results for “NIDDM,” as this broadens the search to include more relevant content.
  • Text analytics algorithms should do more than just find relevant terms — they should provide context as well as content. For example, a search for patients with “pneumonia,” done with considering context, would also bring up phrases like “no history of pneumonia.” A better tool would be able to rule out phrases like “no history of pneumonia,” or “family history of pneumonia” from a search for patients who have been treated for this illness.

The piece goes into far more detail than I can summarize here, so I recommend you read it in full if you’re interested in leveraging text analytics for your organization.

But for what it’s worth, I came away from the piece with the sense that analyzing your clinical textual information is well worth the trouble — particularly if EMR vendors being to add such tools to their systems. After all, when it comes to improving outcomes, we need all the help we can get.

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