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Will UnitedHealth’s New Personal Health Record Make An Impact?

Posted on October 26, 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.

Though the idea of a personal health record was a hot thing for a while, it didn’t become the fixture of the healthcare market that pundits had predicted. In fact, as many readers will recall, even deep pockets like Google and Microsoft couldn’t get their users to sign on to their PHRs en masse.

One of the main reasons the PHR model didn’t take is that people simply didn’t want to use them. In fact, at least at the time, the PHR was almost entirely a solution in search of a problem. After all, if a health data power user and patient advocate like myself didn’t want one, what hope did PHR backers have of interesting your average Joe Blow in aggregating their health data online?

Over time, however, the personal health data landscape has changed, with patient records becoming a bit more portable. While consumers still aren’t beating down the doors to get their own PHR, those who are interested in pulling together their medical records electronically have better access to their history.

Not only that, wearables makers like Apple and Fitbit are sweetening the pot, primarily by helping people pull self-generated data into their health record. Arguably, patient-generated data may not be as valuable as traditional records just yet, but consumers are likely to find it more interesting than the jargon-laden text found in provider records.

Given recent developments like these, I wasn’t entirely surprised to learn that UnitedHealth Group is picking up the PHR torch. According to an article in MedCity News, the giant payer plans to launch what sounds like an updated PHR platform next year to its 50 million benefited plan members.

Apparently, on an earnings call last week UnitedHealth CEO Dave Wichmann said that the company will launch a “fully integrated and fully portable individual health record” in 2019. Notably, this is not just a data repository, but rather an interactive tool that “delivers personalized next-best health actions to people and their caregivers.”

The new health record will be based on UnitedHealth’s Rally health and wellness platform, which the insurer picked up when it acquired Audax Health in 2014. The platform, which has 20 million registered users, works to influence members to perform healthy behaviors in exchange for the incentive dollars,

Over time, Wichmann said, UHG intends to build Rally into a platform which collects and distributes “deeply personalized” health information to individual members, MedCity reported. The idea behind this effort is to highlight gaps in care and help patients assess the care that they get.  Wichmann told earnings call listeners that the platform data will be packaged and presented to clinicians in a form similar to that used by existing EHRs.

UHG’s plans here are certainly worth keeping an eye on over the next year or two. I have no doubt that the nation’s largest commercial payer has some idea of how to format data and make it digestible by systems like Cerner and Epic.

But while patients have become a bit more familiar with the benefits of having their health data on hand, we’re not exactly seeing consumers stampede the providers demanding their own health record either, and I’m far from convinced that this effort will win new converts.

My skepticism comes partly from first-hand experience. As a recent UnitedHealth beneficiary, I’ve used the Rally application, and I didn’t find it all that motivating. Honestly, I doubt any online platform will make much of an impact on patient health on its own, as the reasons for many health issues are multifactorial and can’t be resolved by handing one of us a few Rally bucks.

Personal gripes aside, though, the bigger question remains whether consumers think they’ll get something valuable out of using the new UHG tool. As always, you can never count on them coming just because you built it.

Number Of Health Data Breaches Grew Steadily Over Last Several Years

Posted on October 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.

New research has found that while the number of patient records exposed per breach has varied widely, the number of health data breaches reported grew substantially between 2010 and 2017.

The study, which was conducted by researchers with Massachusetts General Hospital, was published in JAMA. Its aim was to look at the changes in data breach patterns as EHRs have come into wider use.

The authors analyzed 2,149 reported breaches over the previous seven years. The number of records breached for incident varied from 500 to almost 79 million patient records.

Researchers behind the study put breaches reported in three categories: those taking place at healthcare provider sites, within health plans, and at business associate locations.

One thing that stuck out from among the data points was that over that seven-year period, the number of breaches increased from 199 the first year to 344 in 2017. During that period, the only year that did not see an increase in incident volume was 2015.

Another notable if unsurprising conclusion drawn by the researchers was that while 70% of all breaches took place within provider organizations, incidents involving health plans accounted for 63% of all breached records.

Overall, the greatest number of patient records breached was due to compromised network servers or email messages. However, the top reasons for breaches have varied from year-to-year, the analysis found.

For example, the most common type of breach reported in 2010 was theft of physical records. The most commonly breached type of media that year was laptop computer data storage, followed by paper and film records.

Meanwhile, by 2017 data hacking or other information technology incidents accounted for the largest number of breaches, followed by unauthorized access to or disclosure of patient data. In addition, a large number of breaches could be attributed to compromised network servers or email messages.

The number of patient records exposed differed depending on what media was breached. For example, while the total of 510 breaches of paper and film records impact about 3.4 million patient records, 410 breaches of network servers affected nearly 140 million records.

Healthcare AI Could Generate $150B In Savings By 2025

Posted on September 27, 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.

Is the buzz around healthcare AI solutions largely hype, or can they deliver measurable benefits? Lest you think it’s too soon to tell, check out the following.

According to a new report from market analyst firm Frost & Sullivan, AI and cognitive computing will generate $150 billion in savings for the healthcare business by 2025.  Frost researchers expect the total AI market to grow to $6.16 billion between 2018 and 2022.

The analyst firm estimates that at present, only 15% to 20% of payers, providers and pharmaceutical companies have been using AI actively to change healthcare delivery. However, its researchers seem to think that this will change rapidly over the next few years.

One of the most interesting applications for healthcare AI that Frost cites is the use of AI in precision medicine, an area which clearly has a tremendous upside potential for both patients and institutions.

In this scenario, the AI integrates a patient’s genomic, clinical, financial and behavioral data, then cross-references the data with the latest academic research evidence and regulatory guidelines. Ultimately, the AI would create personalized treatment pathways for high-risk, high-cost patient populations, according to Koustav Chatterjee, an industry analyst focused on transformational health.

In addition, researchers could use AI to expedite the process of clinical trial eligibility assessment and generate prophylaxis plans that suggest evidence-based drugs, Chatterjee suggests.

The report also lists several other AI-enabled solutions that might be worth implementing, including automated disease prediction, intuitive claims management and real-time supply chain management.

Frost predicts that the following will be particularly hot AI markets:

  • Using AI in imaging to drive differential diagnosis
  • Combining patient-generated data with academic research to generate personalized treatment possibilities
  • Performing clinical documentation improvement to reduce clinician and coder stress and reduce claims denials
  • Using AI-powered revenue cycle management platforms that auto-adjust claims content based on payer’s coding and reimbursement criteria

Now, it’s worth noting that it may be a while before any of these potential applications become practical.

As we’ve noted elsewhere, getting rolling with an AI solution is likely to be tougher than it sounds for a number of reasons.

For example, integrating AI-based functions with providers’ clinical processes could be tricky, and what’s more, clinicians certainly won’t be happy if such integration disrupts the EHR workflow already in existence.

Another problem is that you can’t deploy an AI-based solution without ”training” it on a cache of existing data. While this shouldn’t be an issue, in theory, the reality is that much of the data providers generate is still difficult to filter and mine.

Not only that, while AI might generate interesting and effective solutions to clinical problems, it may not be clear how it arrived at the solution. Physicians are unlikely to trust clinical ideas that come from a black box, e.g. an opaque system that doesn’t explain itself.

Don’t get me wrong, I’m a huge fan of healthcare AI and excited by its power. One can argue over which solutions are the most practical, and whether AI is the best possible tool to solve a given problem, but most health IT pros seem to believe that there’s a lot of potential here.

However, it’s still far from clear how healthcare AI applications will evolve. Let’s see where they turn up next and how that works out.

Will The Fitbit Care Program Break New Ground?

Posted on September 21, 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.

Wearables vendor Fitbit has launched a connected health program designed to help payers, employers and health systems prevent disease, improve wellness and manage diseases. The program is based on the technology Fitbit acquired when it acquired Twine Health.

As you’ll see, the program overview makes it sound as the Fitbit program is the greatest thing since sliced bread for health coaching and care management, I’m not so convinced, but judge for yourself.

Fitbit Care includes a mix of standard wearable features and coaching. Perhaps the most predictable option is built on standard Fitbit functions, which allow users to gather activity, sleep and heart rate data. However, unlike with individual use, users have the option to let the program harvest their health data and share it with care teams, which permits them to make personalized care recommendations.

Another option Fitbit Care offers is health coaching, in which the program offers participants personalized care plans and walks them through health challenges. Coaches communicate with them via in-communications, phone calls, and in-person meetings, targeting concerns like weight management, tobacco cessation, and management of chronic conditions like hypertension, diabetes, and depression. It also supports care for complex conditions such as COPD or congestive heart failure.

In addition, the program uses social tools such as private social groups and guided workouts. The idea here is to help participants make behavioral changes that support their health goals.

All this is supported by the new Fitbit Plus app, which improves patients’ communication capabilities and beefs up the device’s measurement capabilities. The Fitbit app allows users to integrate advanced health metrics such as blood glucose, blood pressure or medication adherence alongside data from Fitbit and other connected health devices.

The first customer to sign up for the program, Fitbit Care, is Humana, which will offer it as a coaching option to its employer group. This puts Fitbit Care at the fingertips of more than 5 million Humana members.

I have no doubt that employers and health systems would join Humana experimenting with wearables-enhanced programs like the one Fitbit is pitching. At least, in theory, the array of services sounds good.

On the other hand, to me, it’s notable that the description of Fitbit Care is light on the details when it comes to leveraging the patient-generated health data it captures. Yes, it’s definitely possible to get something out of continuous health data collection, but at least from the initial program description, the wearables maker isn’t doing anything terribly new.

Oh well. I guess Fitbit doesn’t have to do anything radical to offer something valuable to payers, employers and health plans. They continue to search for behavioral interventions that actually have an impact on disease management and wellness, but to my knowledge, they haven’t found any magic bullet. And while some of this sounds interesting, I see nothing to suggest that the Fitbit Care program can offer dramatic results either.

 

A Missed Opportunity For Telemedicine Vendors

Posted on June 29, 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.

Today, most direct-to-consumer telemedicine companies operate on a very simple model.

You pay for a visit up front. You talk to the doctor via video, the doctor issues as a prescription if needed and you sign off. Thanks to the availability of e-prescribing options, it’s likely your medication will be waiting for you when you get to the pharmacy.

In my experience, the whole process often takes 45 minutes or less. This beats the heck out of having to wait in line at an urgent care center or worse, the emergency department.

But what about caring for chronic illnesses that can’t be managed by a drive-by virtual visit? Can telemedicine vendors play a role here? Maybe so.

We already know that combining telemedicine with remote monitoring devices can be very effective. In fact, some health systems have gone all-in on virtual chronic care management.

One fascinating example is the $54 million Mercy Virtual Care Center, which describes itself as a “hospital without beds.” The Center, which has a few hundred employees, monitors more than 3,800 remote patients; sponsors a telehealth stroke program offering neurology services to EDs nationwide; manages a team of virtual hospitalists caring for patient around-the-clock using virtual visit tools; and runs Mercy SafeWatch, which the Center says is the largest single-hub electronic intensive care unit in the U.S.

Another example of such hospital-based programs is Intermountain Healthcare’s ConnectCare Pro, which brings together 35 telehealth programs and more than 500 clinicians. Its purpose is to supplement existing staffers and offer specialized services in rural communities where some of the services aren’t available.

Given the success of programs that maintain complex patients remotely, I think a private telemedicine company managing chronic care services might work as well. While hospitals have financial reasons to keep such care in-house, I believe an outside vendor could profit in other ways. That’s especially the case given the emergence of wearable trackers and smartwatches, which are far cheaper than the specialized tools needed in the past.

One likely buyer for this service would be health plans.

I’ve heard some complain publicly that in essence, telemedicine coverage just encourages patients to access care more often, which defeats the purpose of using it to lower healthcare costs. However, if an outside vendor offered to manage patients with chronic illnesses, it might be a more attractive proposition.

After all, health plans are understandably wringing their hands over the staggering cost of maintaining the health of millions of diabetics. In 2017, for example, the average medical expense for people diagnosed with diabetes was about $16,750 per year, with $9,600 due to diabetes. If health plans could lay the cost off to a specialized telemedicine vendor, some real savings might be possible.

Of course, being a telemedicine-based chronic care management company would be far different than offering direct-to-consumer telemedicine services on an occasional basis. The vendor would have to have comprehensive health data management tools, an army of case managers, tight relationships with clinicians and a boatload of remote monitoring devices on hand. None of this would come cheaply.

Still, while I haven’t fully run the numbers, my guess is that this could be a sustainable business model. It’s worth a try.

The Pain of Recording Patient Risk Factors as Illuminated by Apixio (Part 2 of 2)

Posted on October 28, 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 introduced Apixio’s analytics for payers in the Medicare Advantage program. Now we’ll step through how Apixio extracts relevant diagnostic data.

The technology of PDF scraping
Providers usually submit SOAP notes to the Apixio web site in the form of PDFs. This comes to me as a surprise, after hearing about the extravagant efforts that have gone into new CCDs and other formats such as the Blue Button project launched by the VA. Normally provided in an XML format, these documents claim to adhere to standards and offer a relatively gentle face to a computer program. In contrast, a PDF is one of the most challenging formats to parse: words and other characters are reduced to graphical symbols, while layout bears little relation to the human meaning of the data.

Structured documents such as CCDs contain only about 20% of what CMS requires, and often are formatted in idiosyncratic ways so that even the best CCDs would be no more informative than a Word document or PDF. But the main barrier to getting information, according to Schneider, is that Medicare Advantage works through the payers, and providers can be reluctant to give payers direct access to their EHR data. This reluctance springs from a variety of reasons, including worries about security, the feeling of being deluged by requests from payers, and a belief that the providers’ IT infrastructure cannot handle the burden of data extraction. Their stance has nothing to do with protecting patient privacy, because HIPAA explicitly allows providers to share patient data for treatment, payment, and operations, and that is what they are doing giving sensitive data to Apixio in PDF form. Thus, Apixio had to master OCR and text processing to serve that market.

Processing a PDF requires several steps, integrated within Apixio’s platform:

  1. Optical character recognition to re-create the text from a photo of the PDF.

  2. Further structuring to recognize, for instance, when the PDF contains a table that needs to be broken up horizontally into columns, or constructs such the field name “Diagnosis” followed by the desired data.

  3. Natural language processing to find the grammatical patterns in the text. This processing naturally must understand medical terminology, common abbreviations such as CHF, and codings.

  4. Analytics that pull out the data relevant to risk and presents it in a usable format to a human coder.

Apixio can accept dozens of notes covering the patient’s history. It often turns up diagnoses that “fell through the cracks,” as Schneider puts it. The diagnostic information Apixio returns can be used by medical professionals to generate reports for Medicare, but it has other uses as well. Apixio tells providers when they are treating a patient for an illness that does not appear in their master database. Providers can use that information to deduce when patients are left out of key care programs that can help them. In this way, the information can improve patient care. One coder they followed could triple her rate of reviewing patient charts with Apixio’s service.

Caught between past and future
If the Apixio approach to culling risk factors appears round-about and overwrought, like bringing in a bulldozer to plant a rosebush, think back to the role of historical factors in health care. Given the ways doctors have been taught to record medical conditions, and available tools, Apixio does a small part in promoting the progressive role of accountable care.

Hopefully, changes to the health care field will permit more direct ways to deliver accountable care in the future. Medical schools will convey the requirements of accountable care to their students and teach them how to record data that satisfies these requirements. Technologies will make it easier to record risk factors the first time around. Quality measures and the data needed by policy-makers will be clarified. And most of all, the advantages of collaboration will lead providers and payers to form business agreements or even merge, at which point the EHR data will be opened to the payer. The contortions providers currently need to go through, in trying to achieve 21st-century quality, reminds us of where the field needs to go.

The Pain of Recording Patient Risk Factors as Illuminated by Apixio (Part 1 of 2)

Posted on October 27, 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.

Many of us strain against the bonds of tradition in our workplace, harboring a secret dream that the industry could start afresh, streamlined and free of hampering traditions. But history weighs on nearly every field, including my own (publishing) and the one I cover in this blog (health care). Applying technology in such a field often involves the legerdemain of extracting new value from the imperfect records and processes with deep roots.

Along these lines, when Apixio aimed machine learning and data analytics at health care, they unveiled a business model based on measuring risk more accurately so that Medicare Advantage payments to health care payers and providers reflect their patient populations more appropriately. Apixio’s tools permit improvements to patient care, as we shall see. But the core of the platform they offer involves uploading SOAP notes, usually in PDF form, and extracting diagnostic codes that coders may have missed or that may not be supportable. Machine learning techniques extract the diagnostic codes for each patient over the entire history provided.

Many questions jostled in my mind as I talked to Apixio CTO John Schneider. Why are these particular notes so important to the Centers for Medicare & Medicaid Services (CMS)? Why don’t doctors keep track of relevant diagnoses as they go along in an easy-to-retrieve manner that could be pipelined straight to Medicare? Can’t modern EHRs, after seven years of Meaningful Use, provide better formats than PDFs? I asked him these things.

A mini-seminar ensued on the evolution of health care and its documentation. A combination of policy changes and persistent cultural habits have tangled up the various sources of information over many years. In the following sections, I’ll look at each aspect of the documentation bouillabaisse.

The financial role of diagnosis and risk
Accountable care, in varying degrees of sophistication, calculates the risk of patient populations in order to gradually replace fee-for-service with payments that reflect how adeptly the health care provider has treated the patient. Accountable care lay behind the Affordable Care Act and got an extra boost at the beginning of 2016 when CMS took on the “goal of tying 30 percent of traditional, or fee-for-service, Medicare payments to alternative payment models, such as ACOs, by the end of 2016 — and 50 percent by the end of 2018.

Although many accountable care contracts–like those of the much-maligned 1970s Managed Care era–ignore differences between patients, more thoughtful programs recognize that accurate and fair payments require measurement of how much risk the health care provider is taking on–that is, how sick their patients are. Thus, providers benefit from scrupulously complete documentation (having learned that upcoding and sloppiness will no longer be tolerated and will lead to significant fines, according to Schneider). And this would seem to provide an incentive for the provider to capture every nuance of a patient’s condition in a clearly code, structured way.

But this is not how doctors operate, according to Schneider. They rebel when presented with dozens of boxes to check off, as crude EHRs tend to present things. They stick to the free-text SOAP note (fields for subjective observations, objective observations, assessment, and plan) that has been taught for decades. It’s often up to post-processing tools to code exactly what’s wrong with the patient. Sometimes the SOAP notes don’t even distinguish the four parts in electronic form, but exist as free-flowing Word documents.

A number of key diagnoses come from doctors who have privileges at the hospital but come in only sporadically to do consultations, and who therefore don’t understand the layout of the EHR or make attempts to use what little structure it provides. Another reason codes get missed or don’t easily surface is that doctors are overwhelmed, so that accurately recording diagnostic information in a structured way is a significant extra burden, an essentially clerical function loaded onto these highly skilled healthcare professionals. Thus, extracting diagnostic information many times involves “reading between the lines,” as Schneider puts it.

For Medicare Advantage payments, CMS wants a precise delineation of properly coded diagnoses in order to discern the risk presented by each patient. This is where Apixio come in: by mining the free-text SOAP notes for information that can enhance such coding. We’ll see what they do in the next section of this article.

Recorded Video from Dell Healthcare Think Tank Event – #DoMoreHIT

Posted on March 20, 2015 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 mentioned that I was going to be on the Dell Healthcare Think Tank event again this year. It was my 3rd time participating and it didn’t disappoint. In fact, this one dove into a number of insurance topics which we hadn’t ever covered before. I really learned a lot from the discussions and hopefully others learned from me.

Plus, in the first session I had the privilege to sit next to Dr. Eric Topol. He’s got such great insights into what’s happening in healthcare. Of course, I’m also always amazed by Mandi Bishop, who many of you may know from Twitter or her Eyes Wide Shut series here on EMR and HIPAA.

In case you missed the live stream of the event, you can find each of the three recorded sessions below. I also posted the 3 drawings that were created during the event on EMR and EHR. I look forward to hearing your thoughts on what was shared. Thanks Dell for hosting the conversation that brought together so many perspectives from across healthcare.

Session 1: Consumer Engagement & Social Media

Session 2: Bridging the Gap Between Providers, Payers and Patients

Session 3: Entrepreneurship & Innovation