2019 Predictions: M&A, Big Tech, and the Fate of ACOs

The Meaningful Use gravy train finally came to an end in 2018. As the strongest EHR vendors struggle to define new revenue streams, weaker ones faded from view through acquisitions or leveraged buy-out. Meanwhile, funding for ‘digital health’ start-ups continued to increase, though it likely hit the high water mark in 2018. And lest we forget, Amazon, Apple and Google continue their forays into the healthcare sector as the market is simply too big to ignore.

So what’s in store for 2019?

We brought together our analysts’ brain trust and came up with the following baker’s dozen of 2019 predictions. Over the near decade of making these annual predictions, our batting average has consistently been well above .500, so don’t ever say we didn’t give you an advanced warning on the following:  


Revenue cycle management M&A picks up; Optum acquires Conifer

Revenue cycle management M&A activity will continue to pick up with the most notable acquisition by Optum as it doubles down on its Optum 360 managed revenue cycle business and acquires Conifer Health Solutions from Tenet.

Alternative primary care clinics remain a side-show

Despite the hype and media attention around alternative primary care clinics (e.g. Oak Street Health, Chen Med, One Medical), the actual number of physical locations serving patients will remain paltry at less than ten percent of the number of retail health clinic locations. 

Humana finds a life partner with Walmart 

Walgreens will likely make the first move to acquire Humana in 2019, but Walmart will outbid Walgreens to win Humana over.

Regulatory approvals for artificial intelligence-based (AI) algorithms accelerate, tripling the number approved in 2019

The number of FDA approvals for algorithms in 2018 was impressive and shows no signs of abating. Additionally, 2020 will see a further tripling of regulatory approvals for AI.

Choose wisely: 2019 sees the first major shake-out of DTC telehealth vendors

Consumers’ use of telehealth will continue to see rapid growth and rising competition leading to significant consolidation among the plethora of vendors. By year-end, a major non-healthcare-specific consumer brand will join the mix, and the market will be down to five direct-to-consumer (DTC) nationwide brands.

Data science services see extraordinary growth, nearly doubling in 2019

By the end of 2019, every major healthcare analytics vendor will provide a cloud-hosted offering with optional data science and report development services.

In 2019, healthcare organizations (HCOs) adopt a cloud-first strategy

Cloud offerings have become far more robust, concurrent with HCOs’ struggles to recruit IT talent and control costs. Amazon’s AWS and Microsoft’s Azure will be clear winners while Google’s own cloud infrastructure services will remain a distant third in 2019.

New rules from ONC about data blocking have little effect because the business case does not change

Laws and regulations to-date have not compelled providers to freely share data with patients. ONC’s information blocking rule, which will be released before the end of 2018, will make it easier to transfer data to other organizations but will do little to open the data floodgates for patients, clinicians, and developers.

Big tech companies’ intentions in healthcare do little to disrupt the delivery of care

  1. Despite high-profile hires, the Amazon/Berkshire/JPM initiative will make no substantive progress.
  2. Amazon will focus only on the DTC supply chain, payer, and employer—staying away from anything substantive in the provider space.
  3. Apple’s Healthkit and sensor-laden smartwatch will remain sideshows in 2019 awaiting a more actively engaged healthcare consumer.
  4. Google [Deepmind] will never break out of clinical research and drug discovery.

Majority of MSSP ACOs stay and take on risk; hospital-led ACOs lead exits

Despite loud protests, the vast majority of provider-led MSSP ACOs will take on downside-risk as CMS shows flexibility in waivers. However, hospital-led ACOs, who continue to struggle with standing up a profitable MSSP ACO, will exit the program in 2019.

Closure of post-acute facilities shows no signs of slowing

Continued changes in post-acute care reimbursement, especially from CMS, combined with the migration to home-based services, puts further economic strain on these facilities. Nearly twenty percent of post-acute care facilities will shutter or merge in 2019.

2019 Health IT IPO market fails to materialize

The warning signs are there over the last couple of months that the stock market has become skittish. This will extend well into 2019 (if not lead to a mild recession). It will hardly be an ideal time to do an IPO, and those planned by Change Healthcare, Health Catalyst and others will wait another year.

Elon Musk reinvents healthcare

Elon Musk will have a nervous breakdown leading him to reinvent the healthcare system from his bed during his two-week recovery at Cedars-Sinai.

Stay up to the minute.

Did You Know?

Revisiting Our 2018 Predictions

As is our custom here, we like to look back on our predictions for the closing year and see just how well we did. Some years we do amazingly well, others we over-reach and miss on quite a few. For 2018, we got seven of our 13 predictions spot-on, two were mixed results and four predictions failed to materialize. If we were a batter in the MLB we would have gotten the MVP award with a .538 batting average. But we are not and have to accept that some years our prediction average may hover just above the midpoint as it did this year.

Stay tuned, 2019 predictions will be released in about one week and it is our hope that they will inspire both rumination and conversation.

(Note: the bigger and plain text are the original predictions we made in 2017, while the italic text is our review of 2018). 

Merger & acquisition activity continues; Humana or Cigna acquired.

Major mergers and acquisitions that mark the end of 2017 (CVS-Aetna, Dignity Health-CHI and rumored Ascension-Providence) will spill over into 2018. Both Humana and Cigna will be in play, and one of them will be acquired or merged in 2018.

MISS – neither happened. However, Cigna did pick-up PBM service Express Scripts and rumors continue to swirl about a possible Humana-Walmart deal or more recently, even a Walgreens-Humana deal.


Retail health clinics grow rapidly, accounting for 5 percent of primary care encounters.

Hot on the health heels of CVS’ acquisition of Aetna, growth in retail health reignites, albeit off a low overall footprint. By end of 2018, retail health clinic locations will exceed 3,000 and account for ~5% of all primary care encounters; up from 1,800 and ~2%, respectively, in 2015.

MISS – Modest growth in 2018 for retail health clinics with an estimate of around ~2,100 by year’s end. Telehealth, which is seeing rapid growth and on-site clinics may be partially to blame.


Apple buys a telehealth vendor.

In a bid to one-up Samsung’s partnership with American Well, and in a bid to establish itself as the first tech giant to disrupt healthcare delivery, Apple will acquire a DTC telehealth vendor in 2018.

MISS – Apple continues to work on the periphery of care with a focus on driving adoption of its Health Records service in the near-term with a long-term goal of patient-directed and curated longitudinal health records.


Sixty percent of ACOs struggle to break even.

Despite investments in population health management (PHM) solutions, payers still struggle with legacy back-end systems that hinder timely delivery of actionable claims data to provider organizations. The best intentions for value-based care will flounder and 60% of ACOs will struggle to break even. ACO formation will continue to grow, albeit more slowly, to mid-single digits in 2018 to just under 1,100 nationwide (up from 923 as of March 2017).

HIT – MSSP performance data showed only 34% earned shared savings in 2017 (up from 31% in 2016) and by year’s end it is estimated there will be ~1,025 ACOs in operation.


Every major EHR vendor delivers some level of FHIR support, but write access has to wait until 2019.

While some of the major EHR vendors have announced support for write access sometime this year and will definitely deliver this support to their most sophisticated customers, broad-based use of write APIs will happen after 2018. HCOs will be wary about willy-nilly changes to the patient record until they see how the pioneers fare.

HIT FHIR-based read APIs are available from all of the major EHR vendors. Write APIs are still hard to find. To be fair, HCOs as a group are not loudly demanding write APIs.


Cloud deployment chips away at on-premises and vendor-hosted analytics.

True cloud-based deployments from name brand vendors such as AWS and Azure are in the minority today. But their price-performance advantages are undeniable to HIT vendors. Cerner will begin to incent its HealtheIntent customers to cloud host on AWS. Even Epic will dip its toes in the public cloud sometime in 2018, probably with some combination of Healthy Planet, Caboodle, and/or Kit.

HIT – adoption of cloud computing platforms is accelerating quickly across the healthcare landscape for virtually all applications. Cloud-hosted analytics is seeing particularly robust growth.


True condition management remains outside providers’ orbit.

Providers will continue to lag behind payers and self-insured employers in adopting condition management solutions. There are two key reasons why: In particular, CMS’s reluctance to reimburse virtual Diabetes Prevention Programs, and in general, the less than 5% uptake for the CMS chronic care management billing code. In doing so, providers risk further isolation from value-based efforts to improve outcomes while controlling costs.

HIT – Awareness of the CCM billing code (CPT code 99490) remains moderate among providers and adoption is still estimated at a paltry less than 15%.


Mobile-first becomes the dominant platform for over 75% of care management solutions.

Mobile accessibility is critical for dynamic care management, especially across the ambulatory sector. More than 75% of provider-focused care management vendors will have an integrated, proprietary mobile application for patients and caregivers by end of 2018. These mobile-enabled solutions will also facilitate collection of patient-reported outcome measures, with 50% of solutions offering this capability in 2018.

MIXED – While the majority of provider-focused care management vendors do have an integrated mobile application (proprietary or partnership), collecting PROMs is still a functionality that remains limited through an integrated mobile solution.


Solutions continue to document SDoH but don’t yet account for them.

A wide range of engagement, PHM, EHR, and care management solutions will make progress on documenting social determinants of health, but no more than 15% of solutions in 2018 will be able to automatically alter care plan interventions based on SDoH in 2018.

HIT – despite all the hoopla in the market about the need to address SDoH in care delivery, little has been done to date to directly affect dynamic care plans.


ONC defines enforcement rules for “data blocking,” but potential fines do little to change business dynamics that inhibit data liquidity.

The hard, iron core of this issue is uncertainty about its real impact. No one knows what percentage of patients or encounters are impacted when available data is rendered unavailable – intentionally or unintentionally. Data blocking definitely happens but most HCOs will rightly wonder about the federal government’s willingness to go after the blockers. The Office of the National Coordinator might actually make some rules, but there will be zero enforcement in 2018.

MIXED – Last December we said, “The hard iron core of this issue is uncertainty about its real impact.” Still true. Supposedly, rulemaking on information blocking is complete but held up in the OMB. The current administration does not believe in regulation. So “data blocking” may be defined but there was and will be no enforcement or fines this year.


PHM solution market sees modest growth of 5-7%.

Providers will pull back on aggressive plans to broadly adopt and deploy PHM solution suites, leading to lackluster growth in the PHM market of 5% to 7% in 2018. Instead, the focus will be on more narrow, specific, business-driven use cases, such as standing up an ACO. In response, provider-centric vendors will pivot to the payer market, which has a ready appetite for PHM solutions, especially those with robust clinical data management capabilities.

HIT – PHM remains a challenging market from both payment (at-risk value-based care still represents less than 5% of payments nationwide) and value (lack of clear metrics for return on investment) perspectives. All PHM vendors are now pursuing opportunities in the payer market, including EHR vendors.


In-workflow care gap reminders replace reports and dashboards as the primary way to help clinicians meet quality and utilization goals.

This is a case where the threat of alert fatigue is preferable to the reality of report fatigue. Gaps are important, and most clinicians want to address them, but not at the cost of voluminous dashboards or reports. A single care gap that is obvious to the clinician opening a chart is worth a thousand reports or dashboards. By the end of 2018, reports and dashboards will no longer be delivered to front-line clinicians except upon request.

MISS – Reports and dashboards are alive and well across the industry and remain the primary way to inform front-line clinicians about care gaps.


At least two dozen companies gain FDA-approval of products using machine learning in clinical decision support, up from half a dozen in 2017.

Arterys, Quantitative Insights, Butterfly Network, Zebra Medical Vision, EnsoData, and iCAD all received FDA approval for their AI-based solutions in 2017. This is just the start of AI’s future impact in radiology. Pioneer approvals in 2017 — such as Quantitative Insights’ QuantX Advanced breast CADx software and Arterys’s medical imaging platform — will be joined by many more in 2018 as vendors look to leverage the powerful abilities of AI/ML to reduce labor costs and improve outcomes dependent on digital image analysis.

HIT – With about a month left in 2018 the count of FDA approved algorithms year to date is approaching 30 and could potentially hit three dozen by year end. This is a significant ramp up in the regulatory pipeline, but more is needed in the way of clear guidance on how they plan to review continuously learning systems and best practices for leveraging real-world evidence in algorithm training and validation.


What do you think of 2018 for health IT?

FDA Guidance on Clinical Decision Support: Peering Inside the Black Box of Algorithmic Intelligence

Key Takeaways:

  • The FDA has released long-anticipated draft guidance on how they intend to regulate clinical decision support products.
  • For applications with data originating from medical devices, the FDA will continue its oversight, AI or not (e.g., medical image processing).
  • Medical applications that rely on “black box” algorithms unable to be fully understood by the end-user (basically all AI) will be regulated, posing challenges for AI adoption.

Last week, the FDA finally released its long-awaited Draft Guidance on Clinical Decision Support. Following the release, STAT News mentioned experts were disappointed because the agency gave no insight into how it views artificial intelligence. Indeed, a “Command+F” search for “Artificial Intelligence” returns zero results. However, it is unnecessary for the agency to use the term “AI” to provide guidance on how it will consider associated technologies and use cases. The FDA does use the word “algorithm” in its guidance, and although algorithms can vary in sophistication, much of today’s AI technology is based on algorithmic intelligence. The suggestion that the FDA did not address the topic becasue it failed to explicitly mention AI within the document shows the challenges for those unfamiliar with understanding this complex subject.

Nearly all AI will remain under FDA oversight. However…It would be useful for the agency to offer meaningful reference to machine learning or deep learning among the examples of potential use cases.

In fact, the FDA has been reviewing technology with AI components (e.g., rule-based systems, machine learning) for more than a decade. RADLogics received FDA approval for their machine learning application in 2012, widely considered the first AI for clinical use approved by the agency. HealthMyne received FDA clearance for its imaging informatics platform in early 2016. In 2017 at least half a dozen companies received FDA clearance for machine learning applications, including Arterys, the first company to receive approval for a deep learning application, and Butterfly Network, which had 13 different applications approved along with its “ultrasound on a chip” device in late October. Others to receive clearance in 2017 include Quantitative Insights, Zebra Medical Vision, EnsoData and iCAD.

The first indirect reference to products using AI comes in the first paragraph of Section III, in which the agency begins addressing specific examples of companies that will not be exempted from review. Note that the first bolded sentence below is inclusive of nearly every application.

“Under section 520(o)(1)(E), software functions that are intended to acquire, process, or analyze a medical image, a signal from an in vitro diagnostic device, or a pattern or signal from a signal acquisition system remain devices and therefore continue to be subject to FDA oversight. Products that acquire an image or physiological signal, process or analyze this information, or both, have been regulated for many years as devices. Technologies that analyze those physiological signals and that are intended to provide diagnostic, prognostic and predictive functionalities are devices. These include, but are not limited to, in vitro diagnostic tests, technologies that measure and assess electrical activity in the body (e.g., electrocardiograph (ECG) machines and electroencephalograph (EEG) machines), and medical imaging technologies. Additional examples include algorithms that process physiologic data to generate new data points (such as ST-segment measurements from ECG signals), analyze information within the original data (such as feature identification in image analysis), or analyze and interpret genomic data (such as genetic variations to determine a patient’s risk for a particular disease).”

The word “algorithm” is used four times in the document and in each instance the use provides significant insight into the agency’s thinking. The word is first used in the second highlighted sentence above, which provides general examples of algorithms which will continue to be reviewed as medical devices. The guidance goes on in a later section to provide the following more specific examples of algorithms that continue to require premarket approval:

“Software intended for health care professionals that uses an algorithm undisclosed to the user to analyze patient information (including noninvasive blood pressure (NIBP) monitoring systems) to determine which anti-hypertensive drug class is likely to be most effective in lowering the patient’s blood pressure.

“Software that analyzes a patient’s laboratory results using a proprietary algorithm to recommend a specific radiation treatment, for which the basis of the recommendation unavailable for the HCP to review.”

The agency continues to describe the underlying features that must be present for an algorithmically-driven CDS recommendation to be exempted from review, specifically a company must clearly state and make available:

  1. The purpose or intended use of the software function;
  2. The intended user (e.g., ultrasound technicians, vascular surgeons);
  3. The inputs used to generate the recommendation (e.g., patient age and gender); and
  4. The rationale or support for the recommendation.

The first three would seem to be reasonable enough for developers of AI products to provide users, but the fourth is basically impossible. The “black box” nature of most AI systems built using machine learning methods means even leading AI experts cannot unpack an algorithm and fully understand the rationale for a given recommendation, even with full transparency and access to the training data (which is no trivial matter in and of itself).

This is especially clear when taking into consideration additional guidance provided elsewhere in the document regarding software functions that will require oversight:

A practitioner would be unable to independently evaluate the basis of a recommendation if the recommendation were based on non-public information or information whose meaning could not be expected to be independently understood by the intended health care professional user.

Frankly, the agency provided great insight and clarity if you are reading the document to be inclusive of all known AI technologies today. The conclusion is clear that nearly all AI will remain under FDA oversight. However, there are terms that could be used in the final guidance that aren’t buzzwords, such as machine learning, supervised learning and unsupervised learning, among others. It would be useful for the agency to offer meaningful reference to machine learning and/or deep learning among the examples of potential use cases that remain under oversight as medical devices.

In Chilmark’s annual predictions for 2018, we forecast that two dozen companies will receive FDA clearance for products using AI, machine learning, deep learning and computer vision, which would mark a 400-percent increase from 2017. It would be helpful if the agency would create a dedicated channel for engaging companies developing AI products and perhaps even provide guidance on how they evaluate training data sets.

Connected Care: Are We There Yet?


Healthcare organizations (HCOs) are acknowledging the need for next generation tools to realize the promise of newer models of cost-effective, outcomes-driven population health management. As reimbursement changes and business challenges put pressure on the current model of one-to-one, episode-based treatment, the need has emerged for continuous data collection on high-risk patients, in a one-to-many management framework. Yet the reality on the ground is less clear. While the general value proposition of connected care is well understood at this stage, the specific business case remains murky: which use cases, disease states, and patient populations provide the best starting point? To what extent can existing investments be leveraged to enable new models? How much do these solutions cost, and what is the anticipated ROI? With so many vendors angling to serve this market, which approaches rise to the top?

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The Patient Will See You Now

A Worthy Read

This month’s Domain Monitor is a little bit different. We recently read through Dr. Eric Topol’s latest book, The Patient Will See You Now. Over the past few years, Topol has become a “crossover” figure between our insular world of health IT and the more mainstream media. Today he is a widely respected thought leader in the area of digital medicine. In his latest book, he explores the myriad of changes happening to the traditional delivery of medical care, fueled by advances in consumerism, technology, science, regulation…and the list goes on.

While Topol is certainly a visionary, his thesis leaves out some obvious real world considerations about tractability, adoption, usability, health literacy, and more, which ultimately amounts to a sort of a prophetic evangelization of a high-tech future rather than a field guide to the present.

This book is not a roadmap for health executives, nor is it a blueprint for technologists or scientists. That being said, Topol does serve up a complete (if at times off-topic and/or esoteric) survey of the new consumer landscape in healthcare and medicine, along with the market drivers, roadblocks, technologies, and other factors involved. All in all, Topol’s overview of these complex topics is comprehensive, rife with detailed examples of companies, technologies, and concepts throughout.

What follows here is a high level summary of some of the major issues in this book, along with our overall take on Topol’s findings. We have also provided a quick “Executive’s Guide” for those interested in Topol’s work but without the time to pore through the entire book.

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23andMe vs the FDA: How did it come to this?

Big sumo facing a child

Another regulatory David and Goliath story

As most of our readers are likely aware, the FDA this week issued a scathing letter effectively prohibiting the 5 year-old, 23andMe personal genomics testing company from doing business. Quite frankly, this is all pretty unnecessary, and reflects poor policy on the parts of both institutions. Furthermore, this ruling may have longer-term implications that will cripple the process of democratizing genetic testing and research.

23andMe: Naiveté or Arrogance

First and foremost, 23andMe has been selling their personalized genetic testing kits for the last few years despite notice that they needed FDA clearance and have not yet received it. According to the FDA, there have been many interactions with the company to work together to make this test safe and reliable for consumers. In their scathing letter, they lay this out very specifically:

“As part of our interactions with you, including more than 14 face-to-face and teleconference meetings, hundreds of email exchanges, and dozens of written communications, we provided you with specific feedback on study protocols and clinical and analytical validation requirements, discussed potential classifications and regulatory pathways (including reasonable submission timelines), provided statistical advice, and discussed potential risk mitigation strategies. As discussed above, FDA is concerned about the public health consequences of inaccurate results from the PGS device; the main purpose of compliance with FDA’s regulatory requirements is to ensure that the tests work.”

Anne Wojciki, the CEO, yesterday posted their response to the FDA’s letter on the 23andMe blog. In it, she admits that they have not been on top of the filing process:

“In July 2012 23andMe submitted its first application for FDA clearance and followed on with another submission at the end of August. We received feedback on those submissions and acknowledge that we are behind schedule with our responses.”

The FDA is a regulatory body and therefore should never be taken lightly or overlooked. Put simply, they have the power to cripple your business. This leads one to wonder why 23andMe seems to have taken such a lackadaisical attitude towards the FDA and taking so long to follow through with a renewed application that took the FDA’s concerns into account. Did 23andMe really think there would be no repercussions to their inaction? Were they truly that naïve or worse, arrogant?

The FDA: Do they really have the authority to do this?

Legally, yes. The ‘Legal Argument’ website Mootus has taken this issue to the masses, asking for contributions to answer the question of the legality of the FDA’s actions. The clearest predicate case is to Chevron U.S.A., Inc. v. Natural Resources Defense Council, Inc. (Supreme Court 1984):

Courts must give deference to an agency’s reasonable interpretation of an ambiguous provision within the agency’s own organic statute.

If this sounds a little self-serving for the government, that’s because it is. In fairness though, it makes sense as no government agency can foresee every possible permutation of how it’s regulations will be interpreted. Hence the many loopholes federal agencies are always trying to stay on top of.

Before I became interested in healthcare IT, my first jobs out of undergrad were conducting genetics research. I worked in labs at Massachusetts General Hospital and Novartis Institutes for Biomedical Research looking for novel ways to genetically characterize disease for both treatment and risk. Our understanding of ‘genetic risk’ for disease is still very much in its infancy. Like almost all of healthcare, genetic testing is not something that a medical practice will just do for you – there needs to be a legitimate medical need.

Because of my background, the rise of consumer companies selling genetic test kits has always been of interest. My first boss, Rudolph Tanzi, one of the world’s experts on genetics (specifically related to Alzheimer’s disease), was of the opinion that there has not been enough research published to truly inform patients of their risk for different illnesses. For strict medical purposes, this is a prudent position. If you are going to tell someone they have a specific illness based on genetics, then the science better be conclusive.

This is where things with 23andMe become murky. 23and Me has never stated that they are providing medical advice, which very much would make them a medical diagnostic under FDA regulation. To the contrary, they and other consumer genetic testing companies clearly state that they provide information. In the case of 23andMe, they first got their start promoting their ability to do genetic matching to determine an individual’s ancestry. Today, 23and Me promotes that they are disseminating medical information that is already in the public domain, and making it accessible to a layperson for very low cost. Therefore, if one looks to recent FDA mHealth guidelines (PDF) as providing some indication on how the FDA may rule on consumer genetic testing, one could easily assume that 23andMe is “safe” from FDA regulatory burden.

23andMe uses CLIA-certified labs to conduct testing. They cite all of their reference articles for how they determine risk (see asthma example here). They very clearly state in their Terms of Service (TOS) that they are not a medical service, and do not provide diagnostic services. Listed below are the main subheadings from Section 5 of their TOS, “Risks and Considerations Regarding 23andMe Services”:

  • Once you obtain your Genetic Information, the knowledge is irrevocable.
  • You may learn information about yourself that you do not anticipate.
  • The laboratory may not be able to process your sample, and the laboratory process may result in errors.
  • You should not change your health behaviors solely on the basis of information from 23andMe.
  • Genetic research is not comprehensive.
  • 23andMe Services are for research, informational, and educational use only. We do not provide medical advice.

The 23andMe service is meant to be an interesting glimpse into your own history, and potential future. It can also be a powerful information tool to identify what you can do to live a healthier life, much in the way of the Quantified Self movement.

What this means for consumers

As with all of medical care, allowing patients to have access to their own information seems to be against the interests of some very powerful entities. Only in recent years have patients been given access to their own health information, although it can still be a struggle to obtain that information.

Part of what plagues this industry is the continued belief by many healthcare professionals that consumers cannot be trusted – that they can only navigate their health with the assistance of a physician and can’t be relied upon to do their own research. And while this is changing, it is happening ever so slowly. This patronizing paternalism on the part of the healthcare establishment is outdated and needs to change. A new world order is coming to the healthcare sector much like it has come to many others. One where the consumer requests a more dynamic role and the provider becomes more of a coach to help guide the consumer, not dictate what the consumer can and cannot do with information about themselves.

For now, it looks as though access to your own genetic information will continue to be overseen by the FDA, but hopefully in the future such regulating bodies will see the benefit of opening up the floodgates. By allowing curious individuals to assess their genetic information, and then share that at their own discretion, companies like 23andMe are creating a vast new data pool for genetic research. By updating profiles with relevant health developments, this information can be mined to find new correlations that were previously unidentified by the current methods of conducting genetic research after knowing that someone has an illness. Predictive models only get better the more they learn, and more users in this case is more education for the entire genetics community. Similar to what PatientsLikeMe has famously done with testing drug efficacy, 23andMe can theoretically do for genetics. 23andMe may be forced to halt testing for medical issues until this dispute is resolved, but they can still provide ancestry information, and will always have your sample on file if and when they get the clearance to start marketing for medical purposes again.

What does this mean for industry?

Clearly, the FDA is a fickle master, and there are still a lot of gray areas around what they expect to regulate. With the pace of technology advancements continuously accelerating, any regulatory body would be hard-pressed to keep up. The recent publication of their mHealth Guidance provided tremendously valuable clarity to that new industry. However, it also shows that not all products in the healthcare space are expected to adhere to the same set of rules and corporations from any sub-industry should be aware of the specific constraints relevant to them.

Our recommendation is that you always enter the space with open eyes, and regularly interface with the FDA to ensure you are working in concert. Regulations will always be in flux, and showing a willingness to cooperate early will only go in your favor. Eventually, the FDA may realize that the service 23andMe provides is not actually a medical service – although it does touch medicine. This goes for any new medical innovation that is not clearly defined in the FDA charter. In the meantime, at least attempt cooperation and show the organization the respect it merits so it won’t shut you down.

Who will regulate mHealth? Patient Engagement at Crossroads; New Alliance Takes On Interoperability

We came back from HIMSS and got right to work on the March Monthly Update for Chilmark Advisory Services subscribers. As we’ve reported in a previous post, HIMSS13 afforded enormous buzz and less enlightenment regarding the state of health IT, particularly the four key areas we see as essential to this industry making a true difference in patient care. In our March update, and the reports currently underway, Chilmark Research does the opposite: provide insight without buzz. Below are abstracts from this month’s update. To find out how you can receive the full update, send an email to: info at chilmarkresearch dot com

Public vs. Private Oversight of Mobile Health
John Moore III

mHealth, known for rapid innovation and iteration, has a tendency to buck at the snail’s pace of FDA regulation. Last month, during a series of hearings considering whether smartphones and tablets with medical apps qualify as medical devices and thus require FDA approval, many charged the FDA with stifling innovation. After all, how many developers or investors want to sink resources into an industry that will be regulated in ways that have yet to be determined?

Enter Happtique and its Health App Certification Program. Happtique intends to complement the work of the FDA, and has introduced a set of standards for health apps that fall into the grey area between apps that are clearly medical and those with a clear consumer focus. This could herald a new age of credibility for mHealth. However, as both regulator and marketplace for many of the apps that it regulates, Happtique could end up in a very sticky situation. They will need to tread carefully to maintain their objectivity in both certifying apps while at the same time providing a marketplace for mHealth apps.

The March Toward Better Patient Engagement
Naveen Rao

The open question in health IT these days is whether patient engagement will gain traction or if it will suffer the same fate as PHRs. One thing is certain; healthcare needs far better patient engagement methods, processes and techniques than what one finds today as most current efforts in engagement have very little to do with helping a patient manage a condition. Time and again in our discussions with healthcare institutions of all sizes we find the same scenario being played out – engagement today is focused on building patient/customer loyalty to the institution – they are simply no more than marketing efforts.

Stage 2 meaningful use is requiring a deeper level of patient access to their records via view, download and transmit requirements and there is even a requirement for some email messaging between provider and patient. But there is a bigger issue at play, payment reform wherein providers will be taking on more risk for the patient populations they manage. Without deeper engagement with the patient regarding a chronic disease, providers will struggle with these new payment risk models.

Several related markets, such as telemonitoring and wearable tech are taking off. Chilmark analyst Naveen Rao spent near-exclusive attention to the patient-engagement tracks, vendors, and sessions at HIMSS13. In his article for the March update, Naveen identifies three factors that will define if and how well the patient-engagement market will stay afloat in the coming years.

CommonWell Alliance Intends to Tackle Interop
John Moore

The announcement of CommonWell Health Alliance was likely the biggest story to come out of HIMSS (Allscripts acquiring longtime HIE partner dbMotion may have been a close second). The group’s stated purpose is to enable interoperability across the five founding members’ EHRs. For starters at least, this includes: Allscripts, athenahealth, Cerner, Greenway, and McKesson’s RelayHealth division. In its simplest form, CommonWell will establish a set of standards and services that enable query-based health information sharing in a heterogeneous EHR environment.

Part of the challenge with interoperability within a community of heterogeneous EHRs is that standards are useless when it comes to things like patient matching, consent management, or locating records, all of which are fundamental to interoperability and all of which require standardized services model. CommonWell founders know this and have plans to address it. The greatest challenge facing CommonWell, however, may be the market itself as adoption of HIE tech within the ambulatory sector remains a challenge.

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Re-entry into Healthcare

As with the last shuttle mission making its re-entry into the Earth’s atmosphere yesterday, I am re-entering the world of healthcare IT after an extended family vacation in the wilds of Alaska. No, I did not see John Halamka up there, it is after all a VERY BIG state, but I did get the chance to go completely off-the-grid, a blessed reprise and observe what is one of the more beautiful and still untouched landscapes in the northern hemisphere. Upon finally arriving in Vancouver I made the vow to return, but next time it will be to spend more time in the small coastal towns of the Alaskan peninsula, likely via an expedition kayak, to get up close and personal with the people and environs of this small corner of the world.

After being away for nearly two weeks, it is a challenge to pick up where one left off. Cruising through the reams of email (please excuse any delays in getting back to you I’ll get to your email yet, I promise), trying to catch up on my reading of the various industry rags and tapping twitter I feel pretty comfortable in stating the more things change, the more they stay the same (not exactly the best quote for an analyst to say as we thrive on turmoil…).  That being said, following are a few items that did catch my attention and may look into further:

FDA Releases Proposed mHealth App Regulations
On Tuesday, the FDA finally released guidance on how it intends to regulate mHealth Apps. Having taken a cursory review of these proposed regs, have to say I’m quite impressed as the FDA has struck a careful balance of  applying regulatory review where warranted while allowing plenty of room for innovation in this very young and still immature industry sector.  MobihealthNews has a fine write-up on this story.

WebMD Provides Abysmal Guidance and Tanks
WebMD, which has been seemingly immune to the recession, provided Q2’11 guidance that sent its stock into a tailspin and leading to a very rapid (next day) letter to investors from the Chairman to quell fears. Why is this significant? First, pharma is feeling the effects of the recession and is pulling advertising dollars off the table. Over the last few years, WebMD has been putting virtually all of its “eggs in one basket” – pharma. It appears that the golden goose of pharma is no longer laying golden eggs which will likely have a ripple effect on the multitude of other smaller Health 2.0 like companies whose business models are advertising based. Secondly, once again WebMD is projecting contraction in its “private portal” business. This is, or at least was, the 800lb gorilla in the PHR market for employers and payers. WebMD has milked this cow for about all its worth and do not be surprised if others start aggressively moving in. Cerner is one and we’ll talk about another tomorrow.

Stage 2 Meaningful Use Likely Delayed till 2014
Can’t say we didn’t see this coming as ONC’s advisory board basically recommended such but it does complicate the schedule for incentive payments which, as part of ARRA were meant to create jobs and create those jobs quickly. As the recession continues to drag on, there appears to be an acceptance that getting back to near full employment in this country will not occur quickly. Such acceptance has appeared to bring some rationality as to the rollo-out of EHRs. Choosing, installing, mapping workflow, testing, training and going live with an EHR, let alone meet the various requirements of meaningful use (MU) is no small task and this delay will bring a sigh of relief among many a CIO and eligible professional. But now one has to wonder: What does this mean for Stage Three?  Don’t be surprised if Stage Three gets the ax.

I’m sure there are other bits of news that I missed and welcome your input to help educate this off-the-grid analyst on all the wonderful things he missed as he was trudging through the temperate rain forests of Alaska or battling grizzlies for a share of their salmon (note, grizzlies don’t share).  BTW, this last picture is of one of the “deep forest creatures” you’ll find in that rain forest.