Time to SMAC the Healthcare Consumer

Big brother is watching youSMAC – Social, Mobile, Analytics, Cloud – is a popular framework for optimizing business performance through IT. The basic idea is that these four elements all play key roles in generating value from data through capture, storage, and application.

  • Social refers to the consumer or end-user level, where data is created and collected
  • Mobile describes the shift to smartphone and tablet-driven computing
  • Analytics speaks to the growing ability and need to interpret and understand data big and small
  • Cloud refers to the advent of virtual computing through untethered storage and access to data, applications, services, and more

Compelling visions are emerging about how SMAC might be applied to improve the delivery of care. These generally describe a connected patient population that is actively and passively generating new health and behavioral data that are captured through an array of apps and sensors. These data are funneled and blended into algorithms that can suggest trends or predict medical needs, which can then inform appropriate patient engagement. A wide range of specific clinical applications also bubble up from this process, from care alerts and medication reconciliation, to rules authoring and risk scoring.

In theory this sounds great. But of course, there are several obstacles to making it work.

Lately, a different vision of SMAC seems to be emerging in healthcare, focused on the consumer rather than the patient, and the marketing rather than the clinical. Some of these business-oriented applications may look something like this:

  • Social: Advanced use of social media as an interactive brand and rich source of insight on consumer preferences and trends.
  • Mobile: Tools to help consumers navigate the healthcare system the same way we look for movie tickets or deposit checks: with our phones.
  • Analytics: Using population data to understand linkages between people (make of car, marital status, education, vocation, social media presence) and their tendencies (paying for a wellness visit, missing appointments, using digital tools, writing online reviews).
  • Cloud: Virtually everything that everyone does is captured and sent into a cloud, from web searches and click patterns to credit card purchases and retail behavior.

If this seems more like futuristic fiction than reality, consider what your smartphone is tracking. After a recent trip to the local coffeeshop, my phone sent me a note of exactly where I had parked, based on Google’s ability to interpret patterns of passively generated geolocation and accelerometer data.

Are We There Yet?

An article about the digital dust left behind by consumers recently made the rounds online, generating excitement about some of the potential applications of all of this non-health data. It pointed out ideas such as clinical trials eligibility, or public health surveillance. Such uses read well in the press, but others don’t, as MedSeek found out in June. The article also goes into detail about how such use cases are being built at UPMC. The Pittsburgh health system has mined, bought, and mixed census records, claims, prescriptions, utilization, household incomes, education levels, marital status, race, number of children, number of cars, and more. They have created correlations to predict people’s use of services, though they claim not to use those correlations to alter care delivery today. Since UPMC has rolled out its own narrow network plan, does the collection of this information cross a line – will it be used to determine the relative risk of a patient and his or her family when signing up for insurance?

Has Data Ethics Caught up with Data Collection?
The elephant in the room here is if we are ready to openly acknowledge and condone these practices, or if there are still some questions that need answering. To name just a few: If these correlations lead to differential treatment based on disease or age, is this just a watered down, post-reform version of pre-existing conditions? What are repercussions of a company acting based on correlations to someone’s race or gender? Are some of these data falling through a HIPAA loophole? Does it make sense to develop a disclosure or data consent policy here, or even to set rules on which data can be collected and how they can be used? Finally, while efficiencies are needed in healthcare, is it worth feeding giants like UPMC, a non-profit with $10.2B operating revenue, at the potential cost of consumer privacy and autonomy?

While the debate about civil rights continues, consumers may be past the point of outrage, thanks to a rolling banner of stories about how much data about us is being used without our permission. NSA’s surveillance and Facebook’s mood manipulation are treated with a headshake and a shrug. Even if this attitudinal shift serves as a weak thumbs up from consumers, HCOs may still be wary of losing their brand standing in a fiercely competitive marketplace. UPMC and Highmark’s turf war, for example, is so entrenched it has generated its own About.com page. Perhaps too there is a correlation between a person’s likelihood of voting with their feet after a PR crisis, and their education, affluence, and level of health.

Data Talks, But Who’s Listening?
While HCOs have shown some reluctance to SMAC their consumers to shift their operations, others have moved forward. Pharma and medical device manufacturers have been studying us for decades, trying to understand our preferences, what we watch on TV, and where we eat. Now they follow what we’re doing online. Digital agency and social media analytics firm WCG has become adept at monitoring and analyzing data on millions of individuals on behalf of their industry clients, with the end goal of connecting the dots between what people are saying online and what they may be doing in real life.

“We can map patient journeys through various therapeutic areas, based strictly on the social exhaust we are picking up on people,” said Greg Matthews, a managing director at WCG and creator of the MDigitalLife project. Referring to a recent project to track online discussions of cancer, he explained further, “What we’re able to do is look deeply at conversations online, related to a diagnosis, ascertain language using NLP, and understand where they are in the patient journey, from pre-diagnosis to post-treatment.” Matthews also noted that while doctors and individual providers have been active in these conversations, hospitals and health systems have been missing thus far.

While some applications of SMAC may appear controversial, others are simply convenient. Thanks to innovative tech companies, HCOs are able to subtly leverage consumer data to help business, without compromising their integrity. iTriage and Axial Exchange can leverage GPS to define geographic boundaries for lists of providers and facilities. Virtuwell and AskMD are proving that people are willing to divulge their PHI straight into a computer (and pay for it out of pocket) if it gives them better access to care. HCOs are paying all four of these companies to help them rein in patients by giving them something useful.

With tight market competition and a macro shift towards value-based care, the value proposition for using consumer data intelligently has become clear. HCOs now have the means to capture, understand, and act on data about people based on the digital footprints they leave behind. Early applications have been limited to tighter network management and customer retention through apps like iTriage. The next wave of applications is right around the corner, led by systems like UPMC and vendors like MedSeek: selective marketing of services and programs, more sophisticated utilization management, and some degree demographic/socioeconomic targeting. As we collectively become accustomed to this new normal, look for HCOs to begin taking on consumer engagement with an all out SMAC.

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Big Fish Swallows Another – Will it Choke?

fish2Rumors that have been floating around for months that Siemens planned to exit the health IT (HIT) market have come true. Earlier today, Cerner announced that it will acquire Siemens HIT business for a whopping $1.3B with expected close in Q1 2015. While we will be doing a more thorough breakdown of what this acquisition means to the two companies, the market and most importantly their customers in a research piece for clients, following is my back of the envelop analysis.

  • With this acquisition, Cerner now surpasses Epic in # of hospital clients, something I’m sure that makes Cerner’s CEO smile – Neal is a tough competitor.
  • Cerner will certainly support Siemens clients on Siemens clinicals, but there will be a time horizon on that support with Cerner’s ultimate goal of having Siemens clients ultimately switch to Cerner clinicals.
  • A weak spot for Cerner has been their financials. Siemens brings them a reasonably good financials solution that some existing Cerner Millennium clients are already using. The trick here will be to truly integrate the two systems (clinicals of Cerner with financials of Siemens) to be truly competitive in the market.
  • Acquisition gives Cerner a much stronger international presence, especially in Europe – a target growth area for most acute EHR vendors now that US acute care market is basically tapped out.

The price of $1.3B is quite high for what Cerner is getting, but Cerner is not a company known for wasting money. It is also VERY uncharacteristic of Cerner to make such a large acquisition. However, Cerner sees value here to leverage long-term, and they do look long-term.

Much of that future value is likely found in Cerner’s rapidly growing PHM activities (HealtheIntent). One of our analysts just came back from Cerner’s PHM Summit last week and was truly impressed with how aggressive Cerner is moving on this front. There is a huge untapped PHM market among existing Cerner clients and now Siemens clients – potentially huge up-sell opportunities if Cerner does it right.

This acquisition is also just the tip of the iceberg – we’ll see many more in the next 12-24 months as market is way overdue for consolidation.

Note: Our forthcoming 2014 Analytics for PHM Market Trends Report (to be released this month) provides a detailed look at this market including a detailed profile of Cerner and 18 other leading vendors. 

 

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Population Health Management in Real-Time

real-time dataReal-time population health usecases are everywhere in healthcare. Imagine a patient recently diagnosed with congestive heart failure (CHF). As soon as his physician saves the new diagnosis within the EHR, the patient is automatically enrolled in a program and sent an email. As part of the program, the patient steps on a wifi scale every day at home; an alert is surfaced back to the physician when a sudden weight gain is detected. This type of real-time patient/population health management is happening today, albeit as pilots versus anything at scale across a population.

In an ideal world, real-time data — including user generated data, mobile, and social data — will simply arrive and be acted upon. The clinical care team, extended care team, and the patient will receive the necessary alerts and outreach, via the appropriate channel chosen. Outcomes will be tracked, and predictive models will be automatically refined based of feedback loops built into the system.

This kind of care management utopia would enable care processes to move beyond bricks and mortar and towards the consumer/home:

Care ManagementHowever, providers have historically lacked the financial incentives to concentrate on this type of real-time population monitoring. And, under P4P contracts, population heath usecases became more associated with non-urgent matters, e.g,. a patient is overdue for her HbA1c test. (until the readmissions penalties came along).

On the other side of the fence, payers have had the necessary incentives — but have had to make due with adjudicated claims data (or, “paid claims”) in their attempts at population monitoring/preventing adverse events – a less than ideal dataset if one wishes to do real-time, population health management.

Paid Claims: The Data Timeliness Villain. Paid claims data continue to be disparaged by providers as stale and shallow — even as these same providers have come around and now grudgingly accept paid-claims data as necessary for detecting leakage and total cost of care.

Even payers experience a lag time of roughly a month when it comes to analyzing aggregate paid-claims data stores — when all is said and done. Companies like ActiveHealth Management have struggled with this timeliness issue as their vision is to monitor population health in real-time.

Coming from the provider perspective, this timeliness issue is even more aggravating. MSSPs wait months for the initial drop of CMS claims data. On the commercial side, providers working with commercial payers find themselves in the “wild west” when it comes to gaining timely access to these paid-claims.

Beyond Paid-Claims. But wait – the payer side has more to offer than paid-claims data. There are also the data that flows through EDI networks (eligibility checks, referrals, …), and now we see EDI vendors, e.g. NaviNet, formulating PHM offerings that center around leveraging these transactions across their networks. These efforts remain in very early stages and currently focus on fairly mundane but important issues such as leakage.

On the PBM side, the Surescripts network also offers access to eligibility data and med-fill data — a capability that has already been leveraged by many vendors. Specifically Kryptiq (acquired by Surescripts) is currently leveraging these eligibility checks to shine a light on leakage in real-time, within the interface of its Care Manager solution.

Enter Provider-Housed Data Sources. And then there are provider-owned data sources that tend to be more real-time in nature: PMS/billing, labs, ambulatory EHR, inpatient HIS.

Note: The marketing term “real time” is currently up for debate. Usually this means near real time (hourly or nightly). EHRs and labs tend to refresh nightly or weekly. However, the overall trend is for faster refresh rates across all data types.

Granted, clinical data is currently a mess. Data Quality (DQ) problems abound — and high DQ and sufficient trust in the data are precursors to building out real-time alerting usecases. The provider sector as a whole has quite a long ways to go to clean up its data.

HIE vendors tend to be ahead in terms of thinking about real-time alerts that are driven off of clinical data, though most vendors simply just tap into ADT for readmissions usecases. The only vendor that has built up significant real-time clinical alerting capabilities is CareEvolution, a small private HIE vendor based in Ann Arbor, and others we have spoken to are currently building out similar functionality.

How Do We Get People to Pay Attention? This remains the most pressing question. Payers have been trying to get physicians and patients alike to pay attention to their communications for more than a decade, with little success. In speaking with clinicians, most simply say that payer reports are dated, often incomprehensible, relatively meaningless and thus ignored.

Ongoing, real-time population monitoring is just the beginning, a beginning that will need to overcome a number of challenges, chief among them data quality. Cascading the necessary alerts, based on quality datasets into a provider universe that still reels from order-set alerting, and actually getting them noticed — will be the next challenge.

 

 

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Supreme Court Waves Off Software Industry: Bad for HIT

supremeHealthcare depends on new and innovative ideas — often constructed with software. EHRs, HIEs, CPOE, clinical content, medical devices, and numerous medical products are completely or mostly built with software. National governments have helped stimulate innovation over the centuries through the patent system. Inventors devise new, useful and non-obvious things, tell the world about it in a patent application, and receive patents — mini-monopolies that they can then monetize. In exchange for monopoly rents, society receives full disclosure about the invention which encourages other inventors to build on or around the original inventor’s idea. The process nourishes a virtuous circle of innovation, or so the thinking goes.

Whether software-based innovation should be patentable has always been a difficult question. Software does not mesh well with a patent system that was structured for machines. Software patents have been around since the 1970s, but it has never been entirely clear what makes a given software program patentable. A recent Supreme Court decision did nothing to resolve this issue.

Courts have long said that “mathematical algorithms” like “laws of nature” are not patentable. Software is most often nothing more than that — mathematical algorithms translated into code. Yet the number of software patents has exploded in the last decade or so. The problem was exacerbated by changes to the federal court system that resulted in a general philosophy that any patent is better than no patent. The judges and lawyers that run the entire system are patent lawyers — all of whom believe that patents rightly enshrine humanity’s greatest intellectual achievements. Patent trolls, euphemistically referred to as “patent assertion entities”, entered the picture and ratcheted up the speculative fever in what was once a sleepy system of transfers and licensing between big companies. The bottom line is that there is accumulating evidence that software patents do not encourage innovation and may in fact be stifling it.

HIT companies use the patent system as the accompanying data from the US Patent and Trademark Office (USPTO) show. While they do not appear to be big users of the system, other players (e.g., IBM, MSFT, GOOG, ORCL) in the wider economy are. Patent trolls hold patents that HIT companies might inadvertently infringe. Sadly, as in other industry sectors, the majority of HIT companies are resigned to the idea that they might receive cease and desist letters at any time. This is an untenable situation for an industry like HIT in which companies need the flexibility and freedom to innovate.

Quick and Dirty Patent Database Search of HIT Companies

HIT Company

# Patents Found

Sample Patent

Description

Allscripts

8

8,700,428

Managing patient bed assignments and bed occupancy in a health care facility

Athenahealth

7

7,720,701

Automated configuration of medical practice management systems

Cerner

147

8,751,257

Readmission risk assessment

Eclipsys (now part of Allscripts)

10

7,774,215

Enterprise-wide hospital bed management dashboard system

Epic

25

8,731,969

Interactive system for patient access to electronic medical records

Epocrates

7

7,599,846

Method for renewing medical prescriptions

Greenway

8

8,606,593

System and method for analyzing, collecting and tracking patient data across a vast patient population

Medicity

6

8,374,891

Record locator service

Two weeks ago the US Supreme Court issued a widely anticipated opinion on software patentability. Effectively, the Court decided not to decide whether software really is or should be patentable. The Court could well have decided that software is not patentable. Alternatively, it could have spelled out conditions under which software is patentable.

It took neither approach.

Instead, by 9-0 it offered up a brief lesson on the Court’s prior opinions about what is patentable generally, said that the software patent in question was invalid because it was merely an algorithm, and called it a day. The industry is left with the queasy idea that while software patents are everywhere in force, they are valid – unless they are invalid. Uncertainty about software patentability adds to the unpredictability of the licensing and litigation minefield and just exacerbating the problem.

Yet, software inventions should be afforded some protection. After all, software animates innovation. Just because we have a patent system that was designed for physical products doesn’t mean that software inventors be denied the rewards that other inventors have enjoyed for centuries. More importantly, why should society be denied the potential for turbo-charged innovation that the patent system did support once? So far, the federal courts show no ability or inclination to distinguish between good and bad software patents.

Sadly, software patents — under the current system — are not a good idea. It would take a new Supreme Court opinion to say decisively that software patents are indeed patentable and provide clear guidelines – or better yet, instruct the federal government to create clear defensible language that supports software patents. Conversely, Congress could act to refine and clarify the conditions of patentability for software. The latter is unlikely to happen as Congress is beholden to big technology companies, patent trolls and patent lawyers all of whom benefit from the status quo. And the Supreme Court has stated that they will not tread here as well.

We are stuck in a morass.

Without a strong, defensible software patenting system, the software industry, especially for small to mid-size companies, is threatened by questionable litigation that serve no purpose but to extract dubious monopoly rents. Unfortunately, we in the HIT sector who are working to improve the quality of care delivered are under this same threat.

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A Digital Dose of Magic Medicine

snake oilCardiovascular disease is the leading cause of death in America. One out of four adults has two or more chronic diseases. One in three children is overweight or obese. Projections are that by 2050, one third of Americans will have diabetes. These are America’s proverbial ball and chain: lifestyle-driven afflictions that are driving our healthcare spending through the roof, but which can be treated early, mitigated, and in some cases prevented altogether.

Well, what if there was a platform that could help millions to become healthier by encouraging them to take charge of their own health? It could empower people to start living healthier lives through self-driven, day-to-day improvements. Imagine this platform had the following advantages:

  • A high profile, endorsed by celebrities and beloved by households
  • A captive audience that is eager to engage
  • A delivery medium that most of us have in our own homes
  • An information-driven approach to get people to change their lifestyles

The Internet has been abuzz about Apple Healthkit, and Samsung SAMI, and Google Fit.  But more on those in a minute – I was talking about Doctor Oz.

With a TV audience estimated to be nearly 4 million and growing, and a realm of influence that stretches across the web, print media, and television, The Dr. Oz show has made the eponymous physician into a one-man empire with outsize influence over the hearts and minds of middle America. But not all has been healthy in the land of Oz.

As many in our professional circles cheered and jeered, Senator Claire McCaskill called out Dr. Oz as somewhat of a charlatan in front of the country during a testimony on Capitol Hill a few weeks back. Sen. McCaskill is chairwoman of the Subcommittee on Consumer Protection, Product Safety and Insurance, and has taken offense to Dr. Oz’s repeated soft-selling of “magic” pills for weight loss. Across the Internet, opinions abound about the ethical and professional boundaries Oz has breached by pushing products that, as a trained physician, he must know don’t have any scientifically proven benefits.

To be fair, the show and the content are not otherwise awful.The website is fueled by content from Sharecare, the website/startup run by WebMD founder Jeff Arnold and branded by Oz since 2009. Sharecare is a legitimate health IT play – they even hosted a #bluebutton Twitter chat recently, though like Oz, they can overdo the marketing hype at times. And of course, Mehmet Oz himself is a respected cardiologist with appointments at Columbia University and New York Presbyterian Hospital.

The issue isn’t that Oz is a dud – in fact, it’s that he’s far from it, but he still behaves like one when he’s in front of the cameras, either selling the next miracle cure or getting grilled by a former prosecutor now Congresswoman. As health IT’s own celebrity Doc, Eric Topol puts it in a 2013 New Yorker profile:

“He is keenly intelligent and charismatic. Mehmet was always unique, but now he has morphed into a mega-brand…The problem is that he is eloquent and talented, and some of what he says clearly provides a service we need. But how are consumers to know what is real and what is magic? Because Mehmet offers both as if they were one. It all seems to be in the service of putting on a show. And, when you add it up, that seems like something other than medicine. It’s more like medutainment.”

Some have framed the issue in terms of opportunity cost. With such a valuable platform at his disposal, what might be the public health impact be if Dr. Oz was a stronger advocate for judicious diet, steady exercise, and a more balanced lifestyle rather than miracle pills?

The sad truth is, people probably wouldn’t watch his show. In fact, he probably wouldn’t even have a show in the first place. Oz’s style-over-substance delivery is shaped by his studio audience, not the other way around. He has become so popular because the people watching his show crave shortcuts and quick fixes the same way they crave fast food. To give credit where it’s due, Oz understands the American people better than most of us in healthcare. Now if only he would lead some meaningful patient engagement on our behalf.

As much as we complain about silos in health IT, ignoring what’s going on on daytime TV reinforces our separation from the broader challenges we face in healthcare. We keep ourselves busy dissecting new smartphone platforms like Healthkit and hyping up their allure within our white-collar circles, even as we lose sight of the real competitors. Taco Bell too has been innovating for the masses. Think of five people you know – are they more likely to make sure their labs and meds are up to date for their next doctor’s appointment, or buy a 99-cent Quesarito? Automating data entry on these new platforms might possibly get us past the wall that the PHR industry collided with a few short years ago. But no amount of app automation will let us swipe past our own human nature.

In our innovation-addled culture, it’s understandable when people get excited about unproven promises sold to us by corporate wizards, whether in the form of a “magical” diet pill or a “transformative” ride sharing service or a “revolutionary” smartphone app. Dr. Oz’s recent episode serves as a reminder that in healthcare, there are a different set of standards when it comes to the believing the unproven. As healthcare professionals, we too can be tempted to take a seat in the studio audience and add to the chorus of oohs and aahs about new technology.

Let’s just remember that our industry may be part art and part science, but there’s no magic involved.

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Can Apple Keep the Doctor Away?

health“His treatment was fragmented rather than integrated. Each of his myriad maladies was being treated by different specialists – oncologists, pain specialists, nutritionists, hepatologists, and hematologists – but they were not being coordinated in a cohesive approach.”

Steve Jobs, by Walter Isaacson (p. 549)

As you’ve undoubtedly heard, Apple made a big splash last week by announcing “official” involvement in healthcare through a new app and accompanying SDK. In the past week much fanfare has been made and many speculations have been raised. As an industry that is built on the notion of looking forward, the obvious question right now is, “Will Apple Succeed?” An important precursor however is, “What is Apple trying to do?”

The announcement at WWDC was scant on details, comprising just three minutes of the broader two-hour session. More detail is available elsewhere, but the basics are that this fall, Apple will release an app called “Health” to track and store multiple health data, mostly from devices, of around 60 parameters upon release with iOS 8. The app will enable selective sharing of data, across other apps or with other individuals. The app’s release coincides with the pre-release of an SDK called “HealthKit”, designed to allow third party apps built with HealthKit to be able to have common data structures for data management, sharing, and privacy control. Two early partners were announced in Mayo Clinic and Epic, though details of those partnerships are still TBD.

So the vision here appears to be that patients and healthcare providers can use multiple apps written on Healthkit, all through a consumer-controlled, portable hub (that also makes calls!) to help fill the healthcare void when patients are away from a health facility.  Sound familiar? So much for “Think Different” – Apple is not trying out anything new here. Rather, they are betting that this particular formula of consumer-friendly hardware, new software, brand strength and market clout can result in a win. But they are also, finally, addressing a problem that has plagued health apps for years: an inability to aggregate data into one spot for a more complete view of one’s health.

Over the long term, the web-dominant approach to the above vision is slowly dying; the notion of sitting down at a computer to upload workouts or blood sugar readings into a website already seems antiquated compared to automated tracking on a device. So if mobile truly is the future, then Apple seems better positioned then others to capitalize on that trend, save Samsung.

With Samsung’s recent announcement of the SAMI platform, their S-Health app on the S4 and S5, and other recent activity in health IT, they too have arrived to the party. We will cover both tech titans’ varying approaches more deeply as part of the CAS as details around them emerge. For now, looking at ghosts of PHRs past as well as the current mHealth environment, we can point to several issues that will define the success or failure of Apple and their contemporaries.

Timing: Compared to predecessors, Apple has the benefit of timing on their side. Consumer-friendly hardware is now ubiquitous in the market (much of it Apple’s) and growing in sophistication. Healthcare software has decidedly shifted in a mobile-friendly direction, from a wellspring of APIs from major HIT vendors to emergence of standards like HL7’s FHIR. With the MU3 PGHD provision set to roll out this fall, the timing here could work out in Apple’s favor.

Wellness vs. Health: Many from Aetna to Microsoft have struggled trying to straddle the fence between wellness and medical care. We suspect Apple will be no different. Despite the umbrella of “health”, fitness tracking and condition management are two different marketplaces. Apple’s best bet for success may be to drive Wellness growth through B2C efforts, and drive clinical adoption through healthcare partnerships and clinical evangelists. For now, it is Apple’s best interest (and the broader industry’s collectively) to keep these lines blurred.

Quality and Curation:  With regards to adoption, the biggest healthcare complaint about mHealth is that there is too much going on. With over 43,000 apps available in some flavor of health, Healthkit adding more may not necessarily be better. It remains unclear what Apple’s involvement at this level will look like, but if they really want to get a foothold in the marketplace, they are best served by addressing this issue on some level.

Data: Apple is essentially the Epic of their industry: They’re big and well-fed and they don’t play well with their peers. Apple may take the same approach that Epic took before being regulated into interoperability by the ONC; they are big enough and far enough outside of healthcare that the NPRM for Stage 3 PGHD might not matter to them.

Closing Thoughts: Potential vs. Reality

At this early stage, questions can go on forever. Speculation aside, one thing we can safely say is that Apple is not all of a sudden a healthcare company. With this recent announcement they have simply provided some new tools to a broken industry, tools that appear to be arriving at the right place, at the right time.

Hopes seem to be higher within the healthcare industry and across the blogosphere that this is just a first step for Apple. With its beloved brand, vast resources, design-driven thinking, and technological expertise, many are rooting for Apple to be the one to rewrite the chapter on enterprise mHealth strategy. Realistically however, Apple’s goals here are likely more simple: to sell more phones, tap directly into a booming mHealth market (Remember, Apple keeps 30% of all app revenue), and grease the wheels of their widely rumored iWatch rollout.

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