How Much Of The Healthcare Business Is Healthcare?

In The Great Re-Bundling of Healthcare, I argued that healthcare will be rebundled along new dimensions because technology will break assumptions that predicated bundling in the analog era of healthcare delivery.

In that post, I noted that a few industries have been completely dismantled and rebundled by technology:

The print publishing industry – newspaper and magazines – thought that their unique value was in their core product – news, editorials, and classifieds. But the unique value they delivered was in printing and distribution. When the Internet reduced the cost of printing and distribution to effectively $0 and free news became the standard, their businesses collapsed. Print publishers are left servicing the paper news market, which is a fraction the size of the overall digital news market.

Taxi companies thought that their local, retail, administrative, and regulatory overhead was necessary to solve the get-from-point-a-to-point-b problem. Using the Internet, Uber, Lyft, and SideCar proved that none of those overhead functions matter, enabling a new era of get-from-point-a-to-point-b solutions. Taxi companies are left servicing the I-haven’t-heard-of-Uber and there-aren’t-enough-Uber-drivers markets, both of which are rapidly shrinking.

Hotels thought constructing buildings and staffing employees was the only way to solve the get-a-place-to-stay-for-the-night problem. Using the Internet, AirBnB proved that anyone can solve the get-a-place-to-sleep-for-the-night problem for anyone else. Hotels are left servicing the high-end, premium service market in the get-a-place-to-stay-for-the-night business.

These examples beg the question: when healthcare is completely rebundled around digital delivery, what businesses will healthcare providers really be in?

In the examples above, the Internet empowered laymen to circumvent legacy establishments. Using the Internet, laymen performed the same tasks more affordably than traditional retail businesses.

With Watson-like self-diagnostics; an army of cheap, connected, sensors; and a wealth of freely available information on the web, laymen will increasingly self-diagnose and self-medicate whenever and however possible. This process will start at the low end – the simple stuff such as common colds, simple bumps and bruises – and increasingly move up market.

Over time, tri-corders (such as Scanadu), smartphone EKGs (such as AliveCor), smartphone ultrasounds, CTs, MRIs, and blood tests will empower patients to gather all of the necessary diagnostic information without ever visiting a retail medical facility. Patients will send data to providers electronically and consult with providers via video conference. The web will obviate the need for most retail overhead, capital expenditure, and labor cost associated with most care delivery.

Medicine will be disrupted from the bottom up. Hospitals won’t completely go away, but they will be left servicing the high-end of the market – ICUs, surgery, labor and delivery, and other high-acuity conditions – just as hotels, print publications, and taxis service the most expensive segments of their respective markets. The vast majority of care will be delivered as virtually and cost effectively as possible.

By circumventing retail establishments, medicine will centralize as geography loses relevance. Just as the hotel and taxi industries consolidated around mega-platforms such as Uber and AirBnB, healthcare will consolidate around provider hubs that service enormous populations. The mega healthcare systems will have the tools to centrally manage populations and interact with them contextually. The major health systems of the analog era that were bounded by geography will battle to become national behemoths as geography becomes irrelevant. Mayo Clinic, Cleveland Clinic, and others are already doing this by establishing virtual clinics across the country.

Why did the publishing industry, taxi industry, hotel industry, and travel agency industries collapse? Why will all of the old practices of medicine collapse? Cost. The most costly aspects of delivering care are labor and retail overhead. As increasingly small, localized, connected computers gather an increasingly large amount of data, computers will help patients self-diagnose and self-medicate without the need for expensive retail or labor overhead. Computers will automate inherently repetitive processes.

The Fundamental Challenge of ACOs

This post was originally featured on EMRandHIPAA.

I’ve been openly bullish on ACOs and capitated payment models. The only way to achieve the triple aim – quality, cost and access – is to create a system that is structurally incentivized towards those ends. The fee-for-service model will never be structured in a way that incentivizes the triple aim. On the other hand, ACOs do.

Early ACO data is mixed. Although some organizations succeeded in lowering costs and improving outcomes, about 1/3 dropped out of the ACO program entirely, and another 1/3 reported no significant cost or quality changes. Only 1/3 were “successful.”

Why? Why did some organizations succeed where others failed? What did each organization do differently? It’s been proven that some organizations can succeed under this model. But not everyone.

ACOs are disruptive to fee-for-service payment models. ACOs invert incentives. They invert how every employee should think about their job in the context of the larger care delivery system. In ACOs, healthcare professionals are implicitly asked to think about preventative care, which tends to lead towards both cost and quality improvements. On the other hands, in a fee-for-service model, healthcare professionals are only incentivized to simply treat the patient in front of them with no regard for prevention or cost.

When the board of directors of a given organization recognizes the need to change the course of a business, the board usually replaces the CEO. After a new strategy is devised, the new CEO typically replaces most of the executives and lays off a significant number of the existing staff. This accomplishes a few things:

1) reduces the burn, making the organization leaner and more capable of pivoting
2) replaces lots of senior and middle management, who were trained and wired around the old business model, and who may conspire against the new model if they don’t believe in it
3) sends a signal to the remaining staff that management is serious about change

Although this plan doesn’t guarantee success, it’s fairly common in large organizations because it can create impetus to break from the inertia of the status quo. The only thing worse than going after the wrong business model is maintaining one that’s failing.

This of course begs the question, how are providers adopting ACOs? Management at provider organizations that have adopted the ACOs are early adopters. They are pioneers. They are leaders. They can see a new, better, ACO-based future. The last thing management at these organizations is going to do is fire themselves after deciding to transition to an ACO.

In light of the above, I am particularly impressed by the early success of the ACO program. Only 1/3 dropped out. Given the fundamental change at hand, I would consider the early data a harbinger of better changes to come. I suspect that almost all of the remaining ACOs will see more significant improvements in years 2 and 3 as they mature and refine processes around value.

The Pristine Story: Planting Seeds For Growth

50% of patient wait times in the ER can be attributed to waiting for specialists to arrive. The ER staff at Rhode Island Hospital (affiliated with Brown University) are using EyeSight to beam consulting physicians into the ER when consulting physicians would otherwise be unable to physically come in and see patients. We'd like to highlight the clinicians at Rhode Island Hospital, who recently went live with Pristine EyeSight in the ER. We'd like to especially thank Dr. Paul Porter, Dr. Peter Chai, and Dr. Roger Wu for driving the project. You can see videos EyeSight live by clicking on the image above.

Over the past couple of months, we've been working tirelessly to ensure smooth EyeSight rollouts. We've been building out robust test suites, automating deployment mechanisms, and building out new layers of security and authentication. You can take a peek inside by checking out the Pristine engineering blog.

We continue to grow the team. We recently brought aboard 2 new salesmen - Jason Sorrells, and Justin Cannon - both of whom have years of experience selling medical devices and health IT solutions. They're operating regionally throughout the US and helping us reach environments that we would have otherwise been unable to reach.

And as always, we continue to blog away. This month, we'd like to highlight a post from our Client Success Manager, Brett Hogan, who outlined some of the challenges that hospitals and physicians are facing as they try to adopt Glass out-of-the-box.

Why ICD-10?

This post was originally featured on EMRandHIPAA.

At least half a dozen folks have asked me to explain why HHS is mandating the transition to ICD-10. So I thought I’d write a blog post about the subject.

First, I’ll examine some of the benefits that proponents of ICD-10 site. Then, I’ll examine the cost of transition from ICD-9 to ICD-10.

There are about a dozen frequently cited reasons to switch from ICD-9 to ICD-10. But they can be summarized into three major categories:

1) The US needs to catch up to the rest of the world.

2) The more granular nature of ICD-10 will lend itself to data analysis of all forms – claims processing, population health, improved interoperability, clinical trials, research, etc.

3) ICD-9 doesn’t support the latest diagnoses and procedures, and ICD-10 does.

Regarding #1, who cares? Coding standards are intrinsically arbitrary. Sequels are not necessarily better than their predecessors.

Although #2 sounds nice, there are a lot of problems with the supposed “value” of more granular data in practice. Following the classic 80-20 rule of life (80% of value comes from 20% of activity), the majority of codes are rarely used. By increasing the number of codes six-fold, the system is creating 6x the opportunities to inaccurately code. There is no reason to believe that providers will more accurately code, but the chances of incorrect diagnosis are now significantly higher than they were before. Garbage in, garbage out.

Below are some specific examples of how increasing the number of codes will affect processes in the healthcare system:

Payers – payers argue that making codes more granular will improve efficiency in the reimbursement process by removing ambiguity. There is nothing further from the truth. Payers will use the new granularity to further discriminate against providers and reject claims for what will appear to be no reason. With 6x the number of codes, there are at least 6x as many opportunities for payers to reject claims.

Clinical trials – ICD-10 proponents like to argue that with more granular diagnosis codes, companies likeePatientFinder can more effectively find patients and match them to clinical trials. This notion is predicated on the ability of providers to enter the correct diagnosis codes into EMRs, which is a poor assumption. Further, it doesn’t actually address the fundamental challenges of clinical trials recruitment, namely provider education, patient education, and the fact that most patients aren’t limited to trials by diagnosis codes, but rather by other data points (such as number of years with a given disease and comorbidities).

Public health – ICD-10 proponents also claim that the new coding system will help public health officials make better decisions. Again, this is predicated on accuracy of data, which is a poor assumption. But the greater challenge is that the most pressing public health issues of our time simply don’t need any more granularity in diagnosis codes. Public health officials already know what the top 20 public health problems are. Adding 6x the number of codes will not help address public health issues.

Regarding #3, why do we need to reinvent the entire coding system and make the entire system more granular to accommodate new diagnoses and procedures? Why can’t we continue to use the existing structure and simply create new branches of the ICD tree using alphanumeric characters? Why do we need to complicate every existing diagnosis and procedure to support new diagnoses and treatments? We don’t. There are plenty of letters left to be utilized in ICD-9 to accommodate new discoveries in medicine.

Next, I’ll provide a very brief summary of the enormity of the cost associated with transitioning from ICD-9 to ICD-10. The root of the challenge is that a string of interconnected entities, none of whom want to work with one another or even see one another, must execute in sync for the months and years leading up to the transition. Below is a synopsis of how the stars must align:

EMR vendors – EMR vendors must upgrade their entire client base to ICD-10 compliant versions of their systems in the next couple of months to begin testing ICD-10 based claims. Given the timescales at which providers move, the burden of MU2 on vendors, and the upgrade cycles for EMR vendors, this is a daunting challenge.

Providers – providers don’t want to learn a new coding system, and don’t want to see 6 times the number of codes when they search for basic clinical terms. Companies such as IMO can mitigate a lot of this, but only a small percentage of providers use EMRs that have integrated with IMO.

Coding vendors – like EMR vendors, auto-coding vendors must upgrade their clients systems now to one that supports dual coding for ICD-9 and ICD-10. They must also incur significant costs to add in a host of new ICD-10 based rules and mappings.

Coders – coders must achieve dual certification in ICD-9 and ICD-10, and must double-code all claims during the transition period to ensure no hiccups when the final cut over takes place.

Clearinghouses – clearinghouses must upgrade their systems to support both ICD-9 and ICD-10 and all of the new rules behind ICD-10, and must process an artificially inflated number of claims because of the volume of double-coded claims coming from providers.

Payers – payers must upgrade their systems to receive both ICD-9 and ICD-10 claims, process both, and provide results to clearinghouses and providers about accuracy to help providers ensure that everyone will be ready for the cut over to ICD-10.

The paragraphs above do not describe even 10% of the complexity involved in the transition. Reality is far more nuanced and complicated. It’s clear from the above that the likelihood that all of the parties can upgrade their systems, train their staff, and double code claims is dubious. The system is simply too convoluted with too many intertwined but unaligned puzzle pieces to make such a dramatic transition by a fixed drop-dead date.

Lastly, switching to ICD-10 now seems a bit shortsighted in light of the changes going on in the US healthcare system today. ICD-10 is already a decade old, and in no way reflects what we’re learning as we transition from volume to value models of care. It will make sense to change coding schemes at some point, but only when it’s widely understood what the future of healthcare delivery in the US will look like. As of today, no one knows what healthcare delivery will look like in 10 years, let alone 20. Why should we incur the enormous costs of the ICD-10 transition when we know what we’re transitioning to was never designed to accommodate a future we’re heading towards?

At the end of the day, the biggest winners as a result of this transition are the consultants and vendors who’re supporting providers in making the transition. And the payers who can come up with more reasons not to pay claims. Some have claimed that HHS is doing this to reduce Medicare reimbursements to artificially lower costs. Although the incentives are aligned to encourage malicious behavior, I think it’s unlikely the feds are being malicious. There are far easier ways to save money than this painful transition.

The ICD-10 transition may be one of the largest and most complex IT coordination projects in the history of mankind. And it creates almost no value. If you can think of a larger transition in technology history that has destroyed more value than the ICD-9 to ICD-10 transition in the US, please leave a comment. I’m always curious to learn more.

One Small Wink For Man, One Giant Head Nod For Mankind

We would love to issue a huge congratulations to our partners at Rhode Island Hospital (RIH). They just went live with Pristine EyeSight on Google Glass in the ER for dermatology consults.

One of the fundamental challenges of delivering care in an ER is that patients can show up at any time of day with any problem. Often times, the ER staff need to call in a specialist. The problem is that those specialists aren't sitting around doing nothing; they're usually busy in their own clinics (which are rarely in the same building), or at home on call. The physicians and nurses at RIH are using EyeSight on Glass to beam in dermatologists on demand. This is a significant win for all parties:

For the patient - the patient will been treated more quickly than they otherwise would have, which reduces clinical risk and allows the patient to go home sooner. Approximately half of all wait times in ERs can be attributed to waiting for the right provider to arrive.

For the local provider - the local provider will spend less time hunting down the specialist in need, and will finish the exam with the patient more quickly, leading to increased throughput. The local provider may even go home sooner and see their children sooner :).

For the consulting provider - the consulting provider derives an enormous efficiency benefit. EyeSight saves them the pain of driving in or walking over. If the consulting provider is forced to leave their clinic, their clinic schedule will fall behind, leaving all of their patients unhappy and frustrated.

For the ER - the ER benefits by improving throughput, reducing risk, and ultimately increasing HCAHPS scores (which have a high correlation with wait times in outpatient settings).

Last week, the clinical teams at RIH went live with Pristine EyeSight. ER physicians are using EyeSight to securely beam in dermatologists to provide live consultations of skin wounds, rashes, and lesions in the ER. Because dermatologists work in fast-paced outpatient clinics, it's been difficult for dermatologists to come into ERs to see patients. Using Pristine EyeSight, we're improving access and outcomes in ways that were never before possible.

Looking ahead, there are even greater opportunities. We started with dermatology in the ER. We can't wait to leverage this technology with other specialties in the ER, and throughout the hospital.

We've been working with RIH's leadership team for months, and couldn't be happier with the results. We'd like to send a special shout out to Dr. Paul Porter, Dr. Peter Chai, and Dr. Roger Wu for their tenacity in helping us through the Institutional Review Board (IRB), IT, and administrative processes so quickly and diligently to make this a reality.

And lastly, as CEO, I'd like to thank our team for all of their hard work to make this a reality. We've been refining the system for a long time to ensure high reliability and performance. Our client success team has also done a spectacular job in training and deployment.