Calling Dr. Berwick

On April 27, 2004, President George Bush signed Executive Order 13335 establishing the position of the National Health Information Technology Coordinator. Six years, a recession, a change of administration, a couple of major legislations and a multitude of billions of dollars later, the Office of the National Coordinator for Health Information Technology (ONCHIT) is finally on the road to delivering on the original vision behind that executive order.

The stated mission of ONCHIT, as reiterated in the HITECH Act, was the creation of a nationwide interoperable health information technology infrastructure that makes pertinent information available at the point of care, improves health care quality and coordination, reduces health care costs and disparities and does all that while protecting privacy and security. While the 2004 executive order did not go into much operational detail, the HITECH Act provided instruction on the structure and strategy for building the HIT infrastructure. It is interesting to note that the HITECH Act is comprised of two Titles; Title XIII in Division A which outlines the activities expected from ONCHIT and Title IV in Division B which creates the Medicare & Medicaid stimulus incentives to eligible providers. The notorious “Meaningful Use” term appears only in Title IV and only as a prerequisite for stimulus incentives from CMS and is loosely defined by certified technology, electronic prescribing, information exchange and reporting on clinical quality measures. Additional guidance is provided on the selection of clinical quality measures to be in accordance with Section 1890(a) of the Social Security Act, which awards CMS $10 million every year for contracting development of such measures. Meaningful Use seems a rather benign litmus test for CMS to administer prior to dispersing any stimulus incentives. So why is it that “Meaningful Use” became the defining substance of the ONCHIT mission?

From the first meetings of ONCHIT (or ONC for short), Meaningful Use was seen as the centerpiece for the definition of a roadmap to that elusive nationwide interoperable health information technology (HIT) infrastructure. Meaningful Use Stage 1, Stage 2 and Stage 3 were presented as the milestones on the roadmap to success and, as such, ONC assumed an active role in defining the various Meaningful Use stages. Basically, the interoperable HIT infrastructure is not defined according to the capabilities it must have, but instead it is defined in terms of what users of the emerging infrastructure must achieve in order to obtain incentives. This was largely hailed as a wonderful approach. Instead of just building standards and tools to facilitate a nationwide information exchange, we first mandate what we want to exchange, how it should be recorded, who should record it and where it should be reported, and only then do we build the infrastructure to support our mandates. We then throw in some cash and some penalties just to be sure that if we build it, they will indeed come. Sounds very reasonable, except who is “we”?

Now that Stage 1 of Meaningful Use has been largely put to bed (a few minor adjustments not withstanding), ONC is turning its attention to Stage 2 and perhaps Stage 3. Presumably there will be more of what Stage 1 required, many of the capabilities required in Stage 1 will morph into requirements for actual execution, more data will need to be captured and actually exchanged, more standards will be defined and more clinical performance measures will need to be reported. And just like Stage 1, it seems that ONC is leading the charge for Meaningful Use, instead of CMS who will end up just publishing the requirements. No surprises here, except a brand new workgroup of the Health IT Policy Committee chaired by Dr. Blumenthal himself – a Quality Measures workgroup. There is already a Clinical Quality workgroup in the Health IT Standards Committee, so I was intrigued by the policy aspects of quality measures and ONC’s need to address them.

From listening to the first meeting of the Quality Measures workgroup, it seems this is a group of well-intentioned and very talented folks trying to figure out what clinical indicators should be required for Meaningful Use Stage 2 and Stage3 reporting. The main considerations cited in this meeting were parsimony and HIT-sensitivity; parsimony, in the sense of few broadly applicable measures and HIT-sensitivity in the sense of measures best enabled by EHR technology. The entire conversation (transcribed here) is most interesting. The ONC workgroup is aiming at thoroughly examining work done by traditional quality measures builders, such as NQF, and coming up with its own recommendations to support various health care and health care policy goals. The discussion ranged from how clinical measures should support sustainability goals of federally funded Health Information Exchanges (HIE) to their ability to enable operations of Accountable Care Organizations (ACO) to the fact that lipids measurements should be stratified by risk factors.

It seems that ONC is not solely in the business of providing tools and standards to enable the practice of quality medical care as defined by CMS, but it is actively engaged in deciding how medicine will be practiced in the future. I am not entirely certain how this transformation occurred or whether the initial intent was indeed to have Health Information Technology drive the practice of medicine.

And where is CMS? Where is Dr. Berwick?

By all accounts, the most experienced and knowledgeable visionary leader when it comes to quality of health care, is the new CMS Administrator, Dr. Donald Berwick. From his position as Vice President of Quality-of-Care Measurement for the Harvard Community Health Plan, to the Quality Improvement in Health Care demonstration project, and finally to the Institute for Healthcare Improvement (IHI), one would be hard pressed to find anyone better suited to guide health care quality improvements and shape the meaning of Meaningful Use.
So why is it that health care quality improvements and measurements are left to the technology folks? Isn’t this where Dr. Berwick was supposed to provide unrivaled leadership for the entire nation?

Diffusion of EHR Innovation

No matter what your opinion of Electronic Health Records (EHR) is, you would probably agree that the concept of computerizing medical records represents an innovation of sorts. The spread of innovation, or its diffusion, has been researched and modeled by Rogers[1] as a bell shaped advancement through populations of Innovators, Early Adopters, Early Majority, Late Majority and Laggards (the blue curve in the figure below). At some point during this spread of an innovative solution a Critical Mass of adopters, or Tipping Point, is reached and the innovation is assured widespread diffusion (Gladwell[2]).  Adoption is usually described by an S-shaped curve of adopters vs. time, and the rate of adoption is the slope of the S-shaped curve at any given time (the red curve in the figure).

The Tipping Point occurs right after the rate of adoption assumes its largest value which will be maintained throughout most of the adoption process. It is worth noting that the diffusion of innovation model is not predictive. Many innovations linger and die within the Innovator circle. Another important aspect of the model is that the time variable is not constrained. Depending on the rate of adoption, it may take weeks, months or many years for an Innovation to spread throughout a given population. There is no question that EHR adoption is slowly moving up on the ascending side of a classic diffusion model bell curve, but is it moving fast enough? Is the tipping point visible? Are we there yet?

In order to answer these questions and assess where we are on the path to EHR adoption, we must examine the elements affecting diffusion of new ideas, objects or practices, i.e. Innovations, as they pertain to EHRs.

The Innovation – Not all things classified as Innovations are equal and this may explain why some succeed in becoming main stream and others fail. Rogers[1] suggests four defining characteristics of innovation:

• Relative Advantage – To what degree is the EHR perceived to be better than the practice it aims to supersede – paper charts? The daily debates on the merits of EHR in various health care forums are stark testimony to the fact that potential users are sharply divided on the answer to this question. For some, EHRs are increasing efficiency and improving quality of care for patients. For others, EHRs are impediments to quality of care and an endless money pit for the practice. The biggest advertised advantage of EHRs, interoperability, is little more than a promissory note issued by EHR proponents to prospective adopters. The Government is adding an advantage in the form of stimulus incentives and future financial penalties for non-adoption. This advantage seems to be significant for hospitals and large groups, but less so for small private practices.
• Compatibility – Are EHRs compatible with existing values, past experiences and needs of potential adopters? Here EHRs are being propelled onto the much larger stage of health care reform. They are no longer a humble replacement of pen & paper and fax machines. EHRs are instruments of change; a change from treating one patient at a time the best you can, to considering value-based strategies for the benefit of entire populations, and considering those right at the point of care. This seems to be a major departure from a value system created and enriched across many generations of medical doctors.
• Complexity – Simplicity is always a virtue. The complexity of hospital EHRs, with their unwieldy CPOE modules, has created a perception of EHRs being rigid and unduly complicated tools, which take years to master.  The simple ambulatory EHRs available today, have failed to change these perceptions. To be fair, EHRs are inherently more complex than a piece of paper, but that should not necessarily deter adoption. After all, the wheel was more complex than walking, and making fire was extremely hard initially.
• Trialability – Experimenting with small parts of an innovation before taking the final leap reduces adopters’ risk and anxiety. EHRs can be, and mostly are, implemented in stages, particularly in hospitals. In the ambulatory sector there was a trend to implement electronic prescribing as a trial before complete computerization. Perhaps the best exercise of Trialability for EHRs is the free trials offered by too few vendors.
• Observability – An innovation is more likely to be adopted if its results are easily visible to others. This of course assumes that the results are positive. Unfortunately, successful implementations of EHRs are uneventful and largely anonymous, while their failing counterparts, usually associated with astronomic losses in funds and sometimes lives, are very visible, heavily advertised and frankly more interesting. There is no news in a 3 physician practice in Omaha installing a mid-priced EHR and having no problems to report.

Communication Channels – The news and evaluation of an innovation are spread throughout the community by various means, from mass media to informal peer to peer communications. As every EHR vendor knows, the latter is the most prevalent and effective method of disseminating messages amongst physicians. It is also a very slow method of creating awareness and unless the innovation is indisputably positive, much confusion is created by conflicting messages from friends and colleagues, thus slowing down the diffusion process. The Government’s intervention, with all its glorious publicity and billions of dollars in support of the innovation, is doing wonders in bypassing the conventional “word of mouth” diffusion mechanism. The downside is that EHR is now associated with Big Government and a particular flavor of politics.

Time – Time is involved in diffusion of innovation in several ways.

• On an individual level the innovation–decision process goes through five stages known as: knowledge – persuasion – decision – implementation – confirmation. In EHR industry parlance, these translate to: research – assessment – selection – implementation – adoption. The shorter the innovation-decision individual cycle is and the more people actually complete it without dropping out in its midst and the more positive their adoption experience is, the faster an innovation is expected to diffuse. For EHRs this cycle can range anywhere between a few months for a small practice to several years for a large hospital. The Government imposed Meaningful Use schedules are shortening the innovation-decision cycle for those racing to qualify for maximum incentive. Perversely, the inadequate time allowed for implementation will also increase failure rates and adverse events, which does not bode well for long term diffusion rates.
• Diffusion is also affected by the Innovativeness of the population targeted by the innovation. Here is where we encounter the accusations of physician being inherently opposed to technological advancements, and the counter arguments based on the number of iPhones and iPads already owned by physicians, not to mention all the advanced technologies in imaging, surgery and other medical fields, which are readily embraced by the medical community. When it comes to EHRs though, most docs don’t mind being very late adopters or even laggards.
• The rate of adoption dictates how much time it will take for an innovation to diffuse throughout the system. Unfortunately for EHRs, the rate of adoption is heavily dependent on the 5 characteristics of an innovation and none of those are particularly stellar for EHRs. This is why the rate of EHR adoption prior to HITECH has been lingering at the bottom of a very wide S-curve. The Government intervention, which as mentioned above is increasing the financial advantage, is making a marked difference in the rate of adoption effectively pushing EHRs up the S-curve.

The Context – Innovations are diffused within the boundaries of a social system. The structure, norms and leadership of a system also affect the diffusion of innovations.  Systems whose members are similar in education, social status and beliefs (homophilous) are not well suited to rapid change and innovation. Physicians arguably do form such system. The historical low rates of EHR adoption could be attributed to lack of accepted opinion leaders in general, and those who view EHRs as a positive innovation in particular. The public personas that have an MD after their name and relentlessly advocate for EHR adoption are usually not practicing physicians and as such, are not accepted as respected opinion leaders by most practicing doctors.

The diffusion patterns described so far are assuming that the innovation is optional for any given individual. However, innovations are not always an individual choice. Sometimes the decision to innovate is Authority Driven. Authority driven innovations are faster to be adopted and depending on the level of coercion, may follow a completely different path. Up to HITECH, individual physicians in private practice considered EHRs optional. Those employed by hospitals or large groups were experiencing the effects of authority driven innovation all along, thus the much larger adoption rates in those sectors. Although EHRs are not yet mandatory, the increasing pressure exerted by Government incentives, regulations and penalties is changing the diffusion patterns of the EHR innovation.

Keep in mind that Government exertions do not need to continue until every physician in the country has purchased an EHR. They only need to ensure a critical mass of EHR adopters is created and the mythical Tipping Point is reached. The Tipping Point is usually observed at about 15% adoption under normal circumstances and is marked by the emergence of opinion leaders who adopted the Innovation. EHRs and health care in general are anything but normal and I would expect a larger percentage of adoption to be required before EHRs “take off” in a self-sustaining fashion. As to respected opinion leaders, there are none.

So are we there yet? I don’t think so, but we are awfully close.
__________________________________________________
1. Everett M. Rogers (1995), Diffusion of Innovations (Fourth Edition), New York, Free Press.
2. Malcolm Gladwell (2000), The Tipping Point: How Little Things Can Make a Big Difference, New York, Little Brown.

The Red, White and Blue Buttons

On August 3rd President Obama announced the advent of a new button: The Blue Button. The Blue Button is a health data download button. Consumers can presumably click on the Blue Button and their medical records will then commence downloading to their computer (securely, of course). Anybody can get a complete medical record on demand; with no delays from the busy medical records department and no special fees and no rims and rims of paper records to carry around. Sounds like an awesome step forward for medical records portability.

The Centers for Medicare & Medicaid Services (CMS) will make Blue Buttons available for Medicare beneficiaries and so is the Veterans Administration (VA). The Markle Foundation issued a policy paper and a challenge to developers to do something meaningful with the Blue Button data (in partnership with Health 2.0). Crunching the numbers yields about 30% of us with full electronic access to our medical records by virtue of a Blue Button. This is all very exciting and definitely warrants a closer look.

The VA delivers health care and it has an EHR (VistA) and gigantic amounts of electronic medical records to share. The VA also has a website, My HealtheVet, where members can access their latest medical records, view benefits and perform simple transactions, such as requesting meds refills and updating information. My HealtheVet, which is truly a PHR, will now be sporting a Blue Button, so members can download their electronic medical records in ASCII text format. The VA has a sample download file and it looks very useful.

CMS, on the other hand, is basically a payer. CMS will be adding the Blue Button to their member portal, MyMedicare, where claim data will be available for download and also, what seems to be, Self Entered clinical data. Presumably Medicare beneficiaries will update their clinical histories and then push the button to download the file, also in ASCII text format. Unlike the VA, CMS is not quite ready to allow beneficiaries to download this data to their own computers, but prefers that the data is transferred to a commercial PHR instead (e.g. Google Health, Microsoft Health Vault). Why CMS thinks beneficiaries cannot be trusted with their own data, while commercial PHRs can, or how they propose to prevent consumers from keeping copies of their own data, is a bit unclear to me at this point, but CMS “may be conducting a project called "the BlueButton"” to test the concept. As we all know, CMS is very good at pilot projects, so we will probably learn more in time.

The Blue Button is a step in the right direction, but immediately exposes one big problem, a problem that has plagued health care informatics from the start. The VA Blue Button and the CMS Blue Button are creating incompatible text files. There is no common standard for the downloadable information.  Fields have different names (e.g. DOB vs. Date of Birth) and different definitions (e.g. First Name, Last Name vs. Full Name) and objects (e.g. Allergies, Problems) have different subfields. If you compare the VA file and the CMS file, you would be hard pressed to guess that their intended use is identical. Any commercial PHR interested in receiving and incorporating Blue Button files will have to write two separate sets of software to process both VA and CMS files. If private EHRs and payers start adding Blue Buttons to their portals, each providing different information in different formats, we will end up with yet another bewildering array of incompatible data. Shouldn’t the parent “company” of both the VA and CMS (the Federal Government) have defined a Blue Button standard first?

While the Feds work out the Blue Button kinks, I would like to suggest two other buttons that may be even more beneficial than the Blue one, and together will make quite a patriotic splash on any website.

The White Button, so named for those wearing white coats while at work, should allow a physician to get all records for the patient in front of her/him with one click of the White Button. We have the beginnings of a White Button in the form of the, almost complete, medication list that can be obtained in real time from Surescripts. We should build on that concept, which interestingly enough, evolved without the support of massive infrastructure financed by Federal stimulus money. It just made good business sense and it works like a charm.

The Red Button, which will hopefully be used less and less as technology improves, should allow any clinician and any patient who uses health care technology to report safety issues to the FDA, from within the software, and as they occur. Much has been written lately on the need for physicians and hospitals to admit errors, apologize and learn from mistakes. We want to measure quality of physicians’ work and pay them according to outcomes. The same logic should apply to EHR vendors. The Red Button will be our quality measurement tool and should be viewed by HIT vendors as a learning tool as well.
Pay 4 Performance is a two way street.

Appropriately, the day when EHRs routinely come with Red, White and Blue Buttons will be the day we will know that HIT victory has been achieved.

Medicaid EHR Incentives – A Learning Experience

By now almost everybody that has any remote interest in Health Care is aware of the much publicized incentives made available to health care providers for the adoption and meaningful use of certified EHR technology. The most quoted number is $44,000 to be paid by CMS to Medicare physicians. Practically every EHR vendor website is adorned with a Flash banner “educating” doctors on this cash windfall, and practically every HIT detractor is warning that the incentives are just a pittance compared to the real costs of ownership of a certified EHR. Very rarely does anybody go into the intricacies of the available incentives for Medicaid providers, which are almost 50% higher than Medicare and involve clinicians providing care to our most vulnerable citizens. However, there is much to learn from the structure of the Medicaid incentives program.

The HITECH statute sets forth a “net” average allowable cost for purchasing and implementing an EHR at $25,000 for the first year and $10,000 for subsequent years. Of this “net” allowable cost, the Secretary of HHS is authorized to pay Medicaid Eligible Providers up to 85% in stimulus incentives for a total of 6 years. It appears that the Government is about to pay you 85% of your EHR costs for the next 6 years, which is a pretty good deal. Looks, however, can be deceiving. As any early adopter of EHR knows, the total cost of ownership for an EHR over 6 years is well over the “net” allowable of $75,000 set forth in the HITECH Act, and Congress knew that too. This is why the statute instructs the Secretary of HHS to determine the actual average allowable costs of EHR:

“(C) For the purposes of determining average allowable costs under this subsection, the Secretary shall study the average costs to Medicaid providers described in paragraph (2)(A) of purchase and initial implementation and upgrade of certified EHR technology described in paragraph (3)(C)(i) and the average costs to such providers of operations, maintenance, and use of such technology described in paragraph (3)(C)(ii). In determining such costs for such providers, the Secretary may utilize studies of such amounts submitted by States.”

The Secretary indeed researched and studied the actual costs of EHR adoption and, in the CMS final rule, came up with an average allowable cost for purchasing and implementing an EHR of $54,000 for the first year and $20,610 for subsequent years, putting the average cost of ownership for 6 years at $136,440 per Eligible Provider. This is closer to reality, although some would question if the Secretary brought into account loss of productivity while calculating these numbers. At this point, confusion sets in for most folks. If Congress already decided that they would pay no more than 85% of $75,000, why is the Secretary calculating the actual costs and showing us how inadequate the incentive payments really are? The answer lies in the little word “net”.

In the unlikely event that somebody, presumably the tooth fairy, gives you some money to buy an EHR, that amount of money must be deducted from the $54,000 for the first year, and your incentive amount is calculated as 85% of the remainder: First year incentive = ($54,000 – Cash gift for EHR)*85% -or- First year incentive = $25,000*85%, whichever one is smaller. The same logic applies to subsequent years. The only question now is what constitutes a cash gift for EHR technology. Well, the CMS final rule is pretty clear on that. First, State and local government contributions do not count. General grants for improvements do not count either. If you are employed by a Federally Qualified Health Center (FQHC) or Rural Health Clinic (RHC) or anybody else, and your employer purchases an EHR for you, that doesn’t count as a cash gift for EHR, and neither do any in-kind donations from vendors or other entities. Basically, unless someone not mentioned above hands you a wad of dollar bills wrapped in a note stating “This cash is exclusively for your EHR, doctor”, and that wad of dollar bills is greater than $29,000, your stimulus incentive will not be reduced.

You do have to show CMS that you paid for at least 15% of the "net" allowable EHR cost with your own money ($3,750 in the first year and $1,500 in subsequent years), but here is the beauty of the final rule: all those contributions from State, local governments, employers and in-kind donors, which did not count for calculating your “net” allowable cost, can be used to augment, and entirely substitute for, your out of pocket 15%. This is one of the most magnificent examples of bureaucracy at its very best, since when all rules and exclusions are counted, it seems that practically everybody will be eligible for the maximum incentive of $21,250 in the first year and $8,500 in subsequent years. It is worth noting that these amounts don’t cover even half of the Secretary’s estimated average EHR adoption costs.

How about Eligible Providers who are salaried employees, either in a cost-based FQHC or RHC, or any other fee-for-service entity? Most of these doctors assume that they have to assign their incentive payments to their employer, who provided them with the EHR. The CMS final rule clarifies that you can voluntarily assign your incentives to your employer, but you most certainly do not have to do so.

“We believe that, in accordance with 1903(t)(6)(A) of the Act, an EP could reassign payment to a TIN associated with his or her employer or the facility in which she or he works. …  Any reassignment of payment must be voluntary and we believe the decision as to whether an EP does reassign incentive payments to a specific TIN is an issue which EPs and these other parties should resolve.”

Reassignment of incentives to an employer, or any other entity promoting EHR technologies, is left to the physician and his/her employer. There are multiple strong warnings throughout the CMS final rule that such reassignment must be voluntary and the “States must guarantee that the assignment is voluntary”. For anybody contemplating creative arrangements that will reduce payments to employed physicians, in an FQHC for example, to compensate for EHR expenditures, CMS clarifies that “Incentive payments are payments designed to promote the adoption and meaningful use of certified EHR technology and are not payments for medical assistance provided in the FQHC. We do not have the authority under this program to provide that these funds be the basis for the State to reduce its per visit payment to the FQHC.”

In summary, if you are a Medicaid Eligible Provider in private practice, you can expect $63,750 from Medicaid over the next 6 years. If you are an employed Medicaid Eligible Provider, you should clarify with your employer what the expectations are. There is probably nothing regarding incentives in your contract, and while you could allow your employer to collect your incentives, nothing in the CMS final rule mandates that you do so, and quite the opposite is true. You may want to consider that an EHR will most likely reduce your productivity initially, and perhaps for longer than you expect. If you are practicing within a cost-based facility, your income will be adversely affected by the EHR adoption process, and it may make perfect sense to retain your incentive payments as partial compensation for loss of income, even if your employer paid for your EHR.

The Government EHR

No, you didn’t miss anything, there is no Government EHR. But should there be one? And if so, what should it look like?

The argument in favor of a Government EHR goes something like this: If we have 19 Billion dollars to spend on EHR adoption, why not spend a small fraction of that money and buy or build an EHR and make it freely available to all physicians and hospitals? Not a bad idea. I would add that, if we must, we could spend the rest of those billions on training and supporting physicians in their efforts to computerize their records. So how would a Government go about accomplishing such monumental task?

The first option would be a “fixer upper”. Buy something like Epic, which has both an inpatient and an outpatient EHR, hire a team of software developers and hordes of usability and medical informatics experts and set them down to work on the existing product. A slightly less expensive option, which is frequently mentioned, is to use VistA instead of Epic. After all the Government already spent boatloads of money on VistA and many of its users seem satisfied with the product even in its current state. Epic has many satisfied customers as well. Either way, it shouldn’t take more than a couple of years to have a fairly usable product, migrated to new technologies, scaled down for small hospitals and practices and scaled down even more for patients.

The second option is similar to the process by which the Pentagon acquires new fighter jets. HHS would publish a set of requirements and various vendors would create a prototype and bid for the contract. For an EHR, one would expect the likes of Microsoft, IBM, Apple or Google to lead the pack. For this scenario the Government would be free to specify requirements to facilitate all the data collection the Government may need, and probably base the entire project on a Federal Cloud with Internet access either through a downloadable smart client (e.g. TweetDeck) or plain browser (e.g. twitter.com), or both, as circumstances dictate. We should have something to look at in three years or so and could begin rolling it out in earnest in four.

Either option will overcome most impediments to achieving an EHR for every American. A Federal Cloud containing all medical records will obviate the need of reporting to CMS or any other government agency. A true multi-tenant Federal Cloud will be able to uniquely identify each patient, with a very high level of confidence, and automatically create a National Patient Identifier without all the legislative and bureaucratic hassle. Since all data is managed by one entity, assembling a longitudinal, complete record for each one of us, either persistent or on-demand, will become almost trivial. One database schema, one terminology and a unified user interface would practically guarantee abundant and high quality data points for clinical research. Privacy and security policies, all residing in one place, could be driven by the patient, or consumer, through their own longitudinal, comprehensive view of the medical record. There will be no need for intermediaries and push/pull addressing systems with all the associated complexity. Every doctor, clinician, hospital, insurer, researcher and consumer will be accessing the same data, through the same software, within the scope of various privacy & security policies. And it will all be free.

For all those pulling “1984” out and looking to see if medical records are mentioned there, relax, this utopian EHR is not on the Government agenda at this time. There are as many obstacles to building the Federal Cloud EHR as there are to providing a “Public Option” for health insurance and neither one is politically feasible at this time. There is a large and rather influential Health Information Technology industry which will be summarily killed off by a Government EHR initiative. The need for instant gratification and the greater need for political campaigning material preclude anything with a longer than four years time horizon. Americans have a historical aversion to centralized control and would much rather have multiple smaller corporations control smaller chunks of activities and information, regardless of the administrative costs and pitfalls of such approach.

And then, of course, there is the freedom of choice issue. What if I don’t like the Government EHR? What if I want to build my own, or buy one that suits me better? And what comes next, a Government Automobile? And the right to privacy of both consumers and providers is not far behind. Why should the Government have access to every minute detail of my business? What would lawyers do if the Government would require that all their dossiers be uploaded to a Federal Cloud? What do the Constitution and Bill of Rights have to say about such practice? Certainly this is not what our founding fathers had in mind.

Of all the billions of dollars available for EHR adoption, the Government is timidly allocating $60 million to EHR research activities in areas such as security, usability, clinical terminology and some peculiar concept of making EHRs more like iPhones. I have very little hope of anything tangible materializing from any of these research programs anytime soon. In the meantime, tax payers, physicians and various providers of health care services, are spending billions of dollars on “fixing”, deploying and interconnecting fragmented software systems perfectly matching our equally fragmented insurance and health care delivery system. With enough duct tape, strings and wires, we should be able to pull something together.  We’ll fix the rest later….

One Day in the Life of a Meaningful User

All the laws have been passed and all the final rulings have been published. In the spirit of the times, you went out and got yourself an EHR. You did your due diligence and sat through many hours of vendor demonstrations. In the end they all started to blend together, so you talked to friends and colleagues and accepted the Hospital’s offer to pay a big chunk of your EHR costs if you picked the one they wanted you to pick.
Your biller quit in disgust, but other than that the implementation was uneventful and the Hospital folks helped a lot. After several hiccups, your Medicare payments are coming in regularly now and your office is adjusting well to the new software. The documentation templates leave a lot to be desired, but you type well and when you find some free time you may take a stab at customizing them a bit. Here and there you run into bugs and a couple of times the EHR was unavailable for a good two to three hours. Not sure exactly why. Maybe it was the Internet that was unavailable.
Anyway, if all goes according to plan, you will be retiring in 10 years and your much younger partner will be bringing in someone who is probably in Medical School right now. Everything seems under control. But today is different...

Today is January 2nd, 2011 and you are driving to work. Today has to be meaningfully different and your first patient is waiting in Exam Room 1.

Mrs. Kline is a pleasant 68 year old woman, who has been seeing you for ten years or so, for her hypertension (which is well managed), hyperlipidemia and a touch of arthritis. You bring up her chart on your EHR and begin your meaningful use (§ 495.6(d)(7)(i) – Record Demographics - Check). There is a little red sign on the screen saying that Mrs. Kline is overdue for a routine mammogram (§ 495.6(d)(11)(i) – Clinical Decision Support - Check). She says that she got a little postcard from your office the other day (§ 495.6(e)(4)(i) – Patient Reminders - Check) and will be making an appointment soon. You look at the BP recorded by the nurse and also notice that Mrs. Kline gained some weight and her BMI is now well over 30 (§ 495.6(d)(8)(i) – Record Vitals and BMI - Check). You chuckle as you notice that the nurse duly noted that Mrs. Kline does not smoke (§ 495.6(d)(9)(i) – Record Smoking Status - Check). As you listen to Mrs. Kline’s account of her knees “acting up” again and how it is now painful to walk Fluffy in the morning, you glance at her problem list (§ 495.6(d)(3)(i) – Maintain Problem List - Check) and medications (§ 495.6(d)(5)(i) – Maintain Med List - Check). She also mentioned some shortness of breath when walking Fluffy and you proceed to do an examination.

As you look over Mrs. Kline’s slightly swollen knees and check her wrists and elbows too, she tells you about her daughter Ellie and how she is now a third year Dermatology resident. Mrs. Kline is hesitantly wondering if her daughter could peek at her medical records once in a while. Sounds reasonable and you tell her to ask Mary at the front desk to set her up with access to the portal (§ 495.6(d)(12)(i) – Electronic Copy of Medical Records - Check). You explain to her that all her records are on the computer now and even today’s visit summary will be there before she gets home (§ 495.6(d)(13)(i) – Provide Visit Summaries - Check) and (§ 495.6(e)(5)(i) – Timely Access to Medical Records - Check). Her daughter in faraway California should be well informed from now on.

The exam was non eventful and the Lipid panel Mrs. Kline had last week looks good (§ 495.6(e)(2)(i) – Incorporate Lab Results - Check). You proceed to write a new prescription for Celebrex (§ 495.6(d)(1)(i) – CPOE for Meds - Check) and note that she is not allergic to anything (§ 495.6(d)(6)(i) – Maintain Allergy List - Check). The obligatory DDI pops up and you dismiss it as duly noted (§ 495.6(d)(2)(i) – Drug-Drug Interaction - Check). You adjust the BP meds and note that everything is on formulary (§ 495.6(e)(1)(i) – Formulary Check - Check). You ask Mrs. Klein which pharmacy she is using and promptly send all her scripts there (§ 495.6(d)(4)(i) – Electronic Prescribing - Check).  On your way out you talk to Mrs. Kline about the need to monitor her blood pressure carefully now that she is on new meds and to call you if anything changes before her next appointment. You say good bye and good luck to her daughter. Mrs. Kline stops by the front desk and Mary sets her up with a portal account, makes an appointment for her and hands her the BP home monitoring education materials you ordered (§ 495.6(e)(6)(i) – Patient Education Materials - Check).  Your next patient is in Exam Room 2.

As you walk over to your office, Mary mentions that the IT guy will be coming in later today to fill out some security survey (§ 495.6(d)(15)(i) – Protect Electronic Health Records - Check) and test the export function one more time (§ 495.6(d)(14)(i) – Capability to Exchange Clinical Data - Check) and he is certain that it will work this time. There is a new patient in the freshly cleaned Exam Room 1.

It’s after five o’clock and light snow is falling outside. You saw 20 patients today; some with chronic conditions, some very ill (one had to be admitted) and others with incidental scrapes and viruses, but pretty healthy otherwise. There was nothing unusual about today. On your way home you briefly consider that at this rate you should have plenty of data to report to CMS in 3 months (§ 495.6(d)(10)(i) – Report Quality Measures to CMS - Check) and Mary with the IT guy should figure out the rest when the time comes. That Christmas bonus was well deserved.

This was just one of the 3,653 days until your retirement. The extra three are for leap years.
Congratulations, you are now a Meaningful User of EHR technology.

All quoted section numbers are from the CMS Fina Rule on Meaningful Use

What’s in an EHR?

One of the most promising uses of Electronic Health Records (EHR) is Research. As EHRs become more and more widespread and the clinical data previously held in silos of paper charts becomes fluid, exchangeable and duly collected, large clinical repositories should emerge and be made available to those engaged in research, presumably medical research. The results of such research are expected to help us identify cost effective therapies, health care trends and a myriad other quality improving, cost reducing strategies. With such lofty goals in mind, it may be beneficial to look at the actual contents of an EHR as they are today and as they may be tomorrow.

The clinical data captured in many of today’s EHRs, and in all future EHRs, contains a very rich structured and codified data set.

• Diagnoses complete with dates of onset and resolution (if any) and characteristics such as improving or worsening over time
• Medications and Allergies, including all historical changes and adjustments
• Procedures and Immunizations, including diagnostic procedures, surgeries and treatments, all with dates and some with outcomes
• Hospitalizations, ED and Office Visit dates and durations
• Diagnostic Tests and Screenings, including labs, radiology, cognitive screenings, genetic screenings, etc. all with results and dates of service.
• Complete vitals over time, such as height, weight, blood pressure, etc.
• Family Histories of disease and outcomes all the way to aunts, uncles, cousins, nephews and nieces

On top of the clinical data, EHRs also contain demographics and socio-economic data sets.

• Names, addresses, emails, phone numbers for patients and sometimes family members if appropriate
• History of insurance coverage over time with effective coverage dates
• Pharmacies and testing facilities used in the past
• Ethnicity, preferred language, level of education, occupation and employment history
• Academic performance, preferred areas of study, schools and camps attended
• Safety measures in the home (fire safety) and on the road (seatbelts, helmets)
• Family circumstances, including number of children, miscarriages, sexual orientation, habits and abusive or predatory history
• Travel, hobbies, diet, exercise, alcohol, coffee and tobacco consumption over time
• Very limited financial information, such as credit card numbers, bill paying promptness and necessity of payment plans or discounts

By all accounts, this is an exceedingly rich data set and should facilitate almost any type of research one can dream of. We could examine the effects of various therapies on disease progression and estimate cost effectiveness and various correlations with socio-economic circumstance. We could study disparities. We could assess quality of outcomes, sliced and diced by region and institution type. The sky seems to be the limit, or is it?

As anyone engaged in research knows, data points are only one side of the story. Data quality is another. The most publicized assault on the contents stored in our EHRs came over a year ago from the, now very famous, e-patient Dave who attempted to download his medical records from a hospital into his Google Personal Health Record (PHR), only to discover that his EHR was laden with inaccuracies. There were diseases he never had, missing dates, missing meds and tests results, visits that never occurred and all that from one of the most advanced hospital EHR systems in existence. If you look at smaller hospitals and ambulatory practices, you will find that some medical records are electronic but some portions of care are still documented on paper. Patients sometimes ask their doctors to not document certain things and, given the option, some choose to “hide” sensitive information. Physicians sometimes dispense sample medications or call in a script and make only a cursory note in the EHR, or advice patients to see a specialist with no particular follow up documentation. Clerical errors are a given. The possibilities of incomplete, corrupt and misleading, data sets are endless. If that’s not enough, EHRs barely communicate with each other and creating an accurate picture of the continuum of care for any given patient shuttled from doctor(s) to hospital(s) to specialist(s) is nearly impossible.

One solution suggested by so called e-patients is the self-maintained PHR. Patients who want their “damn data” in a computable format seem to think that they could clean it up and make it usable for all sorts of innovative applications. The question here is of course whether the average patient has enough knowledge and enough information to correct the data set and accurately supplement it. For personal use, it is plausible to assume that some of us would be motivated enough and capable enough to create a decent longitudinal medical record in a PHR. For clinical research purposes, such PHR edited data sets would not pass muster any more than the deficient and erroneous original EHR data sets would.

The inescapable conclusion is that, currently, EHR data is ill suited to  the customary rigor of clinical research, and has very little to offer above and beyond claim data which is already in use for general studies on broad trends, such as the famed Dartmouth Atlas Medicare expenditures studies. Looking ahead, it is feasible to assume that data quality will be improving and as paper is phased out and EHRs become more robust, user friendly and widespread, and as privacy and security issues are resolved, we may indeed end up with the proverbial mountain of pure gold for equally pure clinical research.
With lots of patience, determination and proper stewardship, the long term societal rewards from Electronic Health Records are very clear. Right now, we just need to do the right thing and we all, physicians, patients, entrepreneurs, government regulators, know exactly what the right thing is.