In case you missed it, the shocking news was that health IT companies that stood to profit from billions of dollars in federal subsidies to potential customers poured in – well, actually, poured in not that much money at all when you think about it – lobbying for passage of the HITECH Act in 2009. This, putatively, explains why electronic health records (EHRs) have thus far failed to dramatically improve quality and lower cost, with a secondary explanation from athenahealth CEO Jonathan Bush that everything would be much better if the HITECH rules had been written by Jonathan Bush of athenahealth.
Next up: corporate lobbying for passage of the 1862 Pacific Railroad Bill is blamed for Amtrak’s dismal on-time record in 2013.
The actual scandal is more complicated and scary. It has to do with the adamant refusal by hospitals and doctors to adopt electronic records no matter what the evidence. Way back in 1971, for example, when Intel was a mere fledgling and Microsoft and Apple weren’t even gleams in their founders’ eyes, a study in a high-profile medical journal found that doctors missed up to 35 percent of the data in a paper chart. Thirty-seven years later, when Intel, Microsoft and Apple were all corporate giants, a study in the same journal of severely ill coronary syndrome patients found virtually the same problem: “essential” elements to quality care missing in the paper record.
One of the many challenges I face in my clinical work is keeping track of a patient’s multiple health issues, and staying on top of the plan for each issue.
As you might imagine, if I’m having trouble with this, then the patients and families probably are as well.
After all, I don’t just mean keeping up with the multiple recommendations that we clinicians easily generate during an encounter with an older patient.
I mean ensuring that we all keep up with *everything* on the medical problem list, so that symptoms are adequately managed, chronic diseases get followed up on correctly, appropriate preventive care is provided, and we close the loop on previous concerns raised.
This, I have found, is not so easy to do. In fact, I would say that the current norm is for health issues to frequently fall between the cracks, with only a small minority of PCPs able to consistently keep up with all health issues affecting a medically complex adult.
I’m well aware that a good fraction of the people in this country – let’s call them Rush fans – spend their lives furious at the New York Times. I am not one of them. I love the Grey Lady; it would be high on my list of things to bring to a desert island. But every now and then, the paper screws up, and it did so in a big way in its recent piece on the federal program to promote healthcare information technology (HIT).
Let’s stipulate that the Federal government’s $20 billion incentive program (called “HITECH”), designed to drive the adoption of electronic health records, is not perfect. Medicare’s “Meaningful Use” rules – the standards that hospitals’ and clinics’ EHRs must meet to qualify for bonus payments – have been criticized as both too soft and too restrictive. (You know the rules are probably about right when the critiques come from both directions.) Interoperability remains a Holy Grail. And everybody appreciates that today’s healthcare information technology (HIT) systems remain clunky and relatively user-unfriendly. Even Epic, the Golden Child among electronic medical record systems, has been characterized as the “Cream of the Crap.”
It feels like part of me is dying. I am losing something that has been a part of me for nearly 20 years.
I bought in to the idea of electronic records in the early 90′s and was enthusiastic enough to implement in my practice in 1996. My initial motivation was selfish: I am not an organized person by nature (distractible, in case you forgot), and computers do much of the heavy lifting in organization. I saw electronics as an excellent organization system for documents. Templates could make documentation quicker and I could keep better track of labs and x-rays. I could give better care, and that was a good enough reason to use it.
But the EMR product we bought, as it came out of the box, was sorely lacking. Instead of making it easier to document I had to use templates generated by someone else – someone who obviously was not a physician (engineers, I later discovered). So we made a compromise: since it was easier to format printed data, we took that data and made a printed template.
Several email lists I am on were abuzz last week about the publication of a paper that was described in a press release from Indiana University to demonstrate that “machine learning — the same computer science discipline that helped create voice recognition systems, self-driving cars and credit card fraud detection systems — can drastically improve both the cost and quality of health care in the United States.” The press release referred to a study published by an Indiana faculty member in the journal, Artificial Intelligence in Medicine .
While I am a proponent of computer applications that aim to improve the quality and cost of healthcare, I also believe we must be careful about the claims being made for them, especially those derived from results from scientific research.
After reading and analyzing the paper, I am skeptical of the claims made not only by the press release but also by the authors themselves. My concern is less about their research methods, although I have some serious qualms about them I will describe below, but more so with the press release that was issued by their university public relations office. Furthermore, as always seems to happen when technology is hyped, the press release was picked up and echoed across the Internet, followed by the inevitable conflation of its findings. Sure enough, one high-profile blogger wrote, “physicians who used an AI framework to make patient care decisions had patient outcomes that were 50 percent better than physicians who did not use AI.” It is clear from the paper that physicians did not actually use such a framework, which was only applied retrospectively to clinical data.
What exactly did the study show? Basically, the researchers obtained a small data set for one clinical condition in one institution’s electronic health record and applied some complex data mining techniques to show that lower cost and better outcomes could be achieved by following the options suggested by the machine learning algorithm instead of what the clinicians actually did. The claim, therefore, is that if the data mining were followed by the clinicians instead of their own decision-making, then better and cheaper care would ensue.
Anyone who understands the importance of continuity of care knows that health information exchange is essential. How are we supposed to cut waste and duplication from the healthcare system and truly focus on patient welfare if doctor B has no idea what tests doctor A conducted, or what the results were?
The predominant proprietary HIT vendors know this, yet have engaged in prolonged foot-dragging on interoperability and even basic data interfacing. Yes healthcare IT is their business, but interoperability is not in their nature.
As we’ve seen before, the problem is with the business model.
The proprietary business model makes the vendor the single source of HIT for hospital clients. Complexity and dependence are baked into both solutions and client relationships, creating a “vendor lock” scenario in which changing systems seems almost inconceivable.
In the proprietary world, interfacing with third-party products is a revenue generation strategy and technical challenge; the latter, though unnecessary, justifies the former. When we go looking for the reasons that healthcare is a laggard compared with other industries, this single-source model—the obstacle to much-needed competition and innovation—is a primary culprit.
To be fair, provider organizations, with little if any incentive to exchange patient data before the advent of Meaningful Use, haven’t shown much collaborative spirit either. In the fee-for-service model, why would a healthcare organization let patients slip from their grasp? Health reform is finally mandating needed change, but when will proprietary vendors actually enable the interoperability hospitals and practices soon have to demonstrate?
Recent rumblings from Washington, DC, suggest the feds are losing patience.
Every day CIOs are inundated with buzzword-compliant products – BYOD, Cloud, Instant Messaging, Software as a Service, and Social Networking.
In yesterday’s blog post, I suggested that we are about to enter the “post EHR” era in which the management of data gathered via EHRs will become more important than the clinical-facing functions within EHRs.
Today, I’ll add that we do need to a better job gathering data inside EHRs while at the same time reducing the burden on individual clinicians.
I suggest that BYOD, Cloud, Instant Messaging, Software as a Service and Social Networking can be combined to create “Social Documentation” for Healthcare.
In previous blogs, I’ve developed the core concepts of improving the structured and unstructured documentation we create in ambulatory and inpatient environments.
I define “social documentation” as team authored care plans, annotated event descriptions (ranging from acknowledging a test result to writing about the patient’s treatment progress), and process documentation (orders, alerts/reminders) sufficient to support care coordination, compliance/regulatory requirements, and billing.
Over the next few months, the majority of my time will be spent discussing topics such as care coordination, healthcare information exchange, care management, real time analytics, and population health. At BIDMC, we’ve already achieved 100% EHR adoption and 90% Meaningful Use attestation among our clinician community. Now that the foundation is laid, I believe our next body of work is to craft the technology and workflow solutions which will be hallmarks of the “post EHR” era.
What does this mean?
I’ve written previously about BIDMC’s Accountable Care Organization strategy, which can be summed up as ACO=HIE + analytics.
In a “post EHR” era we need to go beyond simple data capture and reporting, we need care management that ensures patients with specific diseases follow standardized guidelines and protocols, escalating deviations to the care team. That team will include PCPs, specialists, home care, long term care, and family members. The goal of a Care Management Medical Record (CMMR) will be to provide a dashboard that overlays hospital and professional data with a higher level of management.
How could this work?
Imagine that we define each patient’s healthcare status in terms of “properties”. Data elements might include activities of daily living, functional status, current care plans, care preferences, diagnostic test results, and therapies, populated from many sources of data including every EHR containing patient data, hospital discharge data, and consumer generated data from PHRs/home health devices.
That data will be used in conjunction with rules that generate alerts and reminders to care managers and other members of the care team (plus the patient). The result is a Care Management Medical Record system based on a foundation of EHRs that provides much more than any one EHR.
My challenge in 2013-2014 will be to build and buy components that turn multiple EHRs into a CMMR at the community level.
Our ancestors began using tools millions of years ago and humanity assumed control of the planet it lives on through a succession of tools ranging from sticks and stones all the way to iPhones and drones. The basic process for discovering or inventing tools hasn’t changed much over the millennia, and it follows two basic patterns. Either an existing artifact is examined for fitness to various purposes until one such purpose is discovered accidentally or through organized efforts, or a problem is identified and a tool is then invented, or located, to solve the problem.
The problem itself could be something that was thought impossible before, such as flying, or a more mundane desire to reduce the effort and expand the capabilities associated with an existing activity, such as moving goods from one place to another. Tools can have limited effects, revolutionize an entire economic sector or can change history, and some tools can have harmful effects that must be balanced with the benefits they offer for the intended task. Tools usually undergo long processes of change, improvement and expansion, and sometimes the evolving tool looks nothing like the original invention. Why are we talking about tools here? Because programmable computers are tools. The computer hardware is like the hammer head and the programming software is like the hammer’s handle (more or less). And EMRs are one such handle.
Let’s imagine that we are software builders and we have a desire to help doctors deliver patient care. And let’s further assume that we, and our prospective customers, examined all the existing tools out there and found them not quite fit for purpose. Let’s also assume that we are not suffering from delusions of grandeur, have the humility to admit that we don’t know how to cure disease and have no interest in global social engineering initiatives. Let’s imagine that we are the misguided founders of a small social business interested in doing well by helping others do good things.
In November 2012, the digital team at HealthEd embarked on a challenge to redesign the face of personal health records. That effort has been rewarded with a first-place win in the category of Best Lab Summaries. And another HealthEd entry was cited as a finalist that “inspired the judges and challenged the status quo.”
About the Health Design Challenge
The Office of the National Coordinator of Health Information Technology and the Department of Veterans Affairs issued a challenge to designers throughout the United States: imagine how personal health records could be improved for clarity, readability, and visual appeal. Given HealthEd’s mission to create better outcomes in personal wellness, the team embraced the Health Design Challenge with typical enthusiasm.
The Health Design Challenge was more than an exercise in graphic design, however. Entrants were required to demonstrate expert knowledge of clinical systems and to render information of relevance for both millennials and senior citizens. The judges wanted more than pretty pictures—participants had to know their stuff.Continue reading…