Tech

Tech

Paging Dr. Google

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For the record: I am a geek. I love technology. I adopted EMR when all the cool kids were using paper. Instead of loitering in the “in” doctors lounge making eyes at the nurses, I was writing clinical content and making my care more efficient. I was getting “meaningful use” out of my EMR even when nobody paid me to do it.

But now who’s laughing? While they are slaving away trying to get their “meaningful use” checks, I’ve moved on to greener pastures, laughing at their sorry butts! It’s just like my mom promised it would be. Thanks mom.

Really, for the record, I am not so much a technology fan as a “systems” guy. I like finding the right tool for the job, building systems that make it easier to do what I want, and technology is perfect for that job. I am not so much a fan of technology, but what technology can do. Technology is not the goal, it is the best tool to reach many of my goals. There are two things that measure the effectiveness of a tool:

1. Is the tool the right one for the job?
2. Is the person using the tool properly?

So, when answering the question I posed at the end of my last post, what constitutes a “good” EMR, I have to use these criteria.

What Apple Can Teach Health Care About Thinking Different

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Apple Incorporated has grown to be among the most valuable and most envied companies on earth. Its products are ubiquitous and beloved by many of their users. Last year, the firm generated nearly $26 billion in profits on revenues of $108 billion. When physicians and others working in health care discuss the lessons that the medical establishment can learn from these types of corporate successes, the conversations almost always revolve around the promise of information technologies, such as electronic record keeping or electronic prescription writing, and the need for increased use of these in medical practice. While these technologies are important, the most valuable lesson from Apple’s success is a demonstration of the power of empathy and the subsequent need for health care providers to emotional connect with our patients.

It is widely known that Steve Jobs and Steve Wozniak built the first Apple computer in Steve Jobs’ garage; what is not as widely known is that they quickly brought in a third partner, Mike Markkula, to join and guide the company. He began by writing a one page statement entitled “The Apple Marketing Philosophy”. This philosophy stressed only three key components of bedrock company principles; the first and most important was empathy.

The Health IT Scandal the NY Times Didn’t Cover

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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.

Zen and the Art of Charting

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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.

The HIT Job

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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.”

Death of an Evangelist

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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.

Data Mining Systems Improve Cost and Quality of Healthcare – Or Do They?

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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 [1].

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.

Is Interoperability Possible in HIT? And if it Is, Do We Even Want it?

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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.

“Social Documentation” for Healthcare

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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.

The “Post EHR” Era

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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.