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Monday, October 27, 2014

An Epic battle: Did the EHR kill Dallas Ebola patient zero? On the double-edged sword of Health IT

Obviously, no. Ebola killed the patient. But, to what extent did inadequate process and technology factors contribute to patient zero's demise? Might a timely, accurate dx helped save his life (and reduce or eliminate his disease vector contact spread risk)? We'll never know. His survival odds were perhaps dicey in the best of circumstances -- but, surely better than they'd have been had he still been in Africa, assuming an accurate initial diagnosis at the ER when he first presented.

Emotions continue to run high in the wake of the increasing number of active Ebola patients reaching U.S. shores and hospitals. Politicians push each other aside vying for media face time. Camera-hugging congressional inquisitions ensue. Calls for travel bans and quarantines continue to dominate above the fold. On the Who-Left-The-Lid-Off-The-Jar-of-Stupid? side of things, twitter hashtags such as #Obola arise, spread, and mutate faster than any airborne or bodily fluids-borne pathogen ever could.

The nurses push back angrily (Not one mention of Epic, interestingly).

In the immediate aftermath of the the Dallas Duncan dx debacle, sharp-elbowed HIT critics wasted no time assigning blame. The ever-strident patient privacy rights advocate Deborah C. Peel, MD posted a LinkedIn piece under a inflammatory click-bait headline "Why did Mr. Duncan have to die for the US to face flaws in EHRs?"

Nothwithstanding that [1] she's a psychiatrist, not an ER doc, [2] wasn't there in the Dallas ER, and [3] is not an Epic user.

It has been quite fashionable in QI circles for some time now to cluck progressively "fix the process, not the blame." Nonetheless, we still tend to reflexively reach for the culpability laser guns when hyperemotionally-charged incidents occur. The mainstream health IT blog comments sections these days are overrun with indignant "we-told-you-so" anti-EHR sentiment.

A paper has just emerged.
Divvy K. Upadhyay, Dean F. Sittig and Hardeep Singh*
Ebola US Patient Zero: lessons on misdiagnosis and effective use of electronic health records
Abstract: On September 30th, 2014, the Centers for Disease Control and Prevention (CDC) confirmed the first travel-associated case of US Ebola in Dallas, TX. This case exposed two of the greatest concerns in patient safety in the US outpatient health care system: misdiagnosis and ineffective use of electronic health records (EHRs). The case received widespread media attention highlighting failures in disaster management, infectious disease control, national security, and emergency department (ED) care. In addition, an error in making a correct and timely Ebola diagnosis on initial ED presentation brought diagnostic decision-making vulnerabilities in the EHR era into the public eye. In this paper, we use this defining “teachable moment” to highlight the public health challenge of diagnostic errors and discuss the effective use of EHRs in the diagnostic process. We analyze the case to discuss several missed opportunities and outline key challenges and opportunities facing diagnostic decision-making in EHR-enabled health care. It is important to recognize the reality that EHRs suffer from major usability and interoperability issues, but also to acknowledge that they are only tools and not a replacement for basic history-taking, examination skills, and critical thinking. While physicians and health care organizations ultimately need to own the responsibility for addressing diagnostic errors, several national-level initiatives can help, including working with software developers to improve EHR usability. Multifaceted approaches that account for both technical and non-technical factors will be needed. Ebola US Patient Zero reminds us that in certain cases, a single misdiagnosis can have widespread and costly implications for public health.
My highlighted review copy of the full paper here (pdf). More:
...[T]he available evidence suggests that the physician did not obtain or appreciate the travel history during the patient encounter and did not consider the possibility of Ebola infection.
Assigning blame to the EHR is not new and often reflects a reluctance to address the complex cognitive and/or performance issues involving front-line staff, especially those related to responsibility and accountability. It is important that we recognize the reality that EHRs suffer from major usability and interoperability issues, but also to acknowledge that they are only tools and not a replacement for basic history-taking, examination skills, and critical thinking.
Several other ‘human factor’ issues may have contributed to the diagnostic error in this case. A host of system-related factors detract from optimal conditions for critical thinking in the ED, leading clinicians to lose situational awareness. These include production pressures, distractions, and inefficient processes. Also, physicians tend to ignore nursing notes, whether on paper or in the EHR. Many organizations modify their EHR-related workflows to ensure that specific data elements required for quality measures (none of which focus on diagnostic quality) are reliably captured...
This paper, while necessarily speculative to a degree, is worth our time; well-done and balanced, pointing up a number of "fix-the-process" recommendations we do well to heed.

A good time at this point to return to Nicholas Carr's fine, (must-read, IMO) book "The Glass Cage" (which I first cited on October 22nd).

Some good HIT history, and thoughts on where we now stand:
LATE IN THE SUMMER OF 2005, researchers at the venerable RAND Corporation in California made a stirring prediction about the future of American medicine. Having completed what they called “the most detailed analysis ever conducted of the potential benefits of electronic medical records,” they declared that the U.S. health-care system “could save more than $81 billion annually and improve the quality of care” if hospitals and physicians automated their record keeping. The savings and other benefits, which RAND had estimated “using computer simulation models,” made it clear, one of the think tank’s top scientists said, “that it is time for the government and others who pay for health care to aggressively promote health information technology.” The last sentence in a subsequent report detailing the research underscored the sense of urgency: “The time to act is now.”

When the RAND study appeared, excitement about the computerization of medicine was already running high. Early in 2004, George W. Bush had issued a presidential order establishing the Health Information Technology Adoption Initiative with the goal of digitizing most U.S. medical records within ten years. By the end of 2004, the federal government was handing out millions of dollars in grants to encourage the purchase of automated systems by doctors and hospitals. In June of 2005, the Department of Health and Human Services established a task force of government officials and industry executives, the American Health Information Community, to help spur the adoption of electronic medical records. The RAND research, by putting the anticipated benefits of electronic records into hard and seemingly reliable numbers, stoked both the excitement and the spending...

Shortly after being sworn in as president in 2009, Barack Obama cited the RAND numbers when he announced a program to dole out an additional $30 billion in government funds to subsidize purchases of electronic medical record (EMR) systems. A frenzy of investment ensued, as some three hundred thousand doctors and four thousand hospitals availed themselves of Washington’s largesse.

Then, in 2013, just as Obama was being sworn in for a second term, RAND issued a new and very different report on the prospects for information technology in health care. The exuberance was gone; the tone now was chastened and apologetic. “Although the use of health IT has increased,” the authors of the paper wrote, “quality and efficiency of patient care are only marginally better. Research on the effectiveness of health IT has yielded mixed results. Worse yet, annual aggregate expenditures on health care in the United States have grown from approximately $2 trillion in 2005 to roughly 2.8 trillion today.” Worst of all, the EMR systems that doctors rushed to install with taxpayer money are plagued by problems with “interoperability.” The systems can’t talk to each other, which leaves critical patient data locked up in individual hospitals and doctors’ offices. One of the great promises of health IT has always been that it would, as the RAND authors noted, allow “a patient or provider to access needed health information anywhere at any time,” but because current EMR applications employ proprietary formats and conventions, they simply “enforce brand loyalty to a particular health care system.” While RAND continued to express high hopes for the future, it confessed that the “rosy scenario” in its original report had not panned out.

Other studies back up the latest RAND conclusions. Although EMR systems are becoming common in the United States, and have been common in other countries, such as the United Kingdom and Australia, for years, evidence of their benefits remains elusive. In a broad 2011 review, a team of British public-health researchers examined more than a hundred recently published studies of computerized medical systems. They concluded that when it comes to patient care and safety, there’s “a vast gap between the theoretical and empirically demonstrated benefits.” The research that has been used to promote the adoption of the systems, the scholars found, is “weak and inconsistent,” and there is “insubstantial evidence to support the cost-effectiveness of these technologies.” As for electronic medical records in particular, the investigators reported that the existing research is inconclusive and provides “only anecdotal evidence of the fundamental expected benefits and risks.”

To date, there is no strong empirical support for claims that automating medical record keeping will lead to major reductions in health-care costs or significant improvements in the well-being of patients. But if doctors and patients have seen few benefits from the scramble to automate record keeping, the companies that supply the systems have profited. Cerner Corporation, a medical software outfit, saw its revenues triple, from $1 billion to $3 billion, between 2005 and 2013. Cerner, as it happens, was one of five corporations that provided RAND with funding for the original 2005 study. The other sponsors, which included General Electric and Hewlett Packard, also have substantial business interests in health-care automation. As today’s flawed systems are replaced or upgraded in the future, to fix their interoperability problems and other shortcomings, information technology companies will reap further windfalls.

As bugs are worked out, features refined, and prices cut, even overhyped systems can eventually save companies a lot of money, not least by reducing their need to hire wage-earning workers. (The investments are, of course, far more likely to generate attractive returns when businesses are spending taxpayer money rather than their own.) This historical pattern seems likely to unfold again with EMR applications and related systems. As physicians and hospitals continue to computerize their record keeping and other operations— the generous government subsidies are still flowing—demonstrable efficiency gains may be achieved in some areas, and the quality of care may well improve for some patients, particularly when that care requires the coordinated efforts of several specialists. The fragmentation and cloistering of patient data are real problems in medicine, which well-designed, standardized information systems can help fix.

...More important, the report and its aftermath reveal how deeply the substitution myth is entrenched in the way society perceives and evaluates automation. The RAND researchers assumed that beyond the obvious technical and training challenges in installing the systems, the shift from writing medical reports on paper to composing them with computers would be straightforward. Doctors, nurses, and other caregivers would substitute an automated method for a manual method, but they wouldn’t significantly change how they practice medicine. In fact, studies show that computers can “profoundly alter patient care workflow processes,” as a group of doctors and academics reported in the journal Pediatrics in 2006. “Although the intent of computerization is to improve patient care by making it safer and more efficient, the adverse effects and unintended consequences of workflow disruption may make the situation far worse.”

...Falling victim to the substitution myth, the RAND researchers did not sufficiently account for the possibility that electronic records would have ill effects along with beneficial ones— a problem that plagues many forecasts about the consequences of automation. The overly optimistic analysis led to overly optimistic policy. As the physicians and medical professors Jerome Groopman and Pamela Hartzband noted in a withering critique of the Obama administration’s subsidies, the 2005 RAND report “essentially ignore[ d] downsides to electronic medical records” and also discounted earlier research that failed to find benefits in shifting from paper to digital records. 9 RAND’s assumption that automation would be a substitute for manual work proved false, as human-factors experts would have predicted. But the damage, in wasted taxpayer money and misguided software installations, was done.

...THE INTRODUCTION of automation into medicine, as with its introduction into aviation and other professions, has effects that go beyond efficiency and cost. We’ve already seen how software-generated highlights on mammograms alter, sometimes for better and sometimes for worse, the way radiologists read images. As physicians come to rely on computers to aid them in more facets of their everyday work, the technology is influencing the way they learn, the way they make decisions, and even their bedside manner.

EMR systems are used for more than taking and sharing notes. Most of them incorporate decision-support software that, through on-screen checklists and prompts, provides guidance and suggestions to doctors during the course of consultations and examinations....
A study of primary-care physicians who adopted electronic records, conducted by Timothy Hoff, a professor at SUNY’s University at Albany School of Public Health, reveals evidence of what Hoff terms “deskilling outcomes,” including “decreased clinical knowledge” and “increased stereotyping of patients.” In 2007 and 2008, Hoff interviewed seventy-eight physicians from primary-care practices of various sizes in upstate New York. Three-fourths of the doctors were routinely using EMR systems, and most of them said they feared computerization was leading to less thorough, less personalized care. The physicians using computers told Hoff that they would regularly “cut-and-paste” boilerplate text into their reports on patient visits, whereas when they dictated notes or wrote them by hand they “gave greater consideration to the quality and uniqueness of the information being read into the record.” Indeed, said the doctors, the very process of writing and dictation had served as a kind of “red flag” that forced them to slow down and “consider what they wanted to say.” The doctors complained to Hoff that the homogenized text of electronic records can diminish the richness of their understanding of patients, undercutting their “ability to make informed decisions around diagnosis and treatment.”...

Although flipping through the pages of a traditional medical chart may seem archaic and inefficient these days, it can provide a doctor with a quick but meaningful sense of a patient’s health history, spanning many years. The more rigid way that computers present information actually tends to foreclose the long view. “In the computer,” Ofri writes, “all visits look the same from the outside, so it is impossible to tell which were thorough visits with extensive evaluation and which were only brief visits for medication refills.” Faced with the computer’s relatively inflexible interface, doctors often end up scanning a patient’s records for “only the last two or three visits; everything before that is effectively consigned to the electronic dust heap.”...

...With paper records, doctors could use the “characteristic penmanship” of different specialists to quickly home in on critical information. Electronic records, with their homogenized format, erase such subtle distinctions. Beyond the navigational issues, Ofri worries that the organization of electronic records will alter the way physicians think: “The system encourages fragmented documentation, with different aspects of a patient’s condition secreted in unconnected fields, so it’s much harder to keep a global synthesis of the patient in mind.” The automation of note taking also introduces what Harvard Medical School professor Beth Lown calls a “third party” into the exam room... More than 90 percent of the Israeli doctors interviewed in the study said that electronic record keeping “disturbed communication with their patients.” Such a loss of focus is consistent with what psychologists have learned about how distracting it can be to operate a computer while performing some other task. “Paying attention to the computer and to the patient requires multitasking,” observes Lown, and multitasking “is the opposite of mindful presence.”

...Studies show that primary-care physicians routinely dismiss about nine out of ten of the alerts they receive. That breeds a condition known as alert fatigue. Treating the software as an electronic boy-who-cried-wolf, doctors begin to tune out the alerts altogether. They dismiss them so quickly when they pop up that even the occasional valid warning ends up being ignored. Not only do the alerts intrude on the doctor-patient relationship; they’re served up in a way that can defeat their purpose.

A medical exam or consultation involves an extraordinarily intricate and intimate form of personal communication. It requires, on the doctor’s part, both an empathic sensitivity to words and body language and a coldly rational analysis of evidence. To decipher a complicated medical problem or complaint, a clinician has to listen carefully to a patient’s story while at the same time guiding and filtering that story through established diagnostic frameworks. The The key is to strike the right balance between grasping the specifics of the patient’s situation and inferring general patterns and probabilities derived from reading and experience...
Being led by the screen rather than the patient is particularly perilous for young practitioners, Lown suggests, as it forecloses opportunities to learn the most subtle and human aspects of the art of medicine— the tacit knowledge that can’t be garnered from textbooks or software. It may also, in the long run, hinder doctors from developing the intuition that enables them to respond to emergencies and other unexpected events, when a patient’s fate can be sealed in a matter of minutes. At such moments, doctors can’t be methodical or deliberative; they can’t spend time gathering and analyzing information or working through templates. A computer is of little help. Doctors have to make near-instantaneous decisions about diagnosis and treatment. They have to act. Cognitive scientists who have studied physicians’ thought processes argue that expert clinicians don’t use conscious reasoning, or formal sets of rules, in emergencies. Drawing on their knowledge and experience, they simply “see” what’s wrong— oftentimes making a working diagnosis in a matter of seconds— and proceed to do what needs to be done. “The key cues to a patient’s condition,” explains Jerome Groopman in his book How Doctors Think, “coalesce into a pattern that the physician identifies as a specific disease or condition.” This is talent of a very high order, where, Groopman says, “thinking is inseparable from acting.” Like other forms of mental automaticity, it develops only through continuing practice with direct, immediate feedback. Put a screen between doctor and patient, and you put distance between them. You make it much harder for automaticity and intuition to develop.

Carr, Nicholas (2014-09-29). The Glass Cage: Automation and Us (Kindle Locations 1380-1581). W. W. Norton & Company. Kindle Edition.
I could not recommend this book more highly. His sections on the evolution and current status of avionics technology deployment is particularly relevant to medicine. Commercial pilots have been to a significant degree reduced to the roles of "deskilled" "machine tenders," which works fine -- until it doesn't. And, when it doesn't, scores of people typically die. I know that many doctors bristle at the endless QI comparison to aviation (checklists, loss of physician "autonomy," team-based "Crew Resource Management," etc), but they will find much with which they'll wholeheartedly agree in Carr's book.

I quickly return to another book I've cited previously while ruminating on the insights of Lawrence Weed, MD (the groundbreaking "Medicine in Denial" guy).

Our brains do have the ability to process the information we take in, but at a cost: We can have trouble separating the trivial from the important, and all this information processing makes us tired. Neurons are living cells with a metabolism; they need oxygen and glucose to survive and when they’ve been working hard, we experience fatigue. Every status update you read on Facebook , every tweet or text message you get from a friend, is competing for resources in your brain with important things like whether to put your savings in stocks or bonds, where you left your passport, or how best to reconcile with a close friend you just had an argument with.

The processing capacity of the conscious mind has been estimated at 120 bits per second. That bandwidth, or window, is the speed limit for the traffic of information we can pay conscious attention to at any one time. While a great deal occurs below the threshold of our awareness, and this has an impact on how we feel and what our life is going to be like, in order for something to become encoded as part of your experience, you need to have paid conscious attention to it...
Humans are, by most biological measures, the most successful species our planet has seen. We have managed to survive in nearly every climate our planet has offered (so far), and the rate of our population expansion exceeds that of any other known organism. Ten thousand years ago, humans plus their pets and livestock accounted for about 0.1% of the terrestrial vertebrate biomass inhabiting the earth; we now account for 98%. Our success owes in large part to our cognitive capacity, the ability of our brains to flexibly handle information. But our brains evolved in a much simpler world with far less information coming at us. Today, our attentional filters easily become overwhelmed. Successful people— or people who can afford it— employ layers of people whose job it is to narrow the attentional filter. That is, corporate heads, political leaders, spoiled movie stars, and others whose time and attention are especially valuable have a staff of people around them who are effectively extensions of their own brains, replicating and refining the functions of the prefrontal cortex’s attentional filter...

The human brain has evolved to hide from us those things we are not paying attention to. In other words, we often have a cognitive blind spot: We don’t know what we’re missing because our brain can completely ignore things that are not its priority at the moment— even if they are right in front of our eyes.
Due to the attentional filter, we end up experiencing a great deal of the world on autopilot, not registering the complexities , nuances, and often the beauty of what is right in front of us. A great number of failures of attention occur because we are not using these two principles to our advantage.

A critical point that bears repeating is that attention is a limited-capacity resource— there are definite limits to the number of things we can attend to at once...
Levitin, Daniel J. (2014-08-19). The Organized Mind: Thinking Straight in the Age of Information Overload (pp. 6-11). Penguin Group US. Kindle Edition.
Indeed. Yet another fine read. The implications of cognitive burden, attentional competition, technological automation. Health IT undeniably has much room for improvement to be a consistently integrated process component of astute clinical care.

More Levitin:
What Doctors Offer

...if MDs are so bad at reasoning, how is it that medicine relieves so much suffering and extends so many lives? I have focused on some high-profile cases— prostate cancer, cardiac procedures— where medicine is in a state of flux. And I’ve focused on the kinds of problems that are famously difficult, that exploit cognitive weaknesses. But there are many successes: immunization, treatment of infection, organ transplants, preventive care, and neurosurgery (like Salvatore Iaconesi’s, in Chapter 4), to name just a few. 

The fact is that if you have something wrong with you, you don’t go running to a statistics book, you go to a doctor. Practicing medicine is both an art and a science. Some doctors apply Bayesian inferencing without really knowing they’re doing it. They use their training and powers of observation to engage in pattern matching—knowing when a patient matches a particular pattern of symptoms and risk factors to inform a diagnosis and prognosis.

As Scott Grafton, a top neurologist at UC Santa Barbara, says, “Experience and implicit knowledge really matter. I recently did clinical rounds with two emergency room doctors who had fifty years of clinical experience between them. There was zero verbal gymnastics or formal logic of the kind that Kahneman and Tversky tout. They just recognize a problem. They have gained skill through extreme reinforcement learning, they become exceptional pattern recognition systems. This application of pattern recognition is easy to understand in a radiologist looking at X-rays. But it is also true of any great clinician. They can generate extremely accurate Bayesian probabilities based on years of experience , combined with good use of tests, a physical exam, and a patient history.” A good doctor will have been exposed to thousands of cases that form a rich statistical history (Bayesians call this a prior distribution) on which they can construct a belief around a new patient. A great doctor will apply all of this effortlessly and come to a conclusion that will result in the best treatment for the patient... [ibid, pp. 248-249]
That which interferes with expert clinical judgment needs to be rooted out and kicked to the curb.

I keep returning to the excellent, voluminous  works of Jerome Carter, MD, at his EHR Science blog:
Creating clinical care systems that support clinical work requires not only a huge up-front effort to determine what the system should do and how it should be structured, but it also requires a design that can accommodate change gracefully (or at least as gracefully as possible).  In the case of clinical care systems, this means examining in detail a range of issues from the highest level, such as users, the work they do, and the environments they work in, down to low-level matters, such as data element names and audit trail designs.  As I have stated in previous posts, there is not enough public discussion on clinical software design principles, methods, techniques, etc. Public discourse concerning EHR systems needs to move beyond who likes their system and who does not.  It is time to acknowledge the inherent complexity of systems that support clinical work and approach their design and implementation accordingly.
Hear, Hear.

One more previously cited book with relevance here:

"Machines are for answers. Humans are for questions."
IN 1945 VANNEVAR BUSH, DIRECTOR OF THE UNITED STATES OFFICE of Scientific Research, published an essay in the Atlantic Monthly, entitled “As We May Think.” In it he expressed concern that the world’s knowledge was growing too fast for anyone to keep up: “The difficulty seems to be, not so much that we publish unduly in view of the extent and variety of present day interests , but rather that publication has been extended far beyond our present ability to make real use of the record. The summation of human experience is being expanded at a prodigious rate, and the means we use for threading through the consequent maze to the momentarily important item is the same as was used in the days of square-rigged ships.” Bush acknowledged that great advances were being made in the compression of information, by way of microfilm technology; he foresaw a time in the not too distant future when the entire Encyclopedia Britannica might be “reduced to the volume of a matchbox.” But even given these advances, he worried that the cost and accessibility of such compression would be too high for most to participate in its benefits.

Access wasn’t the only problem. Bush also argued that the way we stored data, compressed or otherwise, was unfit for purpose. We filed it alphabetically and numerically. That meant we could trace a particular piece of information by following paths and subpaths, as librarians did. But the more information there was, the more cumbersome such methods became. Furthermore, this method of organization didn’t reflect the working of the human mind, with its quicksilver ability to make unlikely connections between very different pieces of information...

Leslie, Ian (2014-08-26). Curious: The Desire to Know and Why Your Future Depends On It (pp. 69-70). Basic Books. Kindle Edition.

AMA Statement on Leadership Departures from the Office of the National Coordinator for Health Information Technology

For immediate release: Oct. 27, 2014
Statement attributed to: Robert M. Wah, MD President, American Medical Association

"The American Medical Association (AMA) understands that Karen DeSalvo is leaving her post as the National Coordinator for Health Information Technology (health IT) to do important work in public health.

"DeSalvo's departure, in addition to those of several other senior staff including the Deputy Director of the Office of the National Coordinator for Health IT (ONC), Jacob Reider, which was also announced last week, leaves a significant leadership gap which could jeopardize the growing momentum around interoperability. 

"Interoperability and data portability are critical components for transforming clinical practice and improving health outcomes. Evidence of that connection can be found in the Administration's new Transforming Clinical Practice Initiative, which supports coordinated care and collaboration among physicians that require high-performing technological systems.

"Unfortunately, physicians have been facing challenges with several poor performing electronic health records (EHRs) that are not interoperable. Without widespread interoperability, the value proposition of EHRs has not been realized and the adoption of new innovative models of care has been hindered.

"The AMA has been calling on ONC to make the Meaningful Use certification requirements more flexible so that vendors have more freedom to innovate and tailor their products to meet physicians' needs. We recently released a Meaningful Use Blueprint to outline ways to improve Stages 1 and 2 of the program and provide suggestions for Stage 3, as well as a framework outlining eight priorities for more usable EHRs.

"The AMA is committed to improving care for our patients and looks forward to continuing to work with ONC, and its sister agency the Centers for Medicare and Medicaid Services, to achieve that goal."
Washington Debrief: Health IT Leaders in Shock over DeSalvo, Reider Departures

DeSalvo, Reider Announce Departures from ONC

Key Takeaway: National Coordinator Karen DeSalvo, M.D. and Deputy National Coordinator Jacob Reider, M.D. join the growing ranks of leaders who have recently departed from the Office of the National Coordinator of Health IT (ONC).

Why it Matters: Since passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act, the ONC has been the nation’s chief health IT strategist and primary health IT cheerleader. With the loss of several top officials at ONC, questions over its future, its funding and its role in coordinating health IT policy are circling in the nation’s capitol.

Health IT leaders were shocked last week to learn the top two health IT officials from the Obama administration are leaving their posts. Late Thursday afternoon, Dr. DeSalvo announced to staff her “immediate” reassignment to the Office of the Assistant Secretary for Health to help manage the national response to Ebola. While many health IT leaders identified DeSalvo’s experience with disaster response and preparedness – citing her work during and after Hurricane Katrina – few could say why she was tapped for the job. It also remained unclear whether DeSalvo would return to her post as National Coordinator.

DeSalvo is leaving the office at a critical time, with MU attestation numbers below historic levels, and big policy priorities related to interoperability and Stage 3 yet to be finalized. So far, fewer than 10 percent of hospitals scheduled to meet Stage 2 meaningful use have done so in 2014; physicians are in their last reporting period, but fewer than 2 percent have met that goal this year. With the development of an interoperability and patient safety center roadmap still in the beginning stages, it remains unclear what impact the loss of leadership will have.

Shortly after DeSalvo’s announcement, Deputy National Coordinator Jacob Reider circulated an email to ONC staff announcing his departure from ONC. In the last six months, ONC has lost Chief Privacy Officer Joy Pritts, Chief Science Officer Doug Fridsma, Chief Nursing Officer Judy Murphy and Director of the Office of Consumer eHealth Lygeia Riccardi...
California hospital faces collapse after $77M EMR investment

...Since there is no vaccine against or cure for the disease caused by Ebola virus, the only way to stop it is to break the chains of infection. Health workers must identify people who are infected and isolate them, then monitor everybody with whom those people have come in contact, to make sure the virus doesn’t jump to somebody else and start a new chain. Doctors and other health workers in West Africa have lost track of the chains. Too many people are sick, and more than two hundred medical workers have died. Health authorities in Europe and the United States seem equipped to prevent Ebola from starting uncontrolled chains of infection in those regions, but they worry about what could happen if Ebola got into a city like Lagos, in Nigeria, or Kolkata, in India. The number of people who are currently sick with Ebola is unknown, but almost nine thousand cases, including forty-five hundred deaths, have been reported so far, with the number of cases doubling about every three weeks. The virus seems to have gone far beyond the threshold of outbreak and ignited an epidemic.

The virus is extremely infectious. Experiments suggest that if one particle of Ebola enters a person’s bloodstream it can cause a fatal infection. This may explain why many of the medical workers who came down with Ebola couldn’t remember making any mistakes that might have exposed them...

Despite its ferocity in humans, Ebola is a life-form of mysterious simplicity. A particle of Ebola is made of only six structural proteins, locked together to become an object that resembles a strand of cooked spaghetti. An Ebola particle is only around eighty nanometres wide and a thousand nanometres long. If it were the size of a piece of spaghetti, then a human hair would be about twelve feet in diameter and would resemble the trunk of a giant redwood tree.

Once an Ebola particle enters the bloodstream, it drifts until it sticks to a cell. The particle is pulled inside the cell, where it takes control of the cell’s machinery and causes the cell to start making copies of it. Most viruses use the cells of specific tissues to copy themselves. For example, many cold viruses replicate in the sinuses and the throat. Ebola attacks many of the tissues of the body at once, except for the skeletal muscles and the bones. It has a special affinity for the cells lining the blood vessels, particularly in the liver. After about eighteen hours, the infected cell is releasing thousands of new Ebola particles, which sprout from the cell in threads, until the cell has the appearance of a ball of tangled yarn. The particles detach and are carried through the bloodstream, and begin attaching themselves to more cells, everywhere in the body. The infected cells begin spewing out vast numbers of Ebola particles, which infect more cells, until the virus reaches a crescendo of amplification. The infected cells die, which leads to the destruction of tissues throughout the body. This may account for the extreme pain that Ebola victims experience. Multiple organs fail, and the patient goes into a sudden, steep decline that ends in death. In a fatal case, a droplet of blood the size of the “o” in this text could easily contain a hundred million particles of Ebola virus...
From "The Ebola Wars." Pretty frightening article.

Today’s EHR systems use different languages and interfaces that make information sharing technologically impossible, while competitive pressures encourage information hoarding and discourage information sharing. The Ebola crisis in Dallas presents a clear and dramatic case – one in which the technology was not designed as well as it might have been and hospital staff failed to make appropriate use of the information it did provide. Although this case does not squarely focus on the absence of interoperability, its absence – along with the absence of any means of communication between health care and public health – lies just below the surface, an additional dimension of the systemic failure presented here.
From Health Affairs: "Ebola And EHRs: An Unfortunate And Critical Reminder"

More to come...

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