Category: Uncategorized

Maslow’s Hierarchy of Health IT

Jul 3, 2014• 4

By David Do, MD

EMR adoption is skyrocketing, in no small part due to government incentives. The office of the national coordinator lauds this hockey-stick curve as a success. Advocates promise electronic records will improve patient care, reduce mistakes, and save healthcare costs. At the same time, doctors love to complain about implementation cost and poor usability. How can we reconcile these differing opinions? The truth is they are describing very different technologies. EMRs, the way they are implemented now, will not accomplish these goals. In fact, early adopters can become stuck at a rudimentary level of functionality, and the extensive feature lists described by meaningful use criteria fail to address the most basic needs for patient care.

I have been at medical institutions at different levels of technological development. Each has a different attitude toward the EMR; for some its loathing, others longing. Some devote resources to try to improve it, but others give up. I realized the parallels with Maslow’s Hierarchy of Needs, people are motivated to attain something only after their very basic needs have been fulfilled. So are EMRs good or bad? Well, it depends on where you are on the hierarchy.

The figure above describes the steps to building a technology infrastructure that will lead to improved patient care. Yes, incentives help us achieve some very basic needs, but the problem is that decisions and investments we make now will determine the ceiling as well.

The Cost Curve Probably Won’t Bend Downwards. But That’s Ok.

Jul 3, 2014• 9

By SARAUBH JHA, MD

To control the nation’s overarching fecundity the government of India raised mass awareness of condoms; the chief effect of which were a load of giggling school boys and a load of giggling school girls. Further, in an initiative by Sanjay Gandhi, vasectomies were performed, nearly en masse, through a mixture of cajolement, economic incentives and coercion.

The fertility curve remained unbent.

Then along came color TV. Paul Ehrlich’s doomsday prophecies were forestalled. I know correlation is not causation, let alone abstinence. I’m just saying.

Policy is a strange and lucky beast. It can survive its futility. It is not so much occasionally inept as often incidental. And it has the epistemological luxury of not being easily falsifiable: i.e. it’s hard to prove that it was not responsible for the effect for which it was instituted.

Can you prove that it was not condoms but color TV that derailed India’s logarithmic fecundity? Good luck randomizing to the television arm.

Yes I can hear you muttering “ahem seatbelts.” This is not to say policy never achieves its desired aims. It’s to say that it’s not easy to distinguish policy’s true successes from pseudo successes.

The Coming Debate Over Specialty Drugs

Jul 2, 2014• 17

By Ceci Connolly

The debate over the price of specialty drugs is intensifying and could well be the next major healthcare issue to dominate the national, even international, agenda. In a nutshell, how will society pay for breakthrough scientific innovation?

Specialty drugs, complex therapies used to treat severe illnesses such as cancer, multiple sclerosis and Hepatitis C, are coming in with price tags that have purchasers sounding alarm bells. At $1,000 per pill, the newest Hep C medication runs about $86,000 for a course of treatment. Two major insurers have publicly cited the price of this single new drug as contributing to next year’s rise in premiums.

In fact, analysis by our team at PwC’s Health Research Institute shows that this one new therapy will impact overall U.S. health costs by .5% this year and .2% next year. Considering the nation’s total healthcare budget is $2.8 trillion, that is a remarkable budgetary impact for one product.

But the story doesn’t end there. Drug costs represent just 15% of total health spending, compared to nearly one-third spent on inpatient care. Short-term budget spikes could become long-term savers from both a cost and health standpoint. For the most severe patients, the price of Hep C medication – that is nearly 90% effective – is three to six times less than treating a lifetime of cirrhosis ($270,000) or providing a liver transplant ($580,000.) Patients essentially “cured” of Hepatitis C can go on to have productive, long lives.

Physician Burnout: It’s Time to Take Care of Our Own

Jul 2, 2014• 22

By SAMANTHA MELTZER-BRODY, MD

Despite highly skilled physicians and advanced technology, the U.S. has not yet figured out how to provide effective affordable health care to everyone. Meanwhile, the health care system is increasingly fractured and stressed—and so are our doctors. Physician burnout impacts nearly half of all seasoned physicians in practice and up to 75% of resident physicians in training1. Over water cooler conversations, as well as in my work as a psychiatrist at the University of North Carolina at Chapel Hill (UNC), I hear more and more physicians report anxiety, stress and emotional exhaustion. Many feel as if they are perpetually swimming upstream; others feel there is no joy or meaning in their work; some want to quit medicine altogether. These good doctors are in crisis in increasingly high numbers — an epidemic that requires immediate attention.

Last year, the UNC School of Medicine launched the Taking Care of Our Own program to address the problem of physician burnout and we have been met with a deluge of physicians asking for help. Burnout, however, is not a diagnosis. It is a constellation of symptoms that include emotional exhaustion, depersonalization and loss of perspective that work is meaningful2. Untreated, burnout syndrome can erode professional behavior at work and healthy relationships at home. This leads to decreased empathy and compassion, poor communication and potentially worse patient outcomes. The personal consequences include disrupted relationships with family and friends, self-medicating with alcohol or other substances, depression and an increased risk of suicide, which is higher among physicians than the general population, in part due to the stigma associated with seeking mental health treatment.

Not a day goes by without my hearing from a physician in distress who has learned about the Taking Care of Our Own program. These conversations have a striking degree of similarity. They typically begin with an apology—a statement about how embarrassing it is to ask for help in dealing with anxiety or depression; or a recent loss; or other emotional stressor that makes it too difficult for the doctor to remain professional and compassionate while managing a demanding workload.

Big Data in Healthcare: Good or Evil? Depends on the Dollars

Jul 1, 2014• 25

By JOE FLOWER

An organization’s “business model” means: How does it make a living? What revenue streams sustain it? How it does that makes all the difference in the world.

Saturday, Natasha Singer wrote in the New York Times about health plans and healthcare providers using “big data,” including your shopping patterns, car ownership and Internet usage, to segment their markets.

The beginning of the article featured the University of Pittsburgh Medical Center (UPMC) using “predictive health analytics” to target people who would benefit the most from intervention so that they would not need expensive emergency services and surgery. The later part of the article mentioned organizations that used big data to find their best customers among the worried well and get them in for more tests and procedures. The article quoted experts fretting that this would just lead to more unnecessary and unhelpful care just to fatten the providers’ bottom lines.

The article missed the real news here: Why is one organization (UPMC) using big data so that people end up using fewer expensive healthcare resources, while others use it to get people to use more healthcare, even if they don’t really need it?

Because they are paid differently. They have different business models.

UPMC is an integrated system with its own insurance arm covering 2.4 million people. As a system it has largely found a way out of the fee-for-service model. It has a healthier bottom line if its customers are healthier and so need fewer acute and emergency services. The other organizations are fee-for-service. Getting people in for more tests and biopsies is a revenue stream. For UPMC it would just be a cost.

The evil here is not using predictive modeling to segment the market. The evil here is the fee-for-service system that rewards waste and profiteering in medicine.

Electronic Cigarettes: What’s in the Vapors?

Jun 30, 2014• 5

By Maciej Goniewicz

Users and non-users of electronic cigarettes (e-cigarettes) have many legitimate questions about these nicotine-delivery devices. E-cigarettes represent a nearly $2-billion-a-year industry, and one that’s growing exponentially. The number of young people trying e-cigarettes doubled from 2011 to 2012, according to the Centers for Disease Control. So it is natural that so many people are interested in the health consequences of using e-cigarettes.

Research from the Department of Health Behavior at Roswell Park Cancer Institute has documented the impact of first-, second- and third-hand exposure to e-cigarette vapors. Our most recent research, done in collaboration with scientists from the Medical University of Silesia in Poland, offers insight into the user’s exposure to carcinogenic carbonyls.

The e-liquids used in e-cigarettes are primarily composed of glycerin and propylene glycol. We set out to find out what chemicals are generated during use of e-cigarettes, particularly at variable voltages. Some devices allow the user to adjust the voltage to increase vapor production and nicotine delivery.

We found that when e-cigarettes were operated at lower voltages, the vapors that were generated contained only traces of some toxic chemicals. These chemicals included the carbonyls formaldehyde, acetaldehyde, and acetone. However, when the voltage was increased, the levels of these toxicants also significantly increased.

The novel finding of our study is that the higher the voltage, the higher the levels of carbonyls. Increasing battery output voltage leads to higher temperature of the heating element inside the e-cigarette. Increasing the voltage from 3.2 to 4.8 volts resulted in increases of anywhere from 4 times to more than 200 times the exposure to formaldehyde, acetaldehyde and acetone. The levels of formaldehyde in vapors from high-voltage devices were similar to those found in tobacco smoke.

Is the Electronic Health Record Defunct?

Jun 30, 2014• 28

By JEROME CARTER , MD

When building software, requirements are everything.

And although good requirements do not necessarily lead to good software, poor requirements never do. So how does this apply to electronic health records? Electronic health records are defined primarily as repositories or archives of patient data. However, in the era of meaningful use, patient-centered medical homes, and accountable care organizations, patient data repositories are not sufficient to meet the complex care support needs of clinical professionals. The requirements that gave birth to modern EHR systems are for building electronic patient data stores, not complex clinical care support systems–we are using the wrong requirements.

Two years ago, as I was progressing in my exploration of workflow management, it became clear that current EHR system designs are data-centric and not care or process-centric. I bemoaned this fact in the post From Data to Data + Processes: A Different Way of Thinking about EHR Software Design. Here is an excerpt.

Do perceptions of what constitutes an electronic health record affect software design? Until recently, I hadn’t given much thought to this question. However, as I have spent more time considering implementation issues and their relationship to software architecture and design, I have come to see this as an important, even fundamental, question.

The Computer-based Patient Record: An Essential Technology for Health Care, the landmark report published in 1991 (revised 1998) by the Institute of Medicine, offers this definition of the patient record:

A patient record is the repository of information about a single patient. This information is generated by health care professionals as a direct result of interaction with the patient or with individuals who have personal knowledge of the patient (or with both).

Note specifically that the record is defined as a repository (i.e., a collection of data). There is no mention of the medium of storage (paper or otherwise), only what is stored. The definition of patient health record taken from the ASTM E1384-99 document, Standard Guide for Content and Structure of the Electronic Health Record, offers a similar view—affirming the patient record as a collection of data. Finally, let’s look at the definition of EHR as it appears in the 2009 ARRA bill that contains the HITECH Act:

ELECTRONIC HEALTH RECORD —The term ‘‘electronic health record’’ means an electronic record of health-related information on an individual that is created, gathered, managed, and consulted by authorized health care clinicians and staff. (123 STAT. 259)

Even here, 10 years later, the record/archive/repository idea persists. Now, back to the issue at hand: How has the conceptualization of the electronic health record as primarily a collection of data affected the design of software systems that are intended to access, manage, and otherwise manipulate said data?

Killer Features of the Next EMR

Jun 29, 2014• 18

By CRAIG MONSEN

I was absent-mindedly playing with my iPhone today and took special notice of a feature I have rarely used before. If you swipe all the way to the left on the home screen, you will get a search bar to search all of your iPhone. This includes contacts, iMessages, and apps. I’ve never needed to use this before—a testament to the iPhone’s ease of use. Just prior to this, I was working on some patient notes using my hospital’s electronic medical record (EMR). In contrast, each task I performed required a highly-regimented, multi-click process to accomplish.

Criticizing EMR interfaces is a well-loved pastime among clinicians. Here, however, I am going to take an oblique approach and reflect instead on what has made good interfaces (all outside of medicine, it turns out) recognized as such.

Speed

The Google Algorithm often gets credit for Google winning the Great Search Engine War. Indeed, there are whole teams dedicated to improving it. However, if you compare algorithms today, even 5 years ago, the differences in results have been only marginal. How does Google stay ahead? Speed. Google has done extensive research to determine what keeps users coming back and it is unequivocally speed of results. It has been much of the motivation for creating their own browser (Chrome) and operating system (Android). Speed means more searches and more searches means more money for Google.

Search

With EMRs, wait times to store and retrieve data can be extremely long. Moreover, it frequently takes multiple clicks to get to the precise page you want, further compounding the problem. But how slow is slow? Research in web user behavior indicates that 47% of consumers expect a web page to load in 2 seconds or less and that 40% of people abandon a website that takes more than 3 seconds to load. It regularly takes over 3 seconds to retrieve an important piece of data from an EMR. That makes the experience constantly frustrating; I wish there was another EMR I could switch to. (As a fun aside, I often find myself logging into two computers side-by-side in the hospital to save precious seconds waiting for the computer to load.)

What Would You Do If You Were Me?

Jun 28, 2014• 25

By NORTIN HADLER, MD

“Effectiveness” is at the forefront of the health policy debate. Effectiveness is the assessment of whether any particular medical intervention actually advantages patients when prescribed in practice settings. To be considered effective, the intervention must result in a clinically meaningful improvement for an adequate percentage of patients. Furthermore, it must not result in a clinically important adverse outcome in too many. Clearly, “effectiveness” is a value-laden construct. How is “meaningful improvement” defined and by whom? How is “important adverse outcome” defined and by whom? How are “adequate percentage” and “too many” defined and by whom?

“Cost-effectiveness” is even more value-laden. It is legislated to be off-the-table in the machinations of the Affordable Care Act for reasons that vary from fear of rationing to fear of compromising profit margins. But no one can exclude cost-effectiveness from the patient-doctor dialogue. Considerations of co-pays and deductibles often weigh heavily in the valuation of interventions.

The greatest advance in clinical medicine in my time in the practice, fast approaching 50 years, is that today patients and their doctors can assess effectiveness as collaborators. No longer does an imperious pronouncement by a physician suffice. Rather, the patient should occupy the driver’s seat with the physician as navigator. For each option in intervention, the patient asks, “Based on the available science, what is the best I can expect?”

For nearly 50 years, no prescription drug could be marketed unless the FDA was convinced that it had a tolerable benefit-to-risk ratio based on scientific studies. The bar for devices (like hip replacements) and procedures (like liposuction) is not as high, but there is usually some informative clinical science of this nature. The science is generally designed in the hope of demonstrating a favorable benefit-to-risk ration. Hence, patients and interventions are chosen to measure outcomes in the best case. However, make no mistake; neither the fact of FDA approval nor common practice is an adequate response to “What is the best I can expect?” If the best case falls short in your mind, why would you acquiesce to the intervention?

Disrupted: How Computerization Is Changing the Practice of Medicine In Surprising Ways

Jun 28, 2014• 39

By BOB WACHTER, MD

Bob Wachter

The following is an excerpt from the preface of my new book, which is tentatively titled: “Disrupted: Hope, Hype and Harm at the Dawn of Medicine’s New Age.” Author’s note and request to THCB readers.

If you’re a 24-year-old who does not plan on getting sick for the next couple of decades, this is probably not the ~~book~~ blog post for you.

By the time you need our healthcare system, it will be wired in ways we can’t imagine today. By then, computers will have transformed healthcare – as they already have retail, publishing, photography, and travel – leaving it better, safer, and maybe even cheaper. Most of the kinks, perhaps other than what our society will do with boatloads of unemployed dermatologists, radiologists, and hospital administrators, will have been ironed out. I hope to live to see this day myself. It’ll be, as my kids say, hecka cool.

But for the rest of us – both those who need our medical system today and those who currently work in it – the path to computerization will be strewn with landmines, large and small. The challenges are everywhere. Medicine, our most intimately human profession, is being dehumanized by the entry of the computer into the exam room. While computers are preventing many medical errors, they are also causing new kinds of mistakes, some of them whoppers. Sensors and monitors are throwing off mountains of data, often leading to more cacophony than clarity. Patients are now in the loop – many get to see their laboratory and pathology results before their doctor does; some are even reading their doctor’s notes – yet are woefully unprepared to handle their hard-fought empowerment.

In short, while someday the computerization of medicine will undoubtedly be that long-awaited “disruptive innovation,” today it’s often just plain disruptive: of the doctor-patient relationship, clinicians’ professional interactions and workflow, and the way we measure and try to improve things. I’d never heard the term “unanticipated consequences” in my professional world until a few years ago, and now we use it all the time, since we – yes, even the insiders – are constantly astonished by the speed with which things are changing and the unpredictability of the results.

Before we go any further, it’s important that you understand that I am all for the computerization of healthcare. I bought my first Mac in 1984, back when one inserted and ejected floppy disks so often (“Insert Excel Disk 2”) that the machine felt more like an infuriating toaster than a sparkling harbinger of a new era. Today, I can’t live without my MacBook Pro, iPad, iPhone, Facetime, Twitter, OpenTable, and Evernote. I even blog and tweet. In other words, I am a typical, electronically overendowed American.

And healthcare needs to be disrupted. Despite being staffed with (mostly) well trained and committed doctors and nurses, our system delivers evidence-based care about half the time, kills a jumbo jet’s worth of patients each day from medical mistakes, and is bankrupting the country. Patients and policymakers are no longer willing to tolerate the status quo, and they’re right.