Shortliffe emphasized the multidisciplinary nature of the field — that clinicians and computer science-oriented types need be involved for health information technology (HIT) to be effective. “Human health is at the core of it,” he said. The goal of biomedical informatics isn’t for computers to replace humans, he said, but for doctors to learn how to use it – as a tool – so that we (human doctors) can practice better medicine.

He reviewed the 50-year history of the field. The super-simple summary goes something like this: in the 1960s hospitals developed early information systems; in the 1970s, early decision support and electronic health records (EHRs) emerged at hospitals and large institutions; in the 1980s clinical research trials led to databases involving patients across medical centers; in the 1990s, progress in science (especially genetics) led to modern biomedical informatics. Now, the vast work includes clinical, imaging, biology (molecular, genomic, proteomic data) and public health.

Clinical informatics is the newest field supported by the American Board of Medical Specialties.  The first boards will be offered in October of this year, he mentioned.

If you’re interested in the future of health IT, as I am, you might want to take a glance at a perspective published recently by Dr. Shortcliffe and two coauthors, Putting Health IT on the Path to Success, in JAMA. The authors consider the slow pace of implementing HIT, and suggest that the solution rests with patient-centric Health Record Banks (HRBs):

“…Health record banks are community organizations that put patients in charge of a comprehensive copy of all their personal, private health information, including both medical records and additional data that optionally may be added by the patient. The patient explicitly controls who may access which parts of the information in his or her individual account.

I’d like to see these emerge.

Marcus Welby, M.D. (1969–1976), IMDb

But if you’re sick – if you’re a patient, and not a consumer, in this blog’s lingo — well, then, of course you need a doctor if you want to get well. Physicians are necessary, still, especially if you’ve got a serious illness, like colon cancer, malaria, catatonic depression, rheumatoid arthritis or Type I diabetes, to name a few doctor’s attention-worthy conditions. Even for someone like me, who’s gone through med school, residency, fellowship and spent years giving medical care to other people, having a thoughtful physician – someone whose experience and intelligence I trust – is indispensible.

My doctors help me sort through the literature, if I choose to read it (I don’t always) and figure out what makes sense for me to live without pain and as fully as possible. I value their work immeasurably. But, as much as I have been helped by nurses, physical therapists, pharmacists and peer patients, the doctor’s opinion matters most. Admittedly, I’m lucky in this. Over the years, I’ve accrued a team of excellent physicians whom I trust. That’s not a common scenario now, which is part of why this question matters so much.

The updated part of the question, now, is whether nurse practitioners (NPs), straight RNs, physician assistants (PAs), pharmacists, social workers and others including, yes, peer patients, should take up much — or even most, of doctors’ tasks. As outlined in a recent editorial, these non-physician health care workers can be paid less and may do a better job at certain chores that, historically, have been carried out by MDs. They can order scans and contact patients about the results, fill out forms for home physical therapy, measure your blood pressure and give injections, like flu shots.

At one level, assigning minor and not-so-minor tasks to other kinds of health care providers sounds great. It’s a partial, 2-for-1 solution, because it relieves the physician shortage and, simultaneously, lowers health care costs. It makes perfect sense, to a point, for efficiency.  There are, legitimately, some tasks that nurses are better-trained to do, such as giving medications. Pharmacists are more likely to pick up on dangerous drug combinations than busy pediatricians, because that’s the focus of their work and training. Peer patients are valuable too. Etc.

But if doctors are just thinking about your “case” or doing complex  procedures, and not being the ones to call you back, or putting in intravenous catheters, or even just sitting and taking a thorough history – they’ll know you less well. And if they spend less time with you, a patient with a serious illness, they – according to the laws of human nature, and my observations on rounds on hospital wards over many years – will not care so much about the outcome of your case. When and if a doctor spends time with a patient, that builds trust, concern, and – possibly, better outcomes.

Reality dictates that we have to protect doctors’ time so they can read, sleep, and spend at least a few minutes each day with the people they care about outside of the workplace, and take care of themselves. If we don’t unload some of the tasks to other health care workers, we’d have to assign fewer patients to each physician. That would exacerbate the shortage…

No simple answer -

ES

So here’s what I see, now – in terms of three priority areas: improving treatment, prevention, and education to inform treatment decisions.

Pumpkins, organized by subtype (WikiCommons image)

As an oncologist, I perceive huge strides in understanding BC since the time of my diagnosis. But these advances are largely invisible to patients because they’re in the realm of pathology and classification of different subtypes. What was essentially a 3-type malignancy with a handful of treatment options has expanded under the molecular microscope to a spectrum of 4, 10 or – what’s probably most accurate – hundreds or thousands of patient-particular conditions, depending on the level of precision by which you define a disease. I’m optimistic, because it looks as though, in my lifetime, BC treatment will be tailored to each patient. There’ll be less surgery and better drugs.

The hitch, now, is not so much with science as with funding– funding to analyze each patient’s tumor at the genetic and protein levels, funding to pay for treatments selected by patients (which might include less treatment and/or palliative care in advanced cases), and funding to educate doctors about BC subtypes and medical progress, so they might offer “modern” advice to each patient in ordinary clinics, apart from clinical trials and academic centers. Newer is not always better in medical care. Same goes for more treatment (especially when it comes to higher doses). Still, the lag between advances in BC science and application of distinct, targeted and better treatments is frustrating at best.

Some of my colleagues call for patience — emphasizing that studies need be confirmed, drugs tested in mice, etc. Their point is that we can’t jump from pathology research and new BC classifications to new therapy. But one lesson I take from progress against AIDS is that maybe we shouldn’t be so patient. At least not for young people with poor-prognosis BC subtypes or stage. We could do studies and studies of particular BC treatments, and studies of studies (those would be meta-analyses) and debate 8 or 10 years from now whether a particular drug or combination of drugs worked in clinical trials that selected for patients with an antiquated subtype of the disease. Or we could move toward “n=1” trials, with smart, well-trained physicians assessing each patient by a combination of old-fashioned physical exams and the most modern of molecular studies of the tumors, considering the options, and moving forward with individual, mini-experimental treatment plans.

I vote for the latter. If the drug works in a patient with advanced BC and the patient feels better, why not?

For people with early-stage BC, prescribing or taking new and essentially untested drugs makes less sense at first glance. That’s because standard treatments are “successful” – leading to long-term remissions and possible cures in over 80 percent of those affected. But these relatively good results may have, paradoxically, hampered development of better drugs that could obviate the need for breast-deforming surgeries and radiation in many women. The possible application of BC drug cocktails, in lieu of surgery for early-stage patients, is a huge question for the future, and one for which trials would be necessary. Just getting those projects going – applying BC science to treatment of early-stage cases – would be a step in the right direction.

As for BC prevention, of course that would be infinitely better than detecting or treating the disease. Unfortunately, I think we’re farther away from preventing the disease than we are from having effective and less brutal treatments for most patients. The problem with lifestyle modification – like staying active and not obese – is that it’s far from full-proof: You can be seemingly fit as a fiddle and get a lethal case of BC. Still, there are plenty of other health-related reasons for women to exercise and eat sensibly. As for avoiding carcinogens or, first, just knowing what chemicals contribute to BC formation and growth, the science isn’t there yet.  It’ll be a long haul before anyone can prove that a particular chemical causes this disease. That said, I advocate research in the slow-growing field of environmental oncology and wish there’d be more enthusiasm for regulating our exposure to likely-toxic chemicals.

The third priority is for improving education in math and science, starting at the elementary school level. Doctors need to understand statistics, but many don’t. They need to know about genomics and basic science in medicine. Patients need this kind of knowledge if they want to have a clue, if they want to engage meaningfully in decisions about which antibody to take, or pill, or whether they want to participate in a clinical trial of pills instead of surgery for a Stage II tumor with high levels of Her2, for example. That’d be a tough decision for an oncologist. I only wish that we could reach the point where we could have those kinds of truly informed conversations about clinical treatment of breast cancer, which happen every day.

We’ve got a lot of information in hand, but we need to learn how to apply that to more patients, faster and more openly.

All for a while. I’m open to ideas on this. Happy October!

ES

Until there’s a way to prevent BC, we need better ways to treat it. Which is why, upon reading the new paper in Nature on genetic patterns in breast cancer, I stayed up late, genuinely excited. As in thrilled, optimistic..The research defined 10 molecular BC subgroups. The distinct mutations and gene expression patterns confirm and suggest new targets for future, better therapy.

The work is an exquisite application of science in medicine. Nature lists 31 individuals and one multinational research group, METABRIC (Molecular Taxonomy of Breast Cancer International Consortium), as authors. The two correspondents, Drs. Carlos Caldas and Samuel Aparicio, are based at the University of Cambridge, in England, and the University of British Columbia in Vancouver, Canada. Given the vastness of the supporting data, such a roster seems appropriate, needed. The paper, strangely and for all its worth, didn’t get much press -

Just to keep this in perspective – we’re talking about human breast cancer. No mice.

The researchers examined nearly 2000 BC specimens for genetic aberrations, in 2 parts. First, they looked at inherited and acquired mutations in DNA extracted from tumors and, when available, from nearby, normal cells, in 997 cancer specimens – the “discovery set.” They checked to see how the genetic changes (SNPs, CNAs and/or CNVs) correlated with gene expression “landscapes” by probing for nearly 29,000 RNAs. They found that both inherited and acquired mutations can influence BC gene expression. Some effects of “driver” mutations take place on distant chromosomal elements, in what’s called a trans effect; others happen nearby (cis).

Next, they honed in on 45 regions of DNA associated with outlying gene expression. This led the investigators to discover putative cancer-causing mutations (accessible in supplementary Tables 22–24, available here). The list includes genes that someone like me, who’s been out of the research field for 10 years, might recall – PTEN, MYC, CDK3 and –4, and others. They discovered that 3 genes, PPP2R2A, MTAP and MAP2K4 are deleted in some BC cases and may be causative. In particular, they suggest that loss of PPP2R2A may contribute to luminal B breast cancer pathology. They find deletion of MAP2K4 in ER positive tumors, indicative of a possible tumor suppressor function for this gene in BC.

Curtis, et al. in “Nature”: April 2012

The investigators looked for genetic “hotspots.” They show these in Manhattan plots, among other cool graphs and hard figures, on abnormal gene copy numbers (CNAs) linked to big changes in gene expression. Of interest to tumor immunologists (and everyone else, surely!), they located two regions in the T-cell receptor genes that might relate to immune responses in BC. They delineated a part of chromosome 5, where deletions in basal-like tumors marked for changes in cell cycle, DNA repair and cell death-related genes. And more –

Cluster Analysis (abstracted), Wikipedia

Heading toward the clinic, almost there…

They performed integrative cluster analyses and defined 10 distinct molecular BC subtypes. The new categories of the disease, memorably labeled “IntClust 1–10,” cross older pathology classifications (open-access: Supplementary Figure 31) and, it turns out, offer prognostic information based on long-term Kaplan-Meier analyses (Figure 5A in the paper: Supplementary Fig 34 and 35). Of note, here, and a bit scary for readers like me, is identification of an ER-positive group, “IntClust 2” with 11q13/14 mutations. This BC genotype appears to carry a much lesser prognosis than most ER-positive cases.

Finally, in what’s tantamount to a 2^nd report, the researchers probed a “validation set” of 995 additional BC specimens. In a partially-shortened method, they checked to see if the same 10 molecular subtypes would emerge upon a clustering analysis of paired DNA mutations with expression profiles. What’s more, the prognostic (survival) information held up in the confirmatory evaluation. Based on the mutations and gene expression patterns in each subgroup, there are implications for therapy. Wow!

I won’t review the features of each type here for several reasons. These are preliminary findings, in the sense that it’s a new report, albeit a model of what’s a non-incremental published set of observations and analysis; it’s early for patients — but not for investigators — to act on these findings. (Hopefully, this will not be the case in 2015, or sooner, preferably, for testing some pertinent drugs in at least a subset of the subgroups identified.) Also, some of the methods these authors used came out in the past decade, after I stopped doing research. It would be hard for most doctors to fully appreciate the nuances, strengths and weaknesses of the study.

Most readers can’t know how skeptical I was in the 1990s, when grant reviewers at the NCI seemed to believe that genetic info would be the cure-all for most and possibly all cancers. I don’t think that’s true, nor due most people involved with the Human Genome Project, anymore. The Cancer Genome Atlas and Project should help in this regard, but they’re young projects, larger in scope than this work, and don’t necessarily integrate DNA changes with gene expression as do the investigators in this report. What’s clear, now, is that some cancers do respond, dramatically, to drugs that target specific mutations. Recently-incurable malignancies, like advanced melanoma and GI stromal tumors, can be treated now with pills, often with terrific responses.

Last night I wondered if, in a few years, some breast cancers might be treated without surgery. If we could do a biopsy, check for the molecular subtype, and give patients the right BC tablets. Maybe we’d just give just a tad of chemo, later, to “mop up” any few remaining or residual or resistant cells. The primary chemotherapy might be a cocktail of drugs, by mouth. It might be like treating hepatitis C, or tuberculosis or AIDS. (Not that any of those are so easy.) But there’d be no lost breasts, no reconstruction, no lymphedema. Can you imagine?

Even if just 1 or 2 of these investigators’ subgroups pans out and leads to effective, Gleevec–like drugs for breast cancer, that would be a dream. This can’t happen soon enough.

With innovative trial strategies like I-SPY, it’s possible that for patients with particular molecular subgroups could be directed to trials of small drugs targeting some of the pathways implicated already. The pace of clinical trials has been impossibly slow in this disease. We (and by this I mean pharmaceutical companies, and oncologists who run clinical trials, and maybe some of the BC agencies with funds to spend) should be thinking fast, way ahead of this post -

And given that this is a blog, and not an ordinary medical publication or newspaper, I might say this: thank you, authors, for your work.

—

He’s a TED speaker, I knew. From the TED bio: “Eric Topol uses the study of genomics to propel game-changing medical research.” His work sounds exciting! I first read of the new book in a recent, tech-minded interview in Wired. Seemed like it might be all theory, no touch-y, little reality. With this lead-in, I wasn’t quite prepared to like this book, although I was interested.

Topol’s book is fantastic. I couldn’t put it down because it’s chock-full of good, critical ideas about clinical medicine. The title, “Creative Destruction,” is a reference to Joseph Schumpeter’s theory of radical transformation through innovation. In Chapter 1, he outlines the “Digital Landscape” and explains, simply, how a convergence of advances in technology over the past 40 years – like personal computers, cell phones, the Internet, connectivity and instant access to data – have set the stage for a dramatic shift in medical culture and practice. Doctors, for some reason, have been slow to adapt digital technology to health care, but this is changing, fast.

One theme that emerges through the book is the capacity for technology – by “knowing” and processing so much real-time information about each person’s condition — to inform more effective, individualized treatments. This comes up in his critique of evidence-based medicine and later, when he considers progress in molecular oncology and again, in a section on the pitfalls of old-fashioned, large clinical trials involving many (hundreds or thousands of) patients unlikely to benefit.

Topol’s comfortable writing about the intersection of science and medicine as few physicians are. He describes several clinical episodes, like when the first patient with a stroke received TPA, a clot-dissolving agent. The point is, he’s been there, at some of the world’s best hospitals, where innovative treatments have been applied. But he’s also seen first-hand disappointment, too. This grounds the work. There’s a long chapter on “Biology” which offers, among other insights, a realistic critique of genetic information that many doctors don’t understand. He identifies value in hypothesis-free research, and considers high-throughput screening.

I should mention two provocative details, among many. One appears in Chapter 3, on “empowered” medical consumers. At the Cleveland Clinic Foundation, where he’d worked and served on the Board of Governors, Topol observed busy, otherwise-occupied trustees who contributed significant time and money to the hospital. One reason they did so, he says, was so they might have access to the best doctors “in case anyone in my family or I get sick” (p. 50). He cites flaws in popular hospital ranking systems, like U.S. News & World Report, and offers tips for how to find a good doctor for a particular condition, like checking publications in Google Scholar and looking for senior authors of highly-cited papers. He writes:

“The heterogeneity of the quality of care is not adequately appreciated, and all too often consumers accept the convenient, easy alternative…If this involves a physician or surgeon who does procedures or operations, it is essential to ask for the exact number of procedures performed per year and cumulatively over his or her career…” (pp. 52–53).

The point here is that physicians are not machines. Some are more capable than others, and the quality of care received depends on the doctor’s training, experience and other human qualities.

Another gem, in Chapter 11, pertains to the “science of individuality.” We’re at a threshold, Topol says, of eliminating ignorance in medicine. For doctors and informed patients who happen upon this review: idiopathic, essential and cryptogenic diseases will be gone. Instead, we’ll have conditions defined molecularly or, even if not understood, rooted in the concept of N=1. He writes:

…a new body of data that can be derived from any individual, both at baseline and after an intervention……This opportunity leverages the immense molecular biological, physiologic, and anatomic data that can be determined for any individual, and reinforces that the ultimate goal of an intervention is to have a markedly favorable impact on each n-of-1, rather than the current model, which emphasizes population medicine with the relatively small chance that any individual may derive benefit.

What he’s saying is that the more quickly and inexpensively we can gather and process details about a patient’s medical condition, the more cleverly we can apply treatments designed to help, even in the absence of large trials.

I love this idea.
—

Kathy Rich, as featured in ‘O’ Magazine

The first lesson, if I might call it that — in the way an oncologist can learn from variations in her patients’ pathology and clinical outcomes — comes from the case of Katherine Russell Rich, who died last week at the age of 56. As reported by Katherine O’Brien in the I Hate Breast Cancer Blog, Rich lived with metastatic BC (MBC) for 18 years. That’s phenomenal, was my first reaction to this news. The prognosis for MBC is said to be around 3 years, and Rich lived for 18 years beyond her tumor’s recurrence with stage IV disease.

As sad and unsatisfactory as this outcome may seem, and it is, Rich’s story offers hope for life beyond the 3 or 4 or 5 years some women with MBC pray, “ask” or otherwise bargain for, fingers-crossed…

As she detailed in an O article, Rich’s initial diagnosis came when she was 32 years old, in 1988. The Times, in an obituary, tells of her lumpectomy, chemo and radiation. In 1993 her cancer came back in bones including her spine. She had a bone marrow transplant, but the disease progressed. Ultimately, she coursed through various and some archaic hormone treatments.

Along the way, she lost or quit a job in publishing, or both, and traveled to India, and authored two books. In a 2010 first-person story about her case, she told of updating her status – of being alive — at Breastcancer.org each year. She wrote:

…I tell the women how deeply I believe there’s no such thing as false hope: all hope is valid, even for people like us, even when hope would no longer appear to be sensible.

Life itself isn’t sensible, I say. No one can say with ultimate authority what will happen — with cancer, with a job that appears shaky, with all reversed fortunes — so you may as well seize all glimmers that appear.

My take, as an oncologist and former clinician, is that patients sometimes surprise you. Hard to know which woman will respond to a non-targeted treatment, or even a drug like an estrogen modulator, without trying. And I wonder – and this is speculative, but maybe, likely, the two together – doctor and patient – worked together to see what worked in Rich’s case over nearly 2 decades, and what didn’t work.

A Bell Curve

If a drug helps, keep it going; if it hurts, stop. There are so many algorithms in medicine, and molecular tools, but maybe the bottom line is how the, one, your patient is doing.

Which leads me to another post, by Dr. David Gorski, a breast cancer surgeon and researcher who blogs as Orac — what once was imagined as a fabulously capable information processor, at Respectful Insolence. He describes how tough it can be to define, and thereby target or destroy, any individual patient’s breast tumor because the cancer cells are constantly changing. Within each woman’s tumor, an evolution-like process is ongoing, leading to selection of treatment-resistant cells. This is not news in oncology; the concept has been understood for years as it applies to “liquid” tumors like leukemia, as he points out.

In breast cancer, understanding the complexity of each case is more recent. Gorski considers a genetic analysis of 104 triple negative breast cancer (TNBC) cases presented at the recent AACR meeting and published last week in Nature:

“…The 59 scientists involved in this study expected to see similar gene profiles when they mapped on computer the genomes of 100 tumours.

But to their amazement they found no two genomes were similar, never mind the same. “Seeing these tumours at a molecular level has taught us we’re dealing with a continuum of different types of breast cancer here, not just one,” explains Steven Jones, co-author of this study.

…TNBC is not a single disease. In fact, even an individual TNBC tumor is not a single disease. Tumor cells evolve as they proliferate, so that the cells in them are genetically heterogeneous. The cells growing in one area of a tumor can and often do harbor markedly different genetic mutations from the cells growing in another part of the tumor…

The team found that each tumor displayed multiple “clonal genotypes,” suggesting that the cancer would have to be treated as multiple diseases, rather than a single entity.

So besides that there are distinct subtypes of breast cancer, those labeled as TNBC are diverse and contain variation within; each patient harbors sub-clones of malignant cells that, in principle, respond differently to treatment.

Orac, the fictional supercomputer (Wiki-Commons image)

Putting these links together –

The message from Katherine O’Brien, who lives with MBC and blogs about it, is that one outlier – like Katherine Russell Rich — can provide hope to other patients and, maybe, clues for scientists about why she lived for so long with metastatic BC. The message from Orac, a physician-scientist blogger, is how hard it is to pinpoint an individual breast tumor’s molecular aspects, because the disease is so mutable and diverse.

The problem, and this reflects evolution in my thinking over a long while, is that published data — the gold standard, what supports EBM — are largely limited to findings based on trials of groups. We understand now, better than we did 10 or 20 years ago, that each patient’s tumor is unique and can evolve over time, naturally or in response to therapy. Clinical trials, though rigorously planned and elaborately structured, are incredibly expensive and flip-floppy, disappointing overall.

What I’m thinking -

Algorithms – except in the broadest sense – may not offer the optimal approach to cancer treatment. Maybe the median doesn’t matter so much as we’d thought.

Here’s a ~retro idea: In 2012, maybe the ideal and most cost-effective oncology practice would blend low-tech observations — like findings on physical examination and how the patient’s feeling — with occasional, high-tech analyses — like markers for genetic drift within a tumor. If doctors are well-trained and non-robotic, in either the literal or figurative sense, and if they lack COIs regarding treatment decisions, they’d provide better, more effective and personalized treatments than what’s typically offered based on evidence reached through elaborate, costly clinical trials of many patients with similar but non-identical cancers.

All for now,

ES

–

First, we need it. The U.S. health care system doesn’t work. It doesn’t serve doctors. Good physicians are few and far between in some geographical regions, in primary care and in needed specialties (like oncology and geriatrics). It doesn’t serve people who might be patients, except if they happen to work for a generous employer that offers a good plan (few do), they are rich enough so they might spend thousands each year out-of-pocket and out-of-network, or they are most fortunate of all, having no serious medical problems to contend with or pay for.

Second, although I wholeheartedly support the Affordable Care Act, because it’s a step in the right direction, I don’t think the legislation goes far enough. We need a simpler, single-payer solution, as in a national health care program, Medicare-style, for all. Why? Because the quasi-plan for state-based exchanges, each with competing offerings and not necessarily interpretable terms of coverage, is too complicated. There’s no reason to think a free market operating at the state level would match the public’s or many individuals’ medical needs. As long as each provider is trying to make a buck, or a billion, it won’t put patients’ access to good care first. Besides, there’ll be administrative costs embedded in each exchange that we could live better without. As for private insurers, well, I couldn’t care less about the well-being of those companies or their executives’ incomes.

Profit is not what medical care is about, or should be about. What we need is a simple, national health plan, Europe-style, available to everyone, with minimal paperwork and, yes, limits to care.

Third point – on rationing.

Some of my readers may wonder how I, who support some costly components of good medical care, like providing breast cancer screening for middle-aged women and sometimes giving expensive drugs to people with illness, favor health care reform. New cancer meds cost around $100,000 year, more or less, as do innovative treatments for cystic fibrosis, inflammatory bowel disease, rheumatoid arthritis and other conditions. I don’t think the sane solution is abandoning expensive but life-saving and quality-of-life-improving treatments.

The hardest part of this debate and what’s so rarely discussed is the appropriate limits of medical treatment, not based on costs — which we can certainly afford if we pull back on administrative expenses of health care and insurers’ huge profits - but on factors like prognosis and age. So, for example, maybe a 45 year old man should get a liver transplant ahead of an 80 year old man. Screening for breast cancer, if it is valuable as I think it is, should perhaps be limited to younger women, maybe those less than 70 or 75, based on the potential for life-years saved. Maybe we shouldn’t assign ICU beds to individuals who are over 85, or 95, or 100 years old.

The real issue in HCR, if you ask me, is who would decide on these kinds of questions. That conversation’s barely begun, and I would like to participate in that…

Meanwhile, the Supreme Court is busy doing its thing, sorting out whether the Affordable Care Act is constitutional or not. I’m glad they’re on the case, so that they might find that it stands and we can move on and forward.

#Obamacare is right -

—

The idea is that people who use health care would each be assigned a universal patient identifier, or UPI. This unique number would link to a person’s health records. In principle it would facilitate transfer of a patient’s medical history between doctors, hospitals and, likely, insurance companies. There are arguments pro – mainly having to do with efficiency and patient safety; and against – mainly having to do with privacy.

My issue is that it reminds me of Auschwitz. But apart from that particular association, labeling people with numbers seems dehumanizing — what’s already a big negative in modern health care. I/we need to realize that already we have numbers. Most people have social security numbers. I have several hospital ID numbers and insurance company numbers.

As for privacy, that’s history, or an illusion. If someone wants to know something about almost any person here in the U.S, they can find it. We inhabit a grid.

The debate reminds me of when I was an oncology fellow, and I treated a woman from Central America who had breast cancer. After she underwent a biopsy at our hospital, I reviewed the slides with the pathologist and wrote orders and injected her with chemotherapy. For 15 years or so I followed her in the clinic, and at some point, maybe 5 years after her diagnosis, she told me that her name was not what I’d thought or what her chart said it was. She’d used a cousin’s name and insurance card to get the care she needed.

More recently, I was with a relative who had an MRI. Upon registering at the radiology facility, he had to show a state-issued picture ID besides his insurance card. The issue was clear: with some 50 million or so Americans uninsured, and others without the ready means to cover co-pays, some people are assuming other patients’ identities to get the care they want or need.

The costs to insurers and hospitals of patient identity fraud — what in some instances I might liken to a hungry person stealing a loaf of bread – may underlie this topic’s appearance in the WSJ.

–

She took my blood pressure with a cuff that made my germ-phobic self run for self-regulation, i.e. I stayed quiet and didn’t express my concern about the fact that it looked like it hadn’t been washed in years. I value this doctor among others in my care, and I didn’t want to complain about anything. Then the woman took my weight. And then she asked if she could take my picture, “for the hospital record.”

I couldn’t contain my wondering self. “What is the purpose of the picture?” I asked.

“It’s for the record,” she explained. “For security.”

I thought about it. My picture is pretty much public domain at this point in my life, a decision I made upon deciding not to blog anonymously. Besides, most everyone at the medical center used to know me, including the receptionists, janitors, cafeteria cashiers, nurses’ aides, social workers, deans, full professors, geneticists, fellows in surgery and old-time voluntary physicians, among others who work there. So why didn’t I want this unidentified woman who works in my oncologist’s office to take my picture?

It made me uncomfortable, and here’s the reason: My picture is a reminder that, without it, I might be like any other patient in the system. They (administrators?, nurses, other docs, maybe even my future doctors) will need or want the picture to recall and be certain who Elaine Schattner is.

Don’t get me wrong. I agreed to the photo after all of maybe 20 seconds deliberating. (And my doctor was, I soon learned, duly informed I’d “had an issue” with it. Was that for just asking the reason?) The unidentified med-tech person used an oddly small, ordinary pink camera to complete her task.

When I met with my doctor, she explained that the photo is for security and, essentially, to reduce the likelihood of errors. The hospital has records of so many thousands of patients, many who have similar or identical names. There are good reasons to make sure that your notes on “Sally Smith” are entered into the chart of “Sally Smith” who is your patient.

It’s understandable. I remember when at the nurses’ station there’d be a sign (on “our” side) saying something like “CAREFUL: Anna Gonzalez in 202, Alma Gonzalez in 204b,” or something like that.

Patients blur.

It’s hard, veritably impossible, for most doctors and nurses to keep mental track of all of the patients they’ve ever seen and examined. There’s utility in the new system. Yes, it’s a good idea for a doctor, say upon receiving a call from a woman she hasn’t seen in 3 or 6 or 9 years, to see her picture in the chart, as a reminder.

But I hope my doctors know who I am, and not just what I look like in the image.

–

The Office Med School Edition

—

The clip is a parody of The Office about Problem Based Learning (PBL).

In a typical PBL, the students meet regularly in small groups. On Monday they begin with clinical aspects of a case. The process involves finding information and researching relevant topics to “solve” the diagnosis and /or a treatment dilemma. Over the course of each week the students move forward, working through a hypothetical patient’s history, physical exam and lab studies to the nitty-gritty of molecules, genes and cells implicated in a disease process.

It’s a lot of fun, usually.

The video was uploaded in February, 2007. It’s attributed to a group of med students at the University of Pittsburgh, class of 2009.

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