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Cardiovascular Medicine, Events, Patient Care, Stanford News

Honoring doctors, nurses of the early days of Stanford’s coronary care unit

Honoring doctors, nurses of the early days of Stanford’s coronary care unit

image.img.320.highWhen I was in the hospital recently to give birth to my daughter, I saw my doctors briefly during their rounds, but it was the nurses and nurse midwives who primarily cared for me. So when I read in a recent Inside Stanford Medicine feature story that 50 years ago, nurses weren’t even allowed to perform tasks like start IVs, I was shocked.

In the 1960s, Stanford was home to one of the earliest coronary care units, led by Alfred Spivack, MD. Spivack taught the nurses working on the unit to take on tasks that were, at the time, mainly done by physicians. Joan Fair, PhD, RN, who was one of the unit’s original nurses and is now a cardiovascular researcher, recalls:

“Some doctors were totally against nurses doing these kinds of things… It also took time for some doctors to accept our opinions about how their patients were doing, or if we saw a problem and called them and asked them to take a different line of treatment.”

Joan Mersch, MSN, the unit’s former nurse coordinator, described in the piece how beneficial this extra training was to patients. “When you know how to read electrocardiograms, recognize lethal cardiac rhythms, perform resuscitation and defibrillation — it saves patient lives,” she said. “You understand what needs to be done, and you can take action.”

A big proponent of using technology to improve care, Spivack depended on the nurses to learn how to use the devices and incorporate them in the daily care of patients. And he also encouraged the nurses to pursue their research interests; many, like Fair, went on to obtain graduate degrees.

Last month, almost two dozen former nurses from the unit came together for a dinner celebrating a major gift from Spivack, which will pay for the nurses’ station in the new heart acute care unit when the new adult hospital opens in 2018.

Photo by Steve Fisch

Big data, BigDataMed15, Events, Medicine and Society, Microbiology, Research, Technology

At Big Data in Biomedicine, Nobel laureate Michael Levitt and others talk computing and crowdsourcing

At Big Data in Biomedicine, Nobel laureate Michael Levitt and others talk computing and crowdsourcing

Levitt2Nobel laureate Michael Levitt, PhD, has been using big data since before data was big. A professor of structural biology at Stanford, Levitt’s simulations of protein structure and movement have tapped the most computing power he could access in his decades-long career.

Despite massive advances in technology, key challenges remain when using data to answer fundamental biological questions, Levitt told attendees of the second day of the Big Data in Biomedicine conference. It’s hard to translate gigabytes of data capturing a specific biological problem into a form that appeals to non-scientists. And even today’s supercomputers lack the ability to process information on the behavior of all atoms on Earth, Levitt pointed out.

Levitt’s address followed a panel discussion on computation and crowdsourcing, featuring computer-science specialists who are developing new ways to use computers to tackle biomedical challenges.

Kunle Olukotun, PhD, a Stanford professor of electrical engineering and computer science, had advice for biomedical scientists: Don’t waste your time on in-depth programming. Instead, harness the power of a domain specific language tailored to allow you to pursue your research goals efficiently.

Panelists Rhiju Das, PhD, assistant professor of biochemistry at Stanford, and Matthew Might, PhD, an associate professor of computer science at the University of Utah, have turned to the power of the crowd to solve problems. Das uses crowdsourcing to answer a universal problem (folding of RNA) and Might has used the crowd for a personal problem (his son’s rare genetic illness).

For Das, an online game called Eterna – and its players – have helped his team develop an algorithm that much more accurately predicts whether a sequence of RNA will fold correctly or not, a key step in developing treatments for diseases that use RNA such as HIV.

And for Might, crowdsourcing helped him discover other children who, like his son Bertrand, have an impaired NGLY1 gene. (His story is told in this New Yorker article.)

Panelist Eric Dishman, general manager of the Health and Life Sciences Group at Intel Corporation, offered conference attendees a reminder: Behind the technology lies a human. Heart rates, blood pressure and other biomarkers aren’t the only trends worth monitoring using technology, he said.

Behavioral traits also offer key insights into health, he explained. For example, his team has used location trackers to see which rooms elderly people spend time in. When there are too many breaks in the bathroom, or the person spends most of the day in the bedroom, health-care workers can see something is off, he said.

Action from the rest of the conference, which concludes today, is available via live-streaming and this app. You can also follow conversation on Twitter by using the hashtag #bigdatamed.

Previously: On the move: Big Data in Biomedicine goes mobile with discussion on mHealthGamers: The new face of scientific research?, Half-century climb in computer’s competence colloquially captured by Nobelist Michael Levitt and Decoding proteins using your very own super computer
Photo of Michael Levitt by Saul Bromberger

Events, Mental Health, Sexual Health, Stanford News, Women's Health

Women’s health experts tackle mood disorders and sexual assault

Women's health experts tackle mood disorders and sexual assault

3131235412_fa7f528735_zEarlier this week I reported from the Women’s Health Forum, held on Monday for the sixth year running. The hardest part about attending the event was deciding which among all the interesting talks to attend.

Among the many sessions, the two that most piqued my interest focused on women’s mental health. Katherine (Ellie) Williams, MD, spoke about mood disorders related to the menstrual cycle, and Laraine Zappert, PhD, discussed the psychological impact of sexual assault. Both are from the school’s Department of Psychiatry and Behavioral Sciences.

Williams’ talk began with a cartoon of a dishwasher bursting with dishes, clothes, a phone, a vacuum – above a caption quip about PMS. The out-of-control energy of the sketch conveys the affective thundercloud often associated with women and their “hormones.” Williams identified three periods when this thundercloud may be an actual mood disorder, as opposed to “normal” fluctuations: pre-menstrual, perinatal, and perimenopausal.

Technically speaking, “PMS” is about physical symptoms and is fairly common, whereas pre-menstrual dysphoric disorders (PMDDs) is all about mood and affects less than 5 percent of women. The disruption happens in the luteal phase of a woman’s cycle, usually the two weeks after ovulation – this is a big chunk of time we’re talking about, nearly 50 percent! Treatments for disorders in all periods include exercise, acupuncture, and diet supplements, and pharmaceuticals like certain birth control pills and antidepressants (which interestingly work differently for women with PMDD than for people in general – when taken only during that luteal phase, they have fast onset time and cause no withdrawal symptoms).

Researchers are learning more about how to predict and prevent cycle-related mood disorders, and increasingly it is clear that life context plays a major role. Stressful life events, interpersonal conflicts, marital tension, and previous mental-health instabilities (from being a perfectionist to having suffered childhood abuse or major depressive breakdowns) are the primary risk factors. This knowledge means clinical practitioners have to think much more broadly about how to help women, particularly in terms of prevention, Williams said.

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Big data, BigDataMed15, Events, Patient Care, Research, Stanford News, Technology

Experts at Big Data in Biomedicine: Bigger, better datasets and technology will benefit patients

Experts at Big Data in Biomedicine: Bigger, better datasets and technology will benefit patients

population health panelThe explosion of big data is transforming the way those in health care are diagnosing, treating and preventing disease, panelists at the Big Data in Biomedicine said on its opening day.

During a five-member panel on population health, experts outlined work that is currently being done but said even bigger datasets and better technology are needed to ramp up the benefits from digital data and to save lives.

“Using the end-of-millions to inform care for the end-of-one – that is exactly where we’re going,” said Tracy Lieu, MD, MPH, director of research at Kaiser Permanente Northern California, a health-care network that includes 21 hospitals, 8,000 physicians and 3.6 million patients. “And we think that in a population like ours, in an integrated system like ours, we are in an ideal setting to do personalized medicine.”

Stanford Medicine professor Douglas Owens, MD, director of the Center for Health Policy and Center for Primary and Outcomes Research, led the panel on Wednesday. He said that big data is also changing how research is being conducted.

“There’s been an explosion of data of all kinds: clinical data, genomics data, data about what we do and how we live,” said Owens. “And the question is how can we best use that data to improve the health of the individual and to improve the health of populations.”

Lieu said two key trends are central to medical researchers: informatics and genomics. She told attendees that Kaiser utilizes a “virtual data warehouse” with the digital data of 14 million patients dating back to 1960. But Lieu cautioned that the data are not always the means to an end, particularly if the findings are not tested and implemented.

“Sometimes we fail. And we fail when we identify a problem of interest, we make a decision to study it, we assemble the data, we analyze and interpret the results – and then we send them off to journals. So we fail to close the loop,” she said, because researchers typically don’t go beyond the publication of data.

Lieu said Kaiser is now focused on trying to close that loop. “To do that, we need the kinds of tools that you in this group and the speakers at this conference are developing,” she explained. “We need better and better technology for rapidly analyzing and aggregating data.”

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Events, Stanford News

Stanford Medicine’s Health Matters event, in pictures

Stanford Medicine's Health Matters event, in pictures

Last weekend’s Health Matters, an annual event, drew more than 750 people to the Stanford Medicine campus. Along with hearing about the latest medical and health advances, participants were offered the chance to talk one-on-one with some of our experts and to participate in a dizzying array of hands-on activities.

For those of you who missed out (and even those who didn’t), save the date for next year’s event: May 14, 2016.

Previously: Stanford’s Health Matters happening on Saturday
Photos by CM Howard Photography

Big data, BigDataMed15, Events, Medicine and Society, Research, Technology

On the move: Big Data in Biomedicine goes mobile with discussion on mHealth

On the move: Big Data in Biomedicine goes mobile with discussion on mHealth

17910585102_33293fefe7_zIda Sim, MD, PhD, would like to prescribe data as easily as she orders a blood test or a prescription for antibiotics. Sim, a professor of medicine at the University of California-San Francisco, told attendees of a Big Data in Biomedicine panel on mHealth yesterday afternoon that she doesn’t want access to data collected willy-nilly, with little regard for the patient’s health condition or needs.

Instead, she wants to tailor data collection to the individual patient. For example, there’s no need to collect activity data for a competitive marathoner, but it would be useful for a sedentary computer programmer.

And she doesn’t care how patients collect their data; they can “bring their own device,” Sim, who also co-directs of biomedical informatics at the UCSF Clinical and Translational Sciences Institute, said.

The design of those devices is integral to the quality of the data developed, pointed out panelist Ram Fish, vice president of digital health at Samsung. He said his team starts with “small data,” making sure devices such as their Simband watch accurately records biomarkers such as blood pressure or heart rate in a single individual, before expanding it to the population level.

He said he’s most keen on developing tools that make a real difference in health, such as the detection of abnormal heart rhythms, a project still in the works.

And speaking of new tools, Stanford’s Euan Ashley, MD, PhD, associate professor of medicine and of genetics, shared some early results from the cardiovascular app MyHeart Counts, which Stanford introduced in March to great acclaim.

Ashley reported that the study has yielded information about the link between sleep patterns and happiness (those who go to bed late and get up late are less happy than others) and about geographic patterns of produce consumption (South Dakota users out-eat Californians when it comes to fruits and veggies). The project’s team is just starting to delve into some of its other findings, which include correlations between the 6-minute timed walk and overall health.

“We’re in a really new era and one we don’t really understand,” Ashley said.

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Big data, BigDataMed15, Events, Genetics, Research, Technology

Big Data in Biomedicine panelists: Genomics’ future is bright, thanks to data-science tools

Big Data in Biomedicine panelists: Genomics' future is bright, thanks to data-science tools

Jill HagenkordStanford’s annual Big Data in Biomedicine began this morning with a “breathtaking set of talks,” as described by Russ Altman, MD, PhD, a Stanford professor of bioengineering, genetics and of medicine.

The first panel focused on genomics, with the speakers presenting a dizzying forecast of a future where biomedical data is standardized and easily accessible to researchers, yet carefully guarded to protect privacy.

“How do we build this in a way that allows you to spend time working on your science, and not spend your time to worry about reinventing the plumbing?,” asked David Glazer, director of engineering at Google and a speaker on the panel.

His team is hard at work ensuring the infrastructure of the Google Cloud Platform can withstand the rigorous demands of a slew of big data projects, including the Million Veteran Program and MSSNG, an effort to understand the genetics of autism.

For panelist Heidi Rehm, PhD, associate professor of pathology at Harvard Medical School and director of the Partners Laboratory for Molecular Medicine, a key hurdle is standardizing definitions and ensuring that supporting evidence is available for system users. For example, data developers should be able to demonstrate why a particular gene variant has been deemed benign, and what definition of “benign” they are using, she said.

Her team has developed a star system, which rates sources of data by their credibility, giving results submitted by expert panels more stars than data submitted by a single researcher.

Rehm also addressed the pros and cons of various models to share data. Rather than collecting it all centrally, she said she expects data will be shared through a small number of hubs, which each have the ability to connect with each other, similar to an airline trafficking model.

Individuals are not standing in the way of research advances, reported panelist Jill Hagenkord, MD, chief medical officer of the personal genetics company 23andMe. She said that of their 950,000 customers, nearly 80 percent have agreed to share their data for research. Participants are also eager to provide additional information when asked, Hagenkord said. It becomes almost a philanthropic effort, they feel grateful that someone is interested in their conditions, she said.

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Behavioral Science, Complementary Medicine, Events, Medical Education, Stanford News

Advice for young docs from psychiatrist David Spiegel: Find a mentor and pursue your passion

Spiegel in office - smallThe takeaway from Stanford David Spiegel‘s recent lunchtime discussion, part of the Psychiatry and Behavioral Science Grand Rounds, was simple: You can’t make it on your own; accept, welcome and offer assistance. To succeed as an academic psychiatrist, it isn’t necessary to come from a line of psychiatrists, as Spiegel, MD, does, he said.

But junior physicians do need mentors, those who know the formal and informal rules of the system and who are willing to make time and lend a hand, a practice Spiegel attributed to his mentor, Irvin Yalom, emeritus professor of psychiatry and behavioral sciences.

Spiegel said that early in his career, he would initially get discouraged when papers or grants would be rejected. Then, he came across a statistic that few hockey players make it out of their first year in the National Hockey League with all of their teeth. It was an “a-ha” moment for the second-generation psychiatrist (Spiegel’s parents were both psychiatrists). Despite hard work, even the best scientists encounter challenges and adversity.

Now, Spiegel is the Jack, Lulu and Sam Willson Professor and a professor of psychiatry and behavioral sciences. He directs the Stanford Center on Stress and Health and is also medical director for the Stanford Center for Integrative Medicine.

Spiegel offered additional advice to the 80-or-so people who gathered to hear him: Disregard convention and explore your interests. “You will do your best work if you’re doing something you’re passionate about,” he said.

Despite the prevalence of psychotherapy, and then of community psychiatry, Spiegel said he stuck by his interest in hypnosis, despite its poor reputation. By conducting statistically sound studies, he developed a body of work demonstrating that hypnosis has real, replicable benefits. This work stood up to critical skeptics and helped secure his tenured position at Stanford, Spiegel said.

Stanford then, and now, has accepted work that expands the bounds of disciplines, as long as it stands up to scientific scrutiny, Spiegel said. “Do whatever the hell you want to do, but be scientific and empirical about it. If you can demonstrate it works, fine,” Spiegel said. He concluded with this parting phrase: “Data rocks!”

Previously: “Tranceformation:” David Spiegel on how hypnosis can change your brain’s perception of your body, Starting a new career in academic medicine? Here’s a bible for the bedside: The Academic Medicine Handbook, Exploring the science of hypnosis with Stanford’s David Spiegel and Stanford psychiatrist David Spiegel’s path west
Photo by L.A. Cicero

Events, Health and Fitness, Nutrition, Obesity, Stanford News, Women's Health

Women’s health expert: When it comes to prevention, diet and exercise are key

Women's health expert: When it comes to prevention, diet and exercise are key

16262076932_96f8309b43_zThis Monday was the sixth annual Stanford Women’s Health Forum, hosted by Stanford’s Women and Sex Differences in Medicine center (WSDM), and I was happy to have been present for the lively talks. The forum focused on prevention, and the keynote, delivered by Marcia Stefanick, PhD, professor of obstetrics and gynecology and WSDM director, highlighted physical activity and weight management as the key preventative actions for women to take.

High blood pressure remains the number one preventable cause of death in women, with physical inactivity and high BMI, both of which contribute to high blood pressure, in third and fourth place. (For the curious readers, smoking comes in second.) Because prevention requires changes in behavior, behavior was what Stefanick focused on. Rather than reinforcing many women’s feelings of embarrassment about their weight, she said, providers should help women feel that they can do something about it.

Healthier behaviors must include diet and exercise. Both fatness and low fitness cause higher mortality; realistic expectations about how to change both should factor into care. Stefanick emphasized that weight loss should be slow: 10 percent of one’s body weight baseline over six months, or one pound per week for moderately overweight people, and no more than two pounds per week. And we need to stop being so sedentary, Stefanick exclaimed. The classic principles of exercise apply – gradually increase the frequency, intensity, and/or duration of exertion. Adults should be getting at least two and a half hours of moderate-intensity aerobic physical activity per week, in addition to doing muscle-strengthening activities at least twice a week, the conference flyer read.

However, citing the problems of eating disorders and older women losing weight without trying, Stefanick stressed that “weight management is a spectrum; there are extremes at both ends.” In describing variations on mesomorphic, endomorphic, and ectomorphic body types, she stated that “we don’t know what the optimal body type is.” It probably varies for each person.

Something I found particularly interesting was Stefanick’s description of gynoid vs android fat distribution patterns (which I learned as “pear” and “apple” body shapes, respectively). Gynoid distribution around the hips, thighs, and butt is more common in women, and includes more subcutaneous fat, while in android distribution, which is more common in men, fat collects around the belly and chest and is actually dispersed among the organs. Such intra-abdominal fat is more damaging to health, as it affects the liver and lipid profile and can cause heart disease, but it’s also much easier to get rid of through exercise (which is one reason men overall have less trouble losing weight than women).

In the spirit of more personalized care, Stefanick also discussed how recommended weight changes during pregnancy should vary according to the person’s prenatal BMI. Someone underweight could gain up to 40 pounds and be healthy, she pointed out, while obese people might actually lose weight during pregnancy for optimal mother-baby health.

Previously: Why it’s critical to study the impact of gender differences on diseases and treatmentsWhen it comes to weight loss, maintaining a diet is more important than diet typeApple- or pear-shaped: Which is better for cancer prevention?A call to advance research on women’s health issues and To meet weight loss goals, start exercise and healthy eating programs at the same time
Photo by Mikaku

Big data, BigDataMed15, Events, Public Health, Research

Big Data in Biomedicine conference kicks off today

Big Data in Biomedicine conference kicks off today

14243103692_67ec6354f0_zThe third annual Big Data in Biomedicine conference kicks off today on the Stanford campus. The three-day event brings together thought leaders from academia, information technology companies, venture capital firms and public health institutions to explore opportunities for extracting knowledge from the rapidly growing reservoirs of health and medical information to transform how we diagnose, treat and prevent disease.

The year’s program will cover the intersection of disciplines as widespread as genomics, population health, neuroimaging and immunology; it will also touch on crowdsourcing, ethical and legal issues and “learning” health systems. Delivering the opening keynote will be Sharon Terry, president and CEO of Genetic Alliance. Other keynote speakers include Kathy Hudson, PhD, deputy director for science, outreach and policy at the National Institutes of Health; France Córdova, PhD, director of the National Science Foundation; Michael Levitt, PhD, professor of structural biology at Stanford and recipient of the 2013 Nobel Prize in Chemistry; and Lloyd Minor, MD, dean of Stanford’s School of Medicine.

Those unable to attend in person can tune in to the live webcast via the conference website. We’ll also be live tweeting the keynote talks and other proceedings from the conference; you can follow the coverage on the @StanfordMed feed or by using the hashtag #bigdatamed.

Previously: Countdown to Big Data in Biomedicine: Leveraging big data technology to advance genomics, Countdown to Big Data in Biomedicine: Mining medical records to identify patterns in public health and Harnessing mobile health technologies to transform human health
Photo from the 2014 Big Data in Biomedicine conference by Saul Bromberger

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