Archive for the ‘Uncategorized’ Category

New Medicine/Old Medicine

Sunday, January 15, 2017 // Uncategorized

I haven’t blogged for awhile.  I haven’t been inspired.  Now I have just finished my  notes for Friday. It was a busy day and I left the office before I had finished all my documentation.  That happens often.  I get home and I spend another hour finishing notes.  This is the way it is with many doctors.  We want the record to reflect something of the patient encounter.  Too often, it is just documenting for reimbursement.  It’s about checking all the boxes necessary to meet certain core measures.  This article in The Annals of Internal Medicine’s section On Being a Doctor  captured the sense of  an older physician’s struggle to take care of patients while  teaching what medicine used to be like.

On Being a Doctor |6 December 2016

Coeur d’Alene

0 Comments Read more
 

Flu Shot Today? Later May Be Better Than Sooner

Sunday, September 18, 2016 // Uncategorized

This article is from Kaiser Health News.  It also was mentioned on NPR and The Rivard Report.  We’re still waiting on our quadrivalent vaccine to come in.  The pharmacies are 600 pound gorillas and get theirs first.  As this article mentions, it is best not to rush out and get it.

The Ads Say ‘Get Your Flu Shot Today,’ But It May Be Wiser To Wait

September 15, 2016


flu shot sign

The pharmacy chain pitches started in August: Come in and get your flu shot.

Convenience is touted. So are incentives: CVS offers a 20-percent-off shopping pass for everyone who gets a shot, while Walgreens donates toward international vaccination efforts.

The start of flu season is still weeks — if not months — away. Yet marketing of the vaccine has become an almost year-round effort, beginning when the shots become available in August and hyped as long as the supply lasts, often into April or May.

Not that long ago, most flu-shot campaigns started as the leaves began to turn in October. But the rise of retail medical clinics inside drug stores over the past decade — and state laws allowing pharmacists to give vaccinations — has stretched the flu-shot season.

The stores have figured out how “to deliver medical services in an on-demand way” which appeals to customers, particularly millennials, said Tom Charland, founder and CEO of Merchant Medicine, which tracks the walk-in clinic industry. “It’s a way to get people into the store to buy other things.”

But some experts say the marketing may be overtaking medical wisdom since it’s unclear how long the immunity imparted by the vaccine lasts, particularly in older people.

Federal health officials say it’s better to get the shot whenever you can. An early flu shot is better than no flu shot at all. But the science is mixed when it comes to how long a flu shot promoted and given during the waning days of summer will provide optimal protection, especially because flu season generally peaks in mid-winter or beyond. Experts are divided on how patients should respond to such offers.

“If you’re over 65, don’t get the flu vaccine in September. Or August. It’s a marketing scheme,” said Laura Haynes, an immunologist at the University of Connecticut Center on Aging.

That’s because a combination of factors makes it more difficult for the immune systems of people older than age 65 to respond to the vaccination in the first place. And its protective effects may wear off faster for this age group than it does for young people.

When is the best time to vaccinate? It’s a question even doctors have.

“Should I wait until October or November to vaccinate my elderly or medically frail patients?” That’s one of the queries on the website of the board that advises the Centers for Disease Control and Prevention on immunizations. The answer is that it is safe to make the shots available to all age groups when the vaccine becomes available, although it does include a caution.

The board says antibodies created by the vaccine decline in the months following vaccination “primarily affecting persons age 65 and older,” citing a study done during the 2011-2012 flu season. Still, while “delaying vaccination might permit greater immunity later in the season,” the CDC notes that “deferral could result in missed opportunities to vaccinate.”

How long will the immunity last?

“The data are very mixed,” said John J. Treanor, a vaccine expert at the University of Rochester medical school. Some studies suggest vaccines lose some protectiveness during the course of a single flu season. Flu activity generally starts in the fall, but peaks in January or February and can run into the spring.

“So some might worry that if [they] got vaccinated very early and flu didn’t show up until very late, it might not work as well,” he said.

But other studies “show you still have protection from the shot you got last year if it’s a year when the strains didn’t change,” Treanor said.

In any given flu season, vaccine effectiveness varies. One factor is how well the vaccines match the virus that is actually prevalent. Other factors influencing effectiveness include the age and general health of the recipient. In the overall population, the CDC says studies show vaccines can reduce the risk of flu by about 50 to 60 percent when the vaccines are well matched.

Health officials say it’s especially important to vaccinate children because they often spread the disease, are better able to develop antibodies from the vaccines and, if they don’t get sick, they won’t expose grandma and grandpa. While most people who get the flu recover, it is a serious disease responsible for many deaths each year, particularly among older adults and young children. Influenza’s intensity varies annually, with the CDC saying deaths associated with the flu have ranged from about 3,300 a year to 49,000 during the past 31 seasons.

To develop vaccines, manufacturers and scientists study what’s circulating in the Southern Hemisphere during its winter, which is our summer. Then — based on that evidence — forecast what flu strains might circulate here to make vaccines that are generally delivered in late July.

For the upcoming season, the vaccines will include three or four strains, including two A strains, an H1N1 and an H3N2, as well as one or two B strains, according to the CDC. It recommends that everyone older than 6 months get vaccinated, unless they have health conditions that would prevent it.

The vaccines can’t give a person the flu because the virus is killed before it’s included in the shot. This year, the nasal vaccine is not recommended for use, as studies showed it was not effective during several of the past flu seasons.

But when to go?

“The ideal time is between Halloween and Thanksgiving,” said Haynes at UConn. “If you can’t wait and the only chance is to get it in September, then go ahead and get it. It’s best to get it early rather than not at all.”

0 Comments Read more
 

Fats, Fat and Death

Sunday, July 24, 2016 // Uncategorized

Here are a couple of recent articles dealing with the type of a fat in the diet and mortality and obesity and mortality.

Being Modestly Overweight Linked to Increased All-Cause Mortality Risk

By Amy Orciari Herman

Edited by Susan Sadoughi, MD, and Richard Saitz, MD, MPH, FACP, FASAM

Being even modestly overweight is associated with increased mortality risk, according to a large meta-analysis in the Lancet. The finding calls into question prior research suggesting that a slightly elevated body-mass index might be protective.

Researchers examined individual participant data from 189 studies comprising nearly four million adults who had never smoked, had no known chronic conditions at baseline, and survived beyond 5 years of follow-up. Participants were from North America, Europe, Australia, and East Asia.

Overall, roughly 386,000 participants died. All-cause mortality was lowest at a BMI of 20.0–24.9 (normal weight) and then increased significantly and linearly beginning at a BMI of 25.0–27.4 (hazard ratio, 1.07). BMIs below 20.0 also posed increased risk. The findings were consistent across geographic regions, and associations between higher BMIs and mortality were greater in younger than older participants and in men than in women.

The authors write, “These findings suggest that if the overweight and obese population had WHO-defined normal levels of BMI, the proportion of premature deaths that could be avoided would be about one in five in North America.”

Dr. Harlan Krumholz of NEJM Journal Watch Cardiology commented: “What I really want to know is not average risk, but who has the most risk, if any, among those who are modestly overweight. Meanwhile, as a physician, my greatest emphasis regarding weight loss will remain on those with marked elevation of BMI, those with the highest risk.”

0 Comments Read more
 

Overuse of Antibiotics

Thursday, May 5, 2016 // Uncategorized

Antibiotics are often prescribed for upper respiratory tract infections inappropriately.  According to the most recent study, 1/3 of antibiotics are prescribed inappropriately.  Overuse of antibiotics leads to resistance of bacteria.  Here is a summary of a recent JAMA article from Physicians First Watch.  Following that is the American College of Physicians informational page for patients on appropriate antibiotic use.

May 5, 2016 Population-Based Estimates of Appropriate and Inappropriate Antibiotic Prescribing Thomas L. Schwenk, MD reviewing Fleming-Dutra KE et al. JAMA 2016 May 3. Tamma PD and Cosgrove SE. JAMA 2016 May 3. Thomas L. Schwenk, MDThe U.S. annual antibiotic prescribing rate in 2010 was about 500 prescriptions per 1000 people; one third of prescriptions were judged to be inappropriate. Thomas L. Schwenk, MDResearch about inappropriate antibiotic prescribing usually focuses on specific conditions and age groups. However, these researchers used several national ambulatory care databases to provide overall population-based estimates that could guide government and professional mandates designed to reduce inappropriate antibiotic prescribing.Researchers assessed appropriateness of antibiotic use in about 184,000 ambulatory visits (not including urgent care centers, “minute” clinics, federal facilities, or long-term care facilities) in 2010 and 2011 using accepted clinical practice guidelines. If guidelines were not available (e.g., for sinusitis), the lowest regional level of antibiotic use was used as a surrogate for appropriateness (almost certainly still an overestimate). For some conditions (e.g., pneumonia), all antibiotic use was deemed to be appropriate.The overall annual rate of antibiotic use was 506 prescriptions per 1000 people, of which roughly two thirds of prescriptions (353 prescriptions/1000 people) were deemed to be appropriate. The overall rate ranged from 423 to 553 prescriptions per 1000 people in the West and South, respectively. Most inappropriate antibiotic use was for acute respiratory conditions (111 prescriptions/1000 people annually).Comment – See more at: http://www.jwatch.org/na41220/2016/05/05/population-based-estimates-appropriate-and-inappropriate#sthash.I2fvkBOG.dpuf

Appropriate Antibiotic Use for Acute Respiratory Tract Infection in Adults: Advice for High-Value Care From the American College of Physicians and the Centers for Disease Control and Prevention

 What are acute respiratory tract infections?

Acute respiratory tract infections (ARTIs) are common in adults. ARTIs include bronchitis, sinus infections, sore throat, and the common cold. Most are caused by a virus, not by bacteria.

What are harms related to antibiotic use?

Antibiotics are medicines used to treat illnesses that are caused by bacteria, such as strep throat (medical name: group A streptococcal pharyngitis) or pneumonia. Antibiotics will not work for illnesses caused by viruses, such as the common cold. Antibiotics can cause harm when they are not used the right way. These harms can include:

Side effects: These can be mild, such as upset stomach, diarrhea, or skin rash. However, in some cases they can be very serious and even life-threatening.

High costs: Prescriptions that are not needed increase patients’ out-of-pocket costs. It is estimated that 50% of antibiotic prescriptions are not needed, totaling more than $3 billion in wasted spending.

Antibiotic resistance: When antibiotics are used when they are not needed, germs and bacteria can become resistant to them. This means that common antibiotics will not be able to treat certain illnesses. Antibiotic-resistant bacteria cause more serious illnesses that are harder to cure and can be life-threatening.

Why are so many people prescribed antibiotics when they are not needed?

Because antibiotics have often been used when not needed, many patients expect to receive antibiotics for ARTIs and believe that they need them to feel better. In other cases, clinicians may prescribe antibiotics right away, rather than waiting or testing to see if they are needed.

How did the ACP develop this advice?

The authors looked at research and clinical guidelines related to antibiotic use for ARTIs. This information was used to develop advice for clinicians and patients.

What does the ACP recommend that patients and physicians do?

Reducing unneeded antibiotic prescribing will improve care, lower costs, and help to stop antibiotic resistance. In most patients, symptoms get better in 1 to 2 weeks. Coughs can sometimes last up to 6 weeks. The ACP recommends the following:

•Clinicians should not prescribe antibiotics for patients with bronchitis. Antibiotics should only be used if patients have pneumonia.

•Clinicians should test patients with symptoms that could be strep throat. Because symptoms alone are not reliable, antibiotics should only be prescribed when testing confirms strep throat. Other sore throat infections do not need antibiotics.

•Clinicians should not prescribe antibiotics for sinus infections unless patients have severe symptoms or symptoms that last more than 10 days. Patients whose symptoms improve but eventually get worse may also need antibiotics.

•Clinicians should not prescribe antibiotics for patients with the common cold.

0 Comments Read more
 

The Benefits of Quitting Smoking

Wednesday, March 2, 2016 // Uncategorized

It’s never too late.  From a recent review article on smoking cessation from the Annals of Internal Medicine. Even patients who have lung cancer have an average survival that is longer in those who quit smoking than those who continue to smoke.

The benefits of quitting begin immediately and last for decades. After 10 years of smoking cessation, the risk for lung cancer in former smokers was reduced up to 50% (1). Smoking cessation reduces risk for death from CAD by two thirds within 2–3 years of quitting, with risk approaching that of persons who have never smoked (12, 13). Circulation improves within weeks of quitting, and stroke risk is reduced to the level of that of nonsmokers in 2–4 years (14). Lung function improves within 3 months. Smoking cessation during the first 3–4 months of pregnancy reduces risk for low birthweight to that of never-smokers. Other benefits include reduced damaging effects on skin, breath, teeth and gums, smell, and taste. Finally, smokers and providers should be aware that tobacco use can affect metabolism of caffeine and commonly prescribed medications, including olanzapine, clozapine, and theophylline (15). Therefore, when smokers successfully quit, medication doses might be lowered.

Health Benefits of Quitting Tobacco

Symptoms: Minutes–days: Lower BP; lower carbon monoxide; better stamina, smell, tasteLung function

  • 2–4 weeks: Decreased respiratory infections

  • 4–12 weeks: Improved lung function

Cardiovascular disease

  • 2–3 months: Improved circulation

  • 1 year: 50% reduction for heart attack

  • 5–15 years: Cardiovascular risk equals that of never-smokers

Cancer: 10 years: Risk for lung cancer reduced by half

Is there an age after which smoking cessation no longer yields benefit?
Smoking cessation benefits people of all ages, regardless of smoking history (6, 7). Older smokers, despite smoking for many years, may have increased motivation from health concerns and symptoms of tobacco-related illness, experience with what has been successful in past quit attempts, and better access to treatment resources.
Two large, recent, retrospective cohort analyses showed that smokers who quit at age 55–64 years gained 4 years of life and that even those who quit after age 70 years had lower risk for mortality than those who continued to smoke (6, 7).
Clinical Bottom Line: Health Consequences of Smoking
Tobacco use affects nearly every organ system in the body and leads to numerous disorders, including heart disease, stroke, many types of cancer, vascular disease, respiratory infections, diabetes, and gastroesophageal reflux disease. The health benefits of quitting start within minutes and continue for years. These risk-reduction benefits are especially significant for smokers with CAD, COPD, or those who are pregnant by reducing preterm labor and low birthweight. Cessation for smokers with children can reduce exposure to and disease caused by environmental tobacco smoke. Even after decades of smoking, those who stop smoking significantly reduce their risk for death from certain diseases, such as lung cancer, and slow the deterioration of lung function in patients with COPD. One is never too old or young, too healthy or sick, to benefit from smoking cessation.
0 Comments Read more
 

“I Heard This on TV….”

Tuesday, February 23, 2016 // Uncategorized

We are constantly bombarded with medical news. It is part of the fodder of the news media.  The problem with this is that information is not all of the same caliber. It doesn’t all carry the same weight. Case in point, a recent study showed and association between proton pump inhibitors like Nexium and chronic kidney disease.  This is a summary from Journal Watch.

  • Proton-Pump Inhibitors Are Associated with Chronic Kidney Disease Thomas L. Schwenk, MD reviewing Lazarus B et al. JAMA Intern Med 2016 Jan 11. Schoenfeld AJ and Grady D. JAMA Intern Med 2016 Jan 11. Thomas L. Schwenk, MDA further reason to use PPIs only when their clinical benefits are clear Thomas L. Schwenk, MD Polypharmacy is one possible cause of the increasing prevalence of chronic kidney disease (CKD) in the U.S. population. Proton-pump inhibitor (PPI) use is associated with acute renal injury, but PPIs also have other biological effects, including hypomagnesemia, that can lead to excess risk for CKD. In a population-based, prospective cohort study, researchers followed 10,482 adults (mean age, 63; 80% white) with normal renal function (estimated glomerular filtration rate, >60 mL/minute/1.73 m2); at baseline, 322 participants used PPIs and 956 participants used histamine-2 (H2)–receptor antagonists. During the study (median follow-up, 14 years), PPI use increased markedly, to ≈27% of participants.At study end, the unadjusted incidence of CKD was significantly higher among baseline-PPI users than among baseline nonusers (14.2 vs. 10.7 cases per 1000 person-years); after statistical adjustment, the difference remained significant (hazard ratio, 1.5). CKD risk for baseline H2–antagonist users remained at baseline levels. A similar replication study in 249,000 participants who were followed for a median 6 years yielded similar results.Comment:These results add to increasing concerns about PPI use, including excess risks for Clostridium difficile infections, pneumonia, and fractures. Editorialists recommend monitoring renal function and magnesium levels in patients who are taking PPIs and who are at high risk for CKD; such patients should switch to H2-antagonists when possible and should not use PPIs for vague complaints of heartburn or dyspepsia. – See more at: http://www.jwatch.org/na40149/2016/01/12/proton-pump-inhibitors-are-associated-with-chronic-kidney#sthash.SV6vDFbi.dpuf

     

    The problem is that observational studies have inherent weaknesses. The following is from Wikepedia.

    Observational study

    From Wikipedia, the free encyclopedia

    Jump to: navigation, search

    In fields such as epidemiology, social sciences, psychology and statistics, an observational study draws inferences from a sample to a population where the independent variable is not under the control of the researcher because of ethical concerns or logistical constraints. One common observational study is about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator.[1][2] This is in contrast with experiments, such as randomized controlled trials, where each subject is randomly assigned to a treated group or a control group.

     

    Weaknesses

    The independent variable may be beyond the control of the investigator for a variety of reasons:

    • A randomized experiment would violate ethical standards. Suppose one wanted to investigate the abortion – breast cancer hypothesis, which postulates a causal link between induced abortion and the incidence of breast cancer. In a hypothetical controlled experiment, one would start with a large subject pool of pregnant women and divide them randomly into a treatment group (receiving induced abortions) and a control group (not receiving abortions), and then conduct regular cancer screenings for women from both groups. Needless to say, such an experiment would run counter to common ethical principles. (It would also suffer from various confounds and sources of bias, e.g.,it would be impossible to conduct it as a blind experiment.) The published studies investigating the abortion–breast cancer hypothesis generally start with a group of women who already have received abortions. Membership in this “treated” group is not controlled by the investigator: the group is formed after the “treatment” has been assigned.[citation needed]
    • The investigator may simply lack the requisite influence. Suppose a scientist wants to study the public health effects of a community-wide ban on smoking in public indoor areas. In a controlled experiment, the investigator would randomly pick a set of communities to be in the treatment group. However, it is typically up to each community and/or its legislature to enact a smoking ban. The investigator can be expected to lack the political power to cause precisely those communities in the randomly selected treatment group to pass a smoking ban. In an observational study, the investigator would typically start with a treatment group consisting of those communities where a smoking ban is already in effect.[citation needed]
    • A randomized experiment may be impractical. Suppose a researcher wants to study the suspected link between a certain medication and a very rare group of symptoms arising as a side effect. Setting aside any ethical considerations, a randomized experiment would be impractical because of the rarity of the effect. There may not be a subject pool large enough for the symptoms to be observed in at least one treated subject. An observational study would typically start with a group of symptomatic subjects and work backwards to find those who were given the medication and later developed the symptoms. Thus a subset of the treated group was determined based on the presence of symptoms, instead of by random assignment.

    Types of observational studies

    • Case-control study: study originally developed in epidemiology, in which two existing groups differing in outcome are identified and compared on the basis of some supposed causal attribute.
    • Cross-sectional study: involves data collection from a population, or a representative subset, at one specific point in time.
    • Longitudinal study: correlational research study that involves repeated observations of the same variables over long periods of time.
    • Cohort study or Panel study: a particular form of longitudinal study where a group of patients is closely monitored over a span of time.
    • Ecological study: an observational study in which at least one variable is measured at the group level.

    Degree of usefulness and reliability

    Although observational studies cannot be used as reliable sources to make statements of fact about the “safety, efficacy, or effectiveness” of a practice,[3] they can still be of use for some other things:

    “[T]hey can: 1) provide information on “real world” use and practice; 2) detect signals about the benefits and risks of…[the] use [of practices] in the general population; 3) help formulate hypotheses to be tested in subsequent experiments; 4) provide part of the community-level data needed to design more informative pragmatic clinical trials; and 5) inform clinical practice.”[3]

    Bias and compensating methods

    In all of those cases, if a randomized experiment cannot be carried out, the alternative line of investigation suffers from the problem that the decision of which subjects receive the treatment is not entirely random and thus is a potential source of bias. A major challenge in conducting observational studies is to draw inferences that are acceptably free from influences by overt biases, as well as to assess the influence of potential hidden biases.

    An observer of an uncontrolled experiment (or process) records potential factors and the data output: the goal is to determine the effects of the factors. Sometimes the recorded factors may not be directly causing the differences in the output. There may be more important factors which were not recorded but are, in fact, causal. Also, recorded or unrecorded factors may be correlated which may yield incorrect conclusions. Finally, as the number of recorded factors increases, the likelihood increases that at least one of the recorded factors will be highly correlated with the data output simply by chance.

    In lieu of experimental control, multivariate statistical techniques allow the approximation of experimental control with statistical control, which accounts for the influences of observed factors that might influence a cause-and-effect relationship. In healthcare and the social sciences, investigators may use matching to compare units that nonrandomly received the treatment and control. One common approach is to use propensity score matching in order to reduce confounding.[4]

    A report from the Cochrane Collaboration in 2014 came to the conclusion that observational studies are very similar in results reported by similarly conducted randomized controlled trials. In other words, it reported little evidence for significant effect estimate differences between observational studies and randomized controlled trials, regardless of specific observational study design, heterogeneity, or inclusion of studies of pharmacological interventions. It therefore recommended that factors other than study design per se need to be considered when exploring reasons for a lack of agreement between results of randomized controlled trials and observational studies.[5]

    In 2007, several prominent medical researchers issued the Strengthening the reporting of observational studies in epidemiology (STROBE) statement, in which they called for observational studies to conform to 22 criteria that would make their conclusions easier to understand and generalise.[6]

    Correlation does not imply causation” is a phrase used in statistics to emphasize that a correlation between two variables does not imply that one causes the other.[1][2] Many statistical tests calculate correlation between variables. A few go further, using correlation as a basis for testing a hypothesis of a true causal relationship; examples are the Granger causality test and convergent cross mapping.[clarification needed (hypothesis testing not well explained here)]

    The counter-assumption, that “correlation proves causation”, is considered a questionable cause logical fallacy in that two events occurring together are taken to have a cause-and-effect relationship. This fallacy is also known as cum hoc ergo propter hoc, Latin for “with this, therefore because of this”, and “false cause”. A similar fallacy, that an event that follows another was necessarily a consequence of the first event, is sometimes described as post hoc ergo propter hoc (Latin for “after this, therefore because of this”).

    For example, in a widely studied case, numerous epidemiological studies showed that women taking combined hormone replacement therapy (HRT) also had a lower-than-average incidence of coronary heart disease (CHD), leading doctors to propose that HRT was protective against CHD. But randomized controlled trials showed that HRT caused a small but statistically significant increase in risk of CHD. Re-analysis of the data from the epidemiological studies showed that women undertaking HRT were more likely to be from higher socio-economic groups (ABC1), with better-than-average diet and exercise regimens. The use of HRT and decreased incidence of coronary heart disease were coincident effects of a common cause (i.e. the benefits associated with a higher socioeconomic status), rather than a direct cause and effect, as had been supposed.[3]

    As with any logical fallacy, identifying that the reasoning behind an argument is flawed does not imply that the resulting conclusion is false. In the instance above, if the trials had found that hormone replacement therapy does in fact have a negative incidence on the likelihood of coronary heart disease the assumption of causality would have been correct, although the logic behind the assumption would still have been flawed.

    BOTTOM LINE: I don’t know if proton pump inhibitors cause kidney disease just like I don’t know if calcium supplements cause heart disease or statins cause ALS. All of these have been implicated in previous observational studies.  I do know that all medication should be used cautiously and not indiscriminately. It is worthwhile to periodically review the drugs that your are taking and discuss with your physician if they should be continued.

     

 

0 Comments Read more
 

“Medical Taylorism” or What is Wrong With Medicine Today

Monday, January 18, 2016 // Uncategorized

This is an excellent editorial from the most recent issue of the New England Journal of Medicine that resonated with me. I wanted to share it. It wasn’t surprising who authored it, two of my favorite authors.

Medical Taylorism

Pamela Hartzband, M.D., and Jerome Groopman, M.D.

N Engl J Med 2016; 374:106-108January 14, 2016DOI: 10.1056/NEJMp1512402

Frederick Taylor, a son of Philadelphia aristocrats who lived at the turn of the last century, became known as the “father of scientific management” — the original “efficiency expert.” He believed that the components of every job could and should be scientifically studied, measured, timed, and standardized to maximize efficiency and profit. Central to Taylor’s system is the notion that there is one best way to do every task and that it is the manager’s responsibility to ensure that no worker deviates from it. “In the past, the man has been first; in the future, the system must be first,” Taylor asserted.1

Toyota, inspired by these principles of “Taylorism,” successfully applied them to the manufacture of cars, thereby improving quality, eliminating waste, and cutting costs. As health care comes under increasing economic pressure to achieve these same goals, Taylorism has begun permeating the culture of medicine.

Advocates lecture clinicians about Toyota’s “Lean” practices, arguing that patient care should follow standardized systems like those deployed in manufacturing automobiles. Colleagues have told us, for example, that managers with stopwatches have been placed in their clinics and emergency departments to measure the duration of patient visits. Their aim is to determine the optimal time for patient–doctor interactions so that they can be standardized.

Meanwhile, the electronic health record (EHR) — introduced with the laudable goals of making patient information readily available and improving safety by identifying dangerous drug–drug interactions — has become a key instrument for measuring the duration and standardizing the content of patient–doctor interactions in pursuit of “the one best way.” Encounters have been restructured around the demands of the EHR: specific questions must be asked, and answer boxes filled in, to demonstrate to payers the “value” of care. Open-ended interviews, vital for obtaining accurate clinical information and understanding patients’ mindsets, have become almost impossible, given the limited time allotted for visits — often only 15 to 20 minutes. Instead, patients are frequently given checklists in an effort to streamline the interaction and save precious minutes. The EHR was supposed to save time, but surveys of nurses and doctors show that it has increased the clinical workload and, more important, taken time and attention away from patients.

Physicians sense that the clock is always ticking, and patients are feeling the effect. One of our patients recently told us that when she came in for a yearly “wellness visit,” she had jotted down a few questions so she wouldn’t forget to ask them. She was upset and frustrated when she didn’t get the chance: her physician told her there was no time for her questions because a standardized list had to be addressed — she’d need to schedule a separate visit to discuss her concerns.

We believe that the standardization integral to Taylorism and the Toyota manufacturing process cannot be applied to many vital aspects of medicine. If patients were cars, we would all be used cars of different years and models, with different and often multiple problems, many of which had previously been repaired by various mechanics. Moreover, those cars would all communicate in different languages and express individual preferences regarding when, how, and even whether they wanted to be fixed. The inescapable truth of medicine is that patients are genetically, physiologically, psychologically, and culturally diverse. It’s no wonder that experts disagree about the best ways to diagnose and treat many medical conditions, including hypertension, hyperlipidemia, and cancer, among others.

To be sure, certain aspects of medicine have benefited from Taylor’s principles. Strict adherence to standardized protocols has reduced hospital-acquired infections, and timely care of patients with stroke or myocardial infarction has saved lives. It may be possible to find one best way in such areas. But this aim cannot be generalized to all of medicine, least of all to such cognitive tasks as eliciting an accurate history, synthesizing clinical and laboratory data to make a diagnosis, and weighing the risks and benefits of a given treatment for an individual patient. Good thinking takes time, and the time pressure of Taylorism creates a fertile field for the sorts of cognitive errors that result in medical mistakes. Moreover, rushed clinicians are likely to take actions that ignore patients’ preferences.

Part of the original promise of scientific management was that increased efficiency and standardization would not only result in a better product at lower cost, but would also give workers more free time to enjoy life. Lillian Gilbreth, who with her husband Frank championed motion studies of workers to boost their efficiency, called this outcome saving time for “happiness minutes”2 (see Perspective article by Gainty, pages xxx–xx). Similarly, some prominent policymakers have claimed that implementing scientific management in medicine would free doctors, nurses, and other members of the clinical team to spend more time with their patients.3 In fact, the opposite seems to be happening. Yet some of the greatest rewards of working in medicine come from spending unstructured time with our patients, sharing their joys and sorrows.

Instead of gaining happiness minutes, clinicians are increasingly experiencing dissatisfaction and burnout as they’re subjected to the time pressures of Taylorism and scientific management in the name of efficiency. We have watched colleagues fleeing to concierge practices, where they have control over their schedules. Others have taken early retirement, unwilling to compromise on what they believe is the time needed to deliver compassionate care. Some have moved into management or consulting positions, where they tell others how to practice while unburdening themselves of their clinical load. Just as Taylor enriched himself by consulting for companies, a growing and lucrative industry has emerged to generate and enforce metrics in medicine. By 2014, the Centers for Medicare and Medicaid Services alone had mandated the use of more than 1000 performance measures. As the Institute of Medicine recently reported, such metrics have proliferated, though many of them have little proven value.4

There is a certain hypocrisy among some of the most impassioned advocates for efficiency and standardization in health care, as Boston neurologist Martin Samuels recently pointed out. “They come from many different backgrounds: conservatives, liberals, academics, business people, doctors, politicians, and more often all the time various combinations of these. But they all have one characteristic in common. They all want a different kind of health care for themselves and their families than they profess for everyone else.”5 What they want is what every patient wants: unpressured time from their doctor or nurse and individualized care rather than generic protocols for testing and treatment.

Yet students are now taught the principles of Taylorism and Toyota Lean as early as their first year of medical school. They enter clinical rotations believing that there must be one best way to diagnose and treat every medical condition. In residency training and beyond, they discover that’s not the case, and they face a steep learning curve as they take on primary responsibility for patient care. We learn how to modify and individualize care in the real world, recognizing the variety of clinical presentations, the reality of multiple coexisting conditions, the variability of human biology, the effects of social and cultural contexts, and the diversity of patients’ preferences regarding risk and benefit, all of which defy rigid protocols.

Medical Taylorism began with good intentions — to improve patient safety and care. But we think it has gone too far. To continue to train excellent physicians and give patients the care they want and deserve, we must reject its blanket application. That we’re beginning to do so is shown, for example, by a bill before Congress that would delay implementation of the Meaningful Use Stage 3 criteria for information-technology use in health care. We need to recognize where efficiency and standardization efforts are appropriate and where they are not. Good medical care takes time, and there is no one best way to treat many disorders. When it comes to medicine, Taylor was wrong: “man” must be first, not the system.

Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

From Beth Israel Deaconess Medical Center and Harvard Medical School — both in Boston.

.References

1

Taylor FW. The principles of scientific management. New York: Harper & Brothers, 1911.

.

2

Lepore J. Not so fast: scientific management started as a way to work. How did it become a way of life? New Yorker October 12, 2009:12-12

.

3

Swensen SJ, Meyer GS, Nelson EC, et al. Cottage industry to postindustrial care — the revolution in health care delivery. N Engl J Med 2010;362:e12-e12
Free Full Text | Web of Science | Medline
.

4

Blumenthal D, McGinnis JM. Measuring vital signs: an IOM report on core metrics for health and health care progress. JAMA 2015;313:1901-1902
CrossRef | Web of Science | Medline
.

5

Samuels M. The anti-hypocrisy rule. Forbes 2014 (http://www.forbes.com/sites/davidshaywitz/2014/12/09/the-anti-hypocrisy-rule).

1 Comment Read more
 

Bad News Causes Deaths?

Wednesday, December 9, 2015 // Uncategorized

We are all inundated by medical news. It is all around us. Most people who hear it give it equal weight, but there is a wide variation in the quality and accuracy of it. This study shows the negative effect that medical news can have. People with heart disease stop their statins, medication which can prolong life and reduce the risk of heart attacks and stroke because of this negative news and some die as a result of this.

Negative news about statins is causing early death for heart disease patients
University of Copenhagen Faculty of Health and Medical Sciences News, 12/08/2015

Researchers in Denmark have found that negative news stories about statins are linked to some people choosing to discontinue their statin treatment, which, in consequence, is associated with an increased risk of heart attacks and dying from heart disease. The study, which was published in the European Heart Journal, shows that for every negative nationwide news story about the cholesterol–lowering group of medicines, there was a nine percent increased risk of people deciding to stop taking statins within six months of first being prescribed the drug. “We found that exposure to negative news stories about statins was linked to stopping statins early and explained two percent of all heart attacks and one percent of all deaths from cardiovascular disease associated with early discontinuation of statins,” said Professor Borge Nordestgaard, Chief Physician at Copenhagen University Hospital in Denmark. During the period from 1995 to 2010 the proportion of people on statins increased from less than one percent to 11%, while early statin discontinuation increased from six percent to 18%. The number of all statin–related news stories (positive, neutral and negative) increased from 30 per year in 1995 to 400 in 2009. In addition to the increased risk from negative news stories, the researchers found that the risk of early statin discontinuation increased per increasing calendar year (4%), increased daily dose (4%), being male (5%), living in cities (13%) and for being of non–Danish ethnicity (67%). In contrast, the risk of discontinuation decreased after exposure to positive news stories about statins (8%), and having cardiovascular disease or diabetes at the time the statins were first prescribed (27% and 9% respectively). In this study the researchers find that close to one in six of individuals discontinue therapy at an early stage, and this represents a major problem for cardiovascular health. These findings suggest a need to develop ways of increasing people’s adherence to statin therapy during the first six months in particular. “Positive news stories tend to be evidence–based, explaining how statins can prevent heart disease and early death, while this is often not the case for negative news stories, which tend to focus on relatively rare and moderate side effects. Considering how often there is a negative statin–related news story, we detected a surprisingly strong association: an increase of nine percent in early discontinuation for each nationwide story. If negative statin–related news stories did not exist at all, then early statin discontinuation would decrease by 1.3% in the whole of the population,” prof Nordestgaard concluded.

0 Comments Read more
 

PSA Police?

Sunday, November 29, 2015 // Uncategorized

Screening for prostate cancer is controversial for reasons outlined in this article from the Wall Street Journal, but now it is taking a new turn. The government is becoming more aggressive in determining what high quality care is. Before they would not pay for certain tests or medications that were unapproved. Now, they will actually penalize doctors. This goes way beyond educating the public. It interferes with shared decision making by patients and their doctors.

Doctors Could be Penalized for Ordering This Test
Wall Street Journal

November 20, 2015

By Melinda Beck

Medicare officials are considering a measure that would penalize doctors who order routine prostate-cancer screening tests for their patients, as part of a federal effort to define and reward quality in health-care services.

The proposal, which hasn’t been widely publicized, has prompted a flurry of last-minute comments to the Centers for Medicare and Medicaid Services, including more than 200 in the past two days, virtually all in opposition. The official comment period began Oct. 26 and ends Friday.

Many of those commenting said the measure would discourage doctors from discussing the pros and cons of screening for prostate-specific antigen (PSA) with their patients and allowing them to decide, as several major medical groups recommend.

“PSA screening is a very controversial topic. The debate is ongoing and people feel very strongly about it, one way or another,” said David Penson, chair of public policy and practice support for the American Urological Association, which urged CMS to reject the proposal. “To make it a quality measure would say, ‘You’re a poor quality doctor if your patients get this test.’ ”

The proposed measure is part of continuing federal efforts to develop ways to identify and reward value in health care. The Obama administration has said it plans to tie 50% of Medicare payments to such quality measures by 2018.

Since 2012, the U.S. Preventive Services Task Force has recommended against routine screening for prostate cancer for men of any age on the grounds that the benefits don’t outweigh the harms.

Studies have shown that screening reduces the risk of death from prostate cancers only minimally, if at all, because most grow so slowly they effectively are harmless.

Yet many men diagnosed with prostate cancer undergo surgery and radiation, which can have lifelong side effects.

Meanwhile, about 28,000 U.S. men die annually from aggressive prostate cancers, often despite getting regular PSA tests and fast treatment.

Both the rate of PSA testing, and diagnoses of early-stage prostate cancer, have declined significantly in the U.S. in recent years, according to studies published in the Journal of the American Medical Association this week. But whether treating fewer cancers early results in more deaths from late-stage prostate cancer later won’t be known for many years.

A CMS official said that as currently drafted, the proposed measure addresses only “non-recommended PSA screenings”—that is, “men who get PSA screening when, under current clinical guidelines, it is not recommended for them.” She said it wouldn’t restrict needed or medically necessary PSA tests.

“Physicians can still order PSA tests if they feel the test is recommended or if the patient requests it,” she said.

The proposal lists some categories of men who would be excluded from the measure, including those with a history of prostate cancer or enlarged prostate, prior elevated PSA levels, or those taking certain medications for prostate issues. It doesn’t mention men at high risk for prostate cancer due to family history or African-American heritage. Some experts say the benefits of screening may outweigh the harms for such patients.

Wanda Flier, president of the American Academy of Family Physicians, which is working with CMS on other quality measures, said it planned to urge the agency to adopt a more flexible measure for PSA screening that would allow for shared decision-making between a patient and physician based on individual circumstances.

“Our goal, as we move to value-based care, is to get to a system that is based on evidence and individual circumstances and not create harm to the patient or undue economic harm to the country,” she said.

0 Comments Read more
 

Blood Pressure: How Low Do You Go?

Sunday, November 15, 2015 // Uncategorized

retro This article got a lot of press and a lot of patient’s questions when the study was ended prematurely several months ago.  I couldn’t answer patient’s questions on the news release because the study hadn’t been published.  Now it has been on November 9th and the results only apply to high risk patients who are being treated for  hypertension.

Bottom line:Treating to a lower blood pressure goal in high risk individuals may be of benefit, but it comes at a potential cost.

Here is the summary from Journal Watch.

SPRINT: Intensive Blood Pressure Control Tied to Lower Adverse CV Events

By Allan S. Brett, MD

Dr. Brett is editor-in-chief of NEJM Journal Watch General Medicine, from which this summary was adapted. See full coverage at the link below.

Treating to a systolic blood pressure target of 120 mm Hg lowered the incidence of adverse cardiovascular events in a high-risk population, according to the SPRINT study published in the New England Journal of Medicine and presented at the American Heart Association’s annual meeting.

Researchers enrolled roughly 9400 patients (age 50 or older) with a systolic BP of 130 to 180 mm Hg and high cardiovascular risk but without diabetes or stroke. Patients were randomized to either intensive or standard treatment (systolic BP targets, 120 or 140 mm Hg, respectively). The researchers were permitted discretion in choosing drug regimens.

The trial was terminated early after a median follow-up of 3.3 years, during which participants’ average systolic BPs were 121.5 mm Hg and 134.6 mm Hg in the intensive- and standard-treatment groups, respectively. The primary composite outcome (myocardial infarction, non-MI acute coronary syndrome, stroke, heart failure, or CV-related death) occurred in 5.2% of intensive-treatment patients and 6.8% of standard-treatment patients. Two individual components of the composite outcome were significantly lower with intensive treatment — heart failure (1.3% vs. 2.1%) and CV-related death (0.8% vs. 1.4%). All-cause mortality also was significantly lower with intensive treatment (3.3% vs. 4.5%).

Several serious adverse events were significantly more common with intensive than with standard treatment: incidences of hypotension, syncope, and electrolyte abnormalities were each about 1 percentage point higher, and incidence of acute kidney injury was about 2 percentage points higher. Among patients without CKD at baseline, the incidence of a >30% decline in glomerular filtration rate was significantly greater with intensive treatment (3.8% vs. 1.1%).

SPRINT has demonstrated that aiming for a systolic BP of 120 mm Hg can lower the rate of adverse cardiovascular events; to prevent 1 event, 61 patients had to be treated for 3.3 years. Keep in mind that SPRINT was limited to middle-aged and older patients at above-average CV risk and that diabetic patients were excluded. Whether the decline in GFR associated with intensive treatment represents a harmless hemodynamic effect or more-serious renal injury is unclear.

Clinicians must understand that BP measurements in this study were based on the average of the three readings, taken automatically at 5-minute intervals with no clinician in the room. This method yields substantially lower readings than does a single measurement by a clinician. If SPRINT is applied without attention to proper BP measurement, substantial overtreatment — with a higher rate of adverse events — likely will occur.

Finally, note that the average achieved systolic BP in the intensive-treatment group (121.5 mm Hg) remained higher than the 120 mm target. This likely represents judicious balancing by treating clinicians who tried to approximate the 120 mm goal while avoiding side effects and excessive polypharmacy.

 

retro SPRINT: Intensive Blood Pressure Control Tied to Lower Adverse CV Events

By Allan S. Brett, MD

Dr. Brett is editor-in-chief of NEJM Journal Watch General Medicine, from which this summary was adapted. See full coverage at the link below.

Treating to a systolic blood pressure target of 120 mm Hg lowered the incidence of adverse cardiovascular events in a high-risk population, according to the SPRINT study published in the New England Journal of Medicine and presented at the American Heart Association’s annual meeting.

Researchers enrolled roughly 9400 patients (age 50 or older) with a systolic BP of 130 to 180 mm Hg and high cardiovascular risk but without diabetes or stroke. Patients were randomized to either intensive or standard treatment (systolic BP targets, 120 or 140 mm Hg, respectively). The researchers were permitted discretion in choosing drug regimens.

The trial was terminated early after a median follow-up of 3.3 years, during which participants’ average systolic BPs were 121.5 mm Hg and 134.6 mm Hg in the intensive- and standard-treatment groups, respectively. The primary composite outcome (myocardial infarction, non-MI acute coronary syndrome, stroke, heart failure, or CV-related death) occurred in 5.2% of intensive-treatment patients and 6.8% of standard-treatment patients. Two individual components of the composite outcome were significantly lower with intensive treatment — heart failure (1.3% vs. 2.1%) and CV-related death (0.8% vs. 1.4%). All-cause mortality also was significantly lower with intensive treatment (3.3% vs. 4.5%).

Several serious adverse events were significantly more common with intensive than with standard treatment: incidences of hypotension, syncope, and electrolyte abnormalities were each about 1 percentage point higher, and incidence of acute kidney injury was about 2 percentage points higher. Among patients without CKD at baseline, the incidence of a >30% decline in glomerular filtration rate was significantly greater with intensive treatment (3.8% vs. 1.1%).

SPRINT has demonstrated that aiming for a systolic BP of 120 mm Hg can lower the rate of adverse cardiovascular events; to prevent 1 event, 61 patients had to be treated for 3.3 years. Keep in mind that SPRINT was limited to middle-aged and older patients at above-average CV risk and that diabetic patients were excluded. Whether the decline in GFR associated with intensive treatment represents a harmless hemodynamic effect or more-serious renal injury is unclear.

Clinicians must understand that BP measurements in this study were based on the average of the three readings, taken automatically at 5-minute intervals with no clinician in the room. This method yields substantially lower readings than does a single measurement by a clinician. If SPRINT is applied without attention to proper BP measurement, substantial overtreatment — with a higher rate of adverse events — likely will occur.

Finally, note that the average achieved systolic BP in the intensive-treatment group (121.5 mm Hg) remained higher than the 120 mm target. This likely represents judicious balancing by treating clinicians who tried to approximate the 120 mm goal while avoiding side effects and excessive polypharmacy.

Why We Chose This as Our Top Story:

André Sofair, MD, MPH: This well-designed study reiterates the importance of individualized blood pressure control. It demonstrates that in certain high-risk patients, more aggressive BP targets may be warranted.

0 Comments Read more