How I chose my doctor

Four years ago after moving back to Iowa City, I needed to find a new primary care doctor. I went to the University’s website and scanned the list of general internists. There I noted a physician that I had known when she was a medical student during my prior stint at the University of Iowa twenty years earlier. She had been an amazing medical student--very bright, hardworking, conscientious, and intellectually curious. My guess was that she now was an amazing internist. I asked a few colleagues about her and the responses were consistent: a superb clinician, an internist’s internist. Exactly what I was looking for.

I scheduled a new patient visit with Dr. B. Was I ever impressed! No stone was left unturned. She didn’t treat me like a doctor (for non-medical readers, that's a good thing). She took a complete history, including asking me if I ever used IV drugs. She took a sexual history. She then performed a complete exam, including genital and rectal exams. I note this as sometimes doctors skip these parts of the H&P given the somewhat awkward situation when they know the patient (another doctor) personally. At the end of the visit, I recall telling her that the encounter should have been videotaped for use as an exemplar for students and residents. When I arrived back to my office, I sent a note to the Chair of Internal Medicine to apprise him of her superb care. He wrote me back: “Yes, Dr. B is the crown jewel of the Department of Internal Medicine.”

Now let’s leave my story for a minute and examine a new study in the BMJ from the University of Michigan on patient preference for physician attire. This is a survey of a convenience sample of 4,000 patients at 10 US academic medical centers. It included both inpatients and outpatients, and used the design of many previous studies, showing patients the same doctor dressed seven different ways (scrubs, formal with white coat, etc.). After viewing the photographs, patients were questioned as to their preference of physician based on attire, as well as asked to rate the physician in the areas of knowledge, trust, care, approachability, and comfort.

The survey is well-designed and well-executed. I’ll let you review the paper if you want to know the results, since I don’t think the results have much validity, don’t merit much discussion, and I’ve blogged about these types of studies, previously (here, here, here, and here). I’m much more interested in why such studies are conducted, the biases they may represent, whether the researchers have an underlying agenda, the utility of the results, and how these studies are pathologic manifestations of professionalism.

Back to my story. Never once, before, during or after my clinic visit with Dr B, did I for a millisecond think about how she would be or was dressed. Granted, I’m not the typical patient as I have insider knowledge regarding doctors that the average patient does not. Even still, all patients want an authentically kind, compassionate, competent doctor who listens intently, and makes access to them easy. While they may have a preference for physician attire, when placed in context (as shown in a previous study), appearance is the least important patient satisfier. When appearance is further studied, attire is the least important characteristic, with hygiene and grooming taking precedence.

To ask patients to infer characteristics such as knowledge and trust on the basis of clothing is ludicrous on its face, and an insult to the study participants. "I chose the doctor with the beautiful tie," said no patient ever. I dislike this study for the same reasons that I dislike the tactics of Disney service excellence and Press-Ganey patient satisfaction initiatives. The common theme is that you can and should manipulate patients' perceptions without changing reality. Per the Michigan study, a white coat makes the doctor look more caring, but all of us know that a jerk in a white coat is still a jerk. If the doctor sits down while talking to a patient, the patient will perceive that they stayed in their room longer. How about sitting down because it makes the patient more comfortable?

The authors argue for patient-centered care and that “attire may be an important, modifiable component of patient care.” How does this study help us to provide patient-centered care since no matter how the data were sliced there was always a sizable fraction (often nearly half) of patients that didn’t agree with the majority opinion? Does this mean we should ask each patient which of the seven attire modes they would prefer before entering the exam room?

Lastly, I don’t think this study is really about what patients think of how doctors dress. Underneath it all, it’s a study about what some doctors think about how other doctors dress. And this is the ugly side of professionalism. Imagine a study where physicians are surveyed on the attire of nurses or carpenters. I think most people would find that creepy. Don’t most of us think that judging people on the basis of how they dress is superficial and somewhat creepy? And the test of whether this is about professionalism is to remove the occupational label in the survey. If patients were told to assess the attire of other people (not doctors) what would be the study implications? If we look at attire through the lens of humanism rather than professionalism, then what matters is simply that your work clothes are clean, comfortable, functional, and safe.

My advice to the Michigan doctors is this: take good care of your patients and they will love you, white coats and all.

New evidence supports high-dose influenza vaccines

People older than 65 years are at particularly high risk for influenza-related medical complications including hospitalizations and death. In 2009, the FDA approved a trivalent inactivated vaccine with four-times the hemagglutinin antigen per strain, which was thought to improve immune response in seniors.

Background data has largely supported high-dose vaccination among seniors. In a multicenter, randomized controlled trial of high vs standard dose vaccine that included almost 32,000 patients during 2011/12 and 2012/13, 1.4% of high-dose and 1.9% standard-dose patients had an influenza-confirmed influenza-like illness, resulting in a relative efficacy of 24%. Adverse events were slightly, but significantly lower in the high-dose group but 3 high-dose recipients had serious vaccine-related events (which all resolved) vs none in the standard-dose group. A very large Medicare study during 2012/13 and 2013/14 reported similar benefits but only during 2012/13 when H3N2 was more common. Perhaps it is difficult to measure a benefit during more mild, H1N1 seasons? There have been other studies supporting the effectiveness and cost-effectiveness (at least during the 2011/12 and 2012/13 H3N2 seasons) of high-dose vaccine.

One of the larger groups of seniors in the US are patients in the Veterans Health Administration (VHA) system, so it makes sense to measure the benefits of high-dose vaccine using the VHA integrated EMR. In the June 1st JID, authors reported results of a large (industry-funded) retrospective cohort study completed using data from the 2015/16 influenza season (an H1N1 year) that included seniors with at least one inpatient or outpatient visit during the prior year (2014/15). The primary outcome was any hospitalization for pneumonia or influenza. The study used a number of nice methods to adjust for confounding including matching on baseline characteristics and the Care Assessment Need (CAN) score, that is a proxy for frailty. They also adjusted for residual confounding using the prior event rate ratio (PERR) method, which you can read more about here. Basically, PERR adjusts for outcome rates in the baseline period (before vaccination) by dividing the relative rate post-vaccination by the relative rate pre-vaccination (in the baseline period).

The final cohort (before matching) included 104,965 standard-dose and 125,776 high-dose recipients during the 2015/16  influenza season. The matched cohort had 49,091 standard-dose and 24,682  high-dose patients. Using the unmatched and matched cohorts, and using the PERR method with each, the relative vaccine effectiveness of high-dose influenza vaccine was 23% and 25%, respectively. This suggests that high-dose vaccine was effective in preventing influenza or pneumonia-associated hospitalizations among VHA patients.

These results are encouraging since they were from a more mild H1N1 season. Even more encouraging, the authors plan to automate the data extraction process and report vaccine effectiveness within 3 months of the end of each influenza season. But one note of caution, having a high-dose vaccine that is 25% more effective isn't a huge improvement, since influenza vaccines in general aren't very effective. So high-dose influenza vaccine is a small step in the right direction - but more research and new influenza vaccines are needed.

Upon Further Review: Reexamining the Illinois MRSA Active Surveillance Mandate

“Thinking without the positing of categories and concepts in general would be as impossible as breathing in a vacuum” – Albert Einstein (1949)

A couple weeks ago, Scott highlighted a study in CID by Lin et al. that sought to estimate the benefits of the 2007 Illinois state-wide mandate of MRSA active surveillance cultures in ICU settings. The post was titled “Good Intentions Does not Always Mean Good Policy” and concluded “There may be many reasons the hospitals in Illinois overall are seeing an estimated 30% decrease in their hospital-onset MRSA BSI (as most states are) since the 2010 NHSN baseline, but admission screening isn’t one of them.” 

I would like to list several reasons why I think we should reconsider the study authors’ conclusions. And if you skip to the end, you will read why I think this study might make more valid conclusions about the lack of benefits of CHG bathing.

Let’s start with validity from Shadish (2001) et al: “We use the term validity to refer to the proximate truth of an inference. When we say something is valid, we make a judgement about the extent to which relevant evidence supports that inference as being true of correct.” Cook and Campbell (1979) outlined four components of validity: statistical conclusion validity, internal validity, construct validity and external validity. I’ve written about their validity typology here, if you’re interested. 

Now let’s review the Illinois study methods. They included data from 25 ICUs and completed eight, one-day point prevalence surveys AFTER the mandate was initiated (twice annually 2008-2011 and annually in 2012 and 2013). There was no concurrent control group.

Thus, this quasi-experimental study design has very low internal validity. It has no measurement before the intervention (sometimes called historical controls) and no concurrent controls. Shadish labeled this design as a “one-group post-test only design” and summarized its limitations with “this design is rarely useful.”

The Illinois study also lacks statistical validity, since it is underpowered to detect a benefit of active surveillance. Shadish lists low statistical power as the first threat to statistical validity since “the experiment may incorrectly conclude that the relationship between treatment and outcome is not significant.” Since the Illinois study is a negative one – claiming active surveillance for MRSA didn’t work, power is particularly important. If you jump ahead to my ICAAC abstract, you will begin to see why the study is likely very underpowered. Point prevalence is very insensitive to changes in acquisition or transmission, so you would need very large studies to see a benefit.

I’ll admit that a statewide study has strong external validity – that is generalizability. 

But let’s focus on construct validity. Construct validity - what Einstein was hinting at in the quote above - describes whether a study measures what it claims to be measuring. For example, if a study claims that active surveillance for MRSA and isolation doesn’t prevent MRSA transmission, that study better measure MRSA transmission. 

Let’s pause here. Now some might say, we don’t care about transmission, we just care about MRSA prevalence or MRSA infections or MRSA CLABSI (or even deaths in Avengers movies). Yet, active surveillance for MRSA doesn’t work like that – it prevents transmission between patients. 

But what if measuring MRSA point prevalence was good enough at detecting MRSA transmission? Thought experiment: what if we found PCN allergy alerts in the EMR annoying and so we eliminated them? To see if this was safe, we then checked to see if anyone was having a PCN allergic reaction every St Patrick’s Day for the next 5 years. Good enough, right? Probably not. Why would we be comfortable saying yearly point prevalence is an adequate way of measuring the benefits of MRSA transmission? I don’t think we should and here’s why:

Back in 2002 I presented an abstract at ICAAC titled: “Point Prevalence and Clinical Culture Positivity of Vancomycin Resistant Enterococci are Poor Estimates of Infection Control Intervention Impact.” This study was based on the VRE model that we eventually published in CID (2004). Anyway, we modeled VRE transmission in the ICU under a condition where active surveillance compliance on admission increased from 60% to 100% and I assumed that isolation prevented 71% of transmissions. This is a math model, so we know that the intervention worked– but could we detect it? The answer was yes but only if we used admission/discharge screening cultures.  If we used point prevalence, like the Illinois study, we would falsely claim that the intervention didn’t work 54% of the time. However, if we used admission/discharge cultures, we would correctly determine that the intervention worked 96% of the time. Here is our conclusion:

“Point prevalence or clinical culture positivity often failed to detect a benefit due to stochastic fluctuations in prevalence and high prevalence of VRE in patients entering the ICU. Studies to assess the benefits of active surveillance for VRE should measure new incident cases. Relying on point prevalence or clinical culture positivity to assess the benefits of infection control interventions may underestimate the magnitude of their benefit and may be responsible for a persistent bias against the broader institution of active surveillance. The benefits of active surveillance and other infection control interventions are probably underestimated.”  

Not bad for 16 years ago – replace VRE with MRSA and you can see why the study by Lin et al cannot be used to evaluate the benefits of active surveillance. Our conclusion was partially driven, as we said, by high rates of VRE colonization on admission. What did Lin et al say about their study: “we assessed MRSA prevalence in a region where MRSA is widely endemic both in the community and within healthcare facilities.” Thus, the MRSA situation in Illinois fits closely with what we modeled.

In conclusion – the study by Lin et al should not be used to claim active surveillance was ineffective in Illinois or elsewhere. When drawing inferences, it is important to remember all four components of validity described by Cook and Campbell 40 years ago. We still need to figure out why MRSA has declined by 30% in Illinois and elsewhere. I do wonder why we are so quick to claim CLABSI bundles, CHG bathing (see below) or other interventions have been driving these MRSA reductions and not active surveillance. If I had to guess, it’s something yellow and not the data.

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Side note: In this same study, the number of hospitals using CHG bathing in their ICUs went from 5 (20%) to 17 (68%). It appears the authors could use these same data and methods to show that CHG doesn’t prevent MRSA in ICUs settings. Interestingly since CHG bathing works at the level of transmission and also on individual patients’ decolonization, point prevalence data would have higher construct validity for evaluating CHG. The study might even be better powered to detect a benefit of CHG.

Lack of Financial Incentives for Preventive Interventions

One of the barriers to infection control and antimicrobial stewardship is the lack of financial support from third-party payers, such as insurance companies and medicare. For example, wouldn't it be great if we could bill for hand hygiene every time it was practiced correctly? The end result of this lack of support is that society is willing to pay thousands for a CABG surgery, for example, but not willing to spend a penny on preventing a surgical site infection.

There is a new perspective in the NEJM by two physician behavioral economists, Katherine Pryor and Kevin Volpp, that examines barriers to putting preventive services on equal financial footing with treatments. While their comments largely focus on patient-targeted (vs population targeted) preventive services like lifestyle-modification for diabetes prevention or smoking cessation, they highlight many barriers that could apply equally to population-level interventions like infection control. I've highlighted a few:

"...treatments determined by the Food and Drug Administration (FDA) to be safe and effective are usually covered by insurers regardless of their cost, but preventive services have been held to a higher standard: they are often assessed on the basis of whether they generate a positive return on investment and save money in the short term. This disparity leads to overprovision of treatments and underprovision of preventive services"

"Even Medicare — which typically covers beneficiaries for life — holds preventive services to a higher standard, applying cost-effectiveness analyses when making coverage decisions about preventive services but not treatments. This double standard has resulted in coverage of cost-ineffective therapies with prices of up to hundreds of thousands of dollars per quality-adjusted life-year, including treatments of questionable benefit"

The perspetive is worth a careful read. Would also be nice to see a similar commentary describing these barriers from an infection control perspective too.

Good Intentions Does not Always Mean Good Policy

How often do negative studies influence our behavior, or better yet our policies? For those of you that are familiar with the work I have published, you know that I published a lot of material focused on MRSA; emerging resistance, community-emergence, burden of disease, attributable cost, risk factors, and on.  I was in a position at CDC to access and synthesize a lot of data, with a goal of putting the problem in perspective and ideally affect policy. Well intended as it was, I remember very clearly in mid-2007 when policy got way ahead of the science. Two independent (but related) events occurred on October 16-17, 2007 that led to several years of a watershed of policy developments. Although I give a huge amount of credit to the very passionate and important patient advocates and consumers that built momentum for the policies – but with hindsight the policy inertia was really overcome when a senior student at Staunton River High School died on October 16 from MRSA sepsis—MRSA he acquired in the community. The press linked that death to Dr. Elizabeth Bancroft’s editorial that same week stating “…more people die of MRSA in the U.S. than of AIDS” published on October 17. Many of us see much of the public reporting and mandatory reporting policies have opened up real pathways for additional hospital resources to invest in HAI prevention. However all of us should recognize some policies of that era are likely in place that really should be re-examined. 

One of these is the Illinois 210 ILCS 83/ legislation requiring all patients admitted to intensive care units be screened for MRSA by nasal active surveillance testing (AST). Lin and colleges just published a negative study with a lot of important findings. To many, the findings will not be a surprise (CID May 15 2018, pp 1535-1539)

• Lin worked with 51 intensive care units at 25 hospitals over 5 years starting within months of enactment of this mandate to evaluate any changes in ICU MRSA prevalence through periodic point prevalence surveys performed by trained study staff during the time of this mandate. The study was a quasi-experimental time series evaluation but without a real before observation group and no control group. However, I believe that any impact would have been additive over time – the first year would have been a sort of wash in period for an intervention as broad in participation as this.  They sampled 3909 patients having the power to even detect an absolute difference in carriage as small as a 1.9% change in prevalence (eg, 10% vs 8.1%) – but they detected none. No change in prevalence of MRSA on these patients. 
  

• Compliance was high overall (93%), admission prevalence was comparable to other studies (9.7%), and overall, at any given survey of known positive patients and unknown, 11.1% were positive in any given month, in any given year of this study.  Sure, time to placement of contact precautions lagged from test turnaround time or from time to test result to actual placement of precautions, but most notably the mandated testing was only 84% sensitive compared to best testing methods  employed by the study investigators. This is the real world after all.

• While these ICUs have invested time, effort, and money into these admission swabbing and targeted placement of contact precautions, the prevalence of MRSA carriage has not budged in these intensive care unit patients.

There may be many reasons the hospitals in Illinois overall are seeing an estimated 30% decrease in their hospital-onset MRSA BSI (as most states are) since the 2010 NHSN baseline, but admission screening isn’t one of them. Maybe its CLABSI prevention, or that uptake of the percentage of study patients receiving CHG baths. However, this study suggests it was not the mandated AST for all ICU patients admitted to the ICU. These patients are bringing their MRSA in with them, let’s free up staff time to prevent the infections.

I know there are many major federal policies we all can be passionate about changing or starting, these are crazy days. But when the scientific evidence is so strong illustrating that a very well-intended policy regarding use of nursing and infection control resources does not have the intended impact – change it. Nursing care can better be spent caring for patients, practicing best infection control for all patients in these intensive care units.