Wrong answer

This morning I stumbled upon this piece, Wrong Answer (free full text here), by Rachel Aviv in The New Yorker. It's an old article from 2014, but a wonderfully written, compelling, sad tale. It's the story of how high stakes standardized testing of middle school students in economically disadvantaged neighborhoods in Atlanta led to cheating by teachers. It focuses on Damany Lewis, a superb teacher totally committed to his students, who tirelessly worked to improve his students' math knowledge and was successful in doing so, but not successful enough to hit an unreachable goal. Responding to increasing pressure to raise testing scores, he and other teachers began to change the answers on students' tests. We all know that cheating is unethical, and at first glance I bet most of us would argue to punish those involved, but read this entire piece (warning: it's long), and you're likely to soften your stance. The consequences of not meeting unreasonable targets were so severe that the teachers felt compelled to cheat in the best interest of their students.

Now take this article from the education setting into the world of healthcare epidemiology, and if you're like me, there will be chills going down your spine as you read it. It should be required reading for anyone who works in healthcare quality or the key stakeholders in this space, from those at the front lines to those who work in professional societies, and to those who create policy at the state or national level. There are also lessons here for patients and patient advocates.

Donald Campbell

What happened in Atlanta shouldn't surprise us. In 1979, Donald Campbell, a psychologist, published a paper, the crux of which has become known as Campbell's law. I wasn't aware of this until I read Aviv's article. It states: "The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor." Moving this to our world, you can delete the word "social" in Campbell's law and take a look at Dan Sexton's commentary, Casablanca Redux, from 2012. Here's an excerpt:

Our informal discussions with other hospital epidemiologists, our experience in evaluating the source of infection in hundreds of bacteremic intensive care unit (ICU) patients, and common sense have led us to suspect that many hospitals do not accurately report their true rates of CLABSI, using current NHSN definitions. In some cases this may reflect an unwillingness of local staff to accept these definitions as accurate or fair; in other situations it may reflect an unconscious desire to hedge or reduce their rate of CLABSI to avoid criticism and negative consequences from their local supervisors in the press, clinicians, or the general public who review their publicly reported data... If clinicians inappropriately or illogically fear or anticipate negative feedback about the rate of CLABSI in their institutions, they may consciously or subconsciously fail to obtain blood culture results for every patient with a possible or likely BSI. Simply put: no culture equals no infection, using standard definitions of CLABSI. 

At some level, we are all complicit in this. And depending on the action, it may not be the wrong thing to do. In fact, it may benefit the patient. For example, better diagnostic stewardship in the form of appropriately ordering fewer urine cultures not only lowers CAUTI rates but reduces antibiotic utilization with several resultant benefits. Still it's important to note that the primary impetus for this was to lower HAI rates. We take into consideration how a new diagnostic test may impact HAI rates and may even allow that to impact the decision to implement (see an excellent paper by Dan on this here). We may allow clinicians to censor infections that infection preventionists have detected even though the cases meet NHSN definitions. And at the extreme, hospitals may engage in practices that may harm patients in order to reduce publicly reported HAI rates. In a recent publication on how physicians in training view quality initiatives, a dirty secret was elicited from a resident during a focus group at an academic medial center: “There’s like the central line infection protocols…. If you suspect that anybody has any type of bacteremia, you don’t do a blood culture, you just do a urine culture and pull the lines … we just don’t even test for it because the quality improvement then like marks you off.” 

While reading Rachel Aviv's paper, I wondered: Do we ever ignore results (i.e., infection rates) that seem too good to be true like the educational administrators in Atlanta did? Do we critically analyze surprisingly good results to the same degree as we do surprisingly bad results? In Damany Lewis' case did the end justify the means? Is there ever a situation where I could be pushed to a similar point as Lewis?

The Atlanta school system harmed students and teachers in a thoughtless quest to improve quality. There were no winners. Sadly, the response to the cheating scandal was to raise the stakes for test scores even higher. With pay for performance the same is happening in health care.

When prevention success stagnates? Treat the patient!

Prevention is paramount – I do believe this, and I know that is so much of what healthcare epidemiologist strive for; however we often become very myopic and focus exclusively on “modifiable risk factors.” It is refreshing to read a nicely done epidemiologic study to illustrate what an impact the infectious disease community can have by improving the way we approach patient treatment. When reading the recent article in JAMA IM by Michihiko Goto and colleagues I was expecting a nice ecologic study showing an impressionistic picture of how improved treatment processes correlate with improved MRSA bacteremia mortality - but our VA colleagues working with big data have painted more of a realistic 

Le Déjeuner sur l’herbe Painting 

by Édouard Manet, 

1863 Musée d’Orsay, Paris

Google Arts & Culture

than an impressionistic picture. Using the VA database, capturing deaths occurring during both the inpatient stay and the post-discharge period, they quantify improved survival at the patient level is driven by improved processes of care for S. aureus bloodstream infection (Association of Evidence-Based Care Processes With Mortality in Staphylococcus aureus Bacteremia at Veterans Health Administration Hospitals, 2003-2014 JAMA IM).

I have been pushing for transitioning efforts to prevent S. aureus (more specifically MRSA) bacteremia to the post-discharge setting, worried that the recent reductions observed among hospital-onset MRSA BSI are not being realized in the post-acute care setting. We’re getting stuck; in fact we have been stuck for a while at preventing community-associated MRSA BSI (See figure). 

Goto and colleagues provide some clarity to preventing deaths related to MRSA BSI (and S. aureus BSI overall) even during periods of prevention stagnation such as we may be in currently. Of note, the incidences of healthcare-associated and hospital-onset MRSA BSI decreased in VHA hospitals between 2003 and 2014, whereas the incidence of CA bacteremia was stable. This is identical to trends illustrated nationally using CDC's EIP data, suggesting the VA analysis may be reflective of what is going on nationally.

Goto utilized the national Veterans Health Administration (VHA) health care system to first determine how to best risk adjust mortality; and then determine the independent effect of each of three pillars of guideline directed processes of care for managing S. aureus bacteremia (SAB): (1) appropriate antibiotic therapy, (2) echocardiography, and (3) consultation with ID specialists. They report lower risk-adjusted mortality among patients with SAB when they received (1), (2), or (3), and there was a nice dose-response relationship between the number of care processes and mortality. They estimate “57.3% of the decrease in risk-adjusted mortality among patients with SAB between 2003 and 2014 could be attributed to increased use of these evidence-based care processes.”

Their paper also sheds some light on the importance of capturing post-discharge data when quantifying mortality related to processes or infections related to the hospital setting!. Risk-adjusted mortality decreased from 23.5% in 2003 to 18.2% in 2014, regardless of MRSA, MSSA, and place of acquisition (Figure).

From Supplemental Figures, Goto et. al.

I was caught by the discrepancy between these mortality rates and the mortality reported by the CDCs Emerging Infections Program invasive MRSA Surveillance, reported around 12%. The latter is limited to in-hospital or 30 day mortality, whichever comes first. Recent data at IDWeek by one Emerging Infection Program site identified another 30% of deaths among patients with MRSA BSI occurred post-discharge. The Goto paper captures these deaths, making their conclusions more realistic. In addition, their risk adjustment for mortality included over 13 comorbidities, timing of infection, and susceptibility. They did an outstanding job of trying to evaluate the relative importance of each care process while accounting for changes/absence/presence of these underlying predictors of mortality (both inpatient and post-discharge). They even did a sensitivity analysis to account for early deaths, before these care processes could occur. Furthermore, the impact of receiving the care processes was similar regardless if the SAB was hospital-onset or community-onset!

The bottom line – following evidence base care processes does save lives. Their analysis support their conclusion that “there is a need for continued implementation of quality improvement initiatives to increase the adoption of these evidence-based care processes for patients with SAB.” Let’s be bold and call these what they are: performance measures! Here we have a potential metric (proportion of SAB receiving said care process), that are closely linked to improved survival, and can be captured electronically in an objective manner (at least in the VA!) improving the reliability of these metrics across facilities. I was glad to find through a google search that IDSA recently (December 2016) urged CMS to move in this direction -- although the details of the status of this proposed measure (#407) are not clear to me.

While we anticipate novel therapeutics for MRSA BSI including immunotherapy adjuvants or vaccines to become available in the not to distant future; quality improvement efforts in the evidence-based processes of care for SAB now will likely improve our patient’s outcome. I hope we can turn our attention here soon -- and have hospitals rewarded for doing so.

Effect of Nonpayment for Preventable Infections on SSI Rates Following Orthopedic Procedures

The debate regarding the effect of CMS's 2008 policy denying incremental payment for 8 complications of hospital care, also known as never events, is ongoing. Some studies have identified reductions in CLABSI and CAUTI after the policy was implemented, while others failed to find reductions in CLABSI, CAUTI or VAP, using a different dataset and methodology.  The impact of the nonpayment policy change on orthopedic procedures is less well studied.

Authors Jereen Kwong and colleagues published a study in the July ICHE that examined the effect of the policy on SSI following spine fusion, shoulder and elbow arthrodesis and repair, and spinal refusion procedures, but not hip and knee replacements (since they aren't covered under the policy). To determine the impact, they analyzed 20% of all inpatient discharges among patients ages 60 to 80yo using the HCUP National Inpatient Sample from 2000 to 2013. This is an all-payer sample in that it covers patients where Medicare is the primary payer but also non-Medicare populations.

The authors' primary hypothesis was that if the CMS policy had an impact, we would see larger reductions in SSI rates among Medicare vs control, non-Medicare patients. You can probably sense my concern immediately. How would bundles implemented to reduce SSI only have an effect on Medicare patients? It is unlikely that infection preventionists or clinicians would even have knowledge of their payor status. If non-Medicare controls have had the same exposure, they can't be used as controls!

Without getting into the methods details, the authors were expecting larger changes in SSI rates in the Medicare vs non-Medicare populations and they didn't find significant differences RR=0.9, 95% CI 0.8-1.1)  Looking at their Figure 1 below, we can see that SSI rates were slightly higher in Medicare populations (dashed line) vs non-Medicare populations before and after the non-payment policy went into effect. If I were to do this analysis, I would have looked for a change in intercept and/or slope in the SSI rates before vs after the policy combining both payor populations. Looking at the figure, there doesn't seem to be much change after the policy went into effect in either group. So we can agree with the authors that the policy had limited or no impact on SSI rates, but not for the reasons the authors state.

On the positive side, SSI rates have been declining over the entire 14-year study period - so surgeons and infection prevention folks can pat themselves on the back. Keep on doing whatever you've been doing!

The Playing Field is Still Warped . . .

Over the past decade, public reporting of facility-specific HAI performance has had a dramatic impact on infection prevention programs.  The increased awareness of HAI prevention by an increasing diversity of stakeholders (administrators, payors, patients, etc.) has arguably led to increased emphasis on HAI prevention and, in many cases, more resources to infection prevention programs.  These changes were very apparent at my institution where we increased our IP staff from 3 infection preventionists, 2 hospital epidemiologists and one administrative assistant to 9 IPs, 2 data analysts, 1 chart abstractor, 1 program coordinator, and partial support for 4 HEs (not including the antibiotic stewardship program support).  HAI performance is front and center among our annual quality goals, tied to department chair incentives, and the days since the last HAI are posted publically on our inpatient units for all to see.  Most importantly, our frontline healthcare workers understand and routinely discuss what were once surveillance acronyms like "CLABSI" and "CAUTI."  We've seen remarkable reductions in HAIs (and, more importantly, the associated patient harm) during this time (e.g. CLABSI in our ICUs have reduced 80% in the past 8 years). 

Our story is not unique.  Many hospitals have noted marked reductions in HAI rates.  One could argue that many, if not all, of the "low" and even "middle" hanging fruits have been tackled, and we are starting to reach the area where uncontrollable differences in patient risk factors/case mix may lead to different HAI performance across facilities.  With HAI performance tied to increasing financial consequences, however, the need to better insure a level and fair playing field across facilities is growing.  In this context, the recent report from the HHS Office of Inspector General on the CMS HAI reporting is very interesting.  The report focused on the validation of reported HAI data.  They found that while sufficient data were validated (as per regulatory requirements) and 99% of reviewed hospitals passed validation (only 6 failed), concerns were raised regarding how hospitals were selected for validation:

"However, CMS’s approach to selecting hospitals for validation for payment year 2016 made it less likely to identify gaming of quality reporting (i.e., hospitals’ manipulating data to improve their scores). CMS did not include any hospitals in its targeted sample on the basis of their having aberrant data patterns. Targeting hospitals with aberrant patterns for further review could help identify inaccurate reporting and protect the integrity of programs that make quality-based payment adjustments."

Gaming strategies that may be employed include overculturing (to designate an infection as POA), underculturing (if no blood cultures are collected . . . voila! No CLABSIs!), and adjudication/clinician veto ("I know that met the definition for SSI, but it was just a seroma . . . that I treated with antibiotics . . . uh, prophylactically . . . yeah, that's it!).  We have no clue how widespread these practices may be, but the OIG report notes that the current validation strategy should be enhanced to better capture gaming.  With the growing financial consequences placed on HAI prevention, it is paramount that everyone plays fair to better level the playing field.  Now, if we could also get more patient risk factors into the SIR models . . .

Playing Nice: Infection Control and Clinical Microbiology in the Pay-For-Performance Era

As it's probably clear, it's been a great honor for me to work (and blog) with Dan and Mike over the past 8! years. One of the things that stands out when talking shop is their ability to see both sides of an argument even while pushing for the changes they support. Many times, their ability to see both sides clearly is possible because they've lived both sides - Mike has been an ID chief and hospital epidemiologist and is now our CQO and Dan is an ID chief, hospital epidemiologist and clinical microbiologist. You know, if I was a fellow or faculty member looking for a hospital epidemiologist position with great mentorship and support, I would move to Iowa...but I digress.

One specific area where understanding competing goals is critically important is the interplay between the increasing sensitivity and precision of microbiologic tests and the growing pressure to reduce HAI. As you can imagine, with 3% of CMS payments potentially at risk, anything that could impact HAI rates in a negative fashion is bound to be a flashpoint for hospital administrators. With that in mind, I point you to Dan's excellent commentary just published in JCM that examines the implications of advances in microbiological testing on HAI rates and provides specific suggestions for how hospital epi programs and clinical microbiology labs can work together to respond to these changes.

Initially, Dan provides three scenarios where changes in the micro lab could directly impact HAI rates (1) The effect of MALDI-TOF on CLABSI rates (2) The shift from EIA to nucleic-acid amplification tests (NAAT) for C. difficile detection and (3) Pressure to block urine culture ordering to reduce CAUTI. After delving into the current CMS reimbursement landscape, the unintended consequences of improvements in diagnostic testing and the use/misuse of surveillance definitions, he provides six valuable recommendations that clinical microbiology labs (CML) and infection prevention programs (IPP) should consider:

(1) CML leadership should select diagnostic approaches with the goal of improving individual patient outcomes

(2) Hospital and IPP leadership should not pressure the CML to alter diagnostic practices based on the need to demonstrate lower HAI rates for pay-for-performance measures. 

(3) Public health authorities (CDC/NHSN) must be proactive in adjusting HAI metrics to changing CML technology

For recommendations 4-6, you're gonna have to read his commentary. But a hint at #6 -  CML and IPP leadership need to collaborate and advocate for their needs, because, unlike at Iowa, both sides aren't always present in the mind of a single person.

Measurement fatigue: The backlash

Anyone who’s been in the hospital infection prevention business for any length of time is familiar with a specific form of cognitive dissonance. We believe, on the one hand, that the publicly-reported, metric-focused, pay-for-performance (PFP) environment has brought increased resources to infection prevention and resulted in a real decrease in healthcare-associated infections (HAIs); yet we believe, on the other hand, that these high stakes have led to a number of unintended adverse consequences, including gaming of HAI definitions, an unhealthy focus on measures that may not merit the resources and attention, and have engendered cynicism as it becomes apparent that PFP measures may not correlate with actual quality or value.

Over the past week, I’ve read three pieces that make me wonder if we’re reaching a tipping point, as clinicians begin to push back effectively against the proliferation of “measures”, “metrics”, “performance targets” (whatever you wish to call them), in an attempt to seek a balance between them and the words of Francis Peabody, that “the secret of the care of the patient is in caring for the patient.” I’ve pasted some key quotes below from each of these pieces.

First, an excellent opinion piece from Dr. Robert Wachter in the New York Times:

"All of this began innocently enough. But the measurement fad has spun out of control. There are so many different hospital ratings that more than 1,600 medical centers can now lay claim to being included on a “top 100,” “honor roll,” grade “A” or “best” hospitals list. Burnout rates for doctors top 50 percent, far higher than other professions. A 2013 study found that the electronic health record was a dominant culprit. Another 2013 study found that emergency room doctors clicked a mouse 4,000 times during a 10-hour shift. The computer systems have become the dark force behind quality measures….

....Our businesslike efforts to measure and improve quality are now blocking the altruism, indeed the love, that motivates people to enter the helping professions. While we’re figuring out how to get better, we need to tread more lightly in assessing the work of the professionals who practice in our most human and sacred fields."

Next, from a fascinating report of hospitalists unionizing in Oregon:

"To work in a hospital today is to be constantly preoccupied with money, and one of the more grating features as far as the Sacred Heart hospitalists are concerned has been the administration’s celebration of “skin in the game.” That means creating financial incentives for doctors to hit performance targets — like lowering patient’s length of stay and doing well on patient satisfaction surveys. The phrase entered the Sacred Heart lexicon in 2014, but the underlying concept has spread throughout the profession in recent years…. 

…the increasing focus on metrics like readmission rates and hospital-acquired infections had created more work for hospitalists, who are responsible for a lot of documentation."

And finally, from a NEJM piece on “Taylorism” in medicine:

"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."

(This last piece probably should have given a shout-out to a piece by Mike that started by similarly invoking Frederick Winslow Taylor.)

Clamoring for CLAMBI

Last month we blogged on updated NHSN surveillance definitions and we bemoaned the fact that CLAMBIs (central line associated mucosal barrier injury bloodstream infections) are not being separated from CLABSIs for public reporting, and more importantly for the CMS pay-for-performance programs. These infections are particularly common in patients with hematologic malignancies, are due to the translocation of enteric flora into the bloodstream, and unlike true CLABSIs are not preventable. A new paper in Infection Control and Hospital Epidemiology from Northwestern University demonstrates why this is important.

All cases of CLABSI were identified over a 14-month period on 2 inpatient hem/onc/BMT units (72 beds). The cases were further subdivided into "true" CLABSIs (i.e., not associated with mucosal barrier injury) and CLAMBIs. A total of 66 infections were identified, of which 47 (71%) were CLAMBIs. E. coli, enterococci and viridans streptococci accounted for 62% of the pathogens isolated.

The authors note that at the present time CLABSIs identified outside of ICUs are not publicly reported nationally; however, the CLAMBI patients spillover into ICUs. At Northwestern, 12% of ICU CLABSIs were determined to actually be CLAMBIs.

Is it any wonder that tertiary care hospitals are disproportionately affected by CMS penalties? This is just one of many reasons.

SHEA 2015 Update: Abstract Deadline (January 30th), Pro-Con Session and Certificates

SHEA - Orlando, May 14-17, 2015

The SHEA spring meeting in Orlando is really coming together. With the abstract deadline approaching (January 30th) and the full agenda finalized, I wanted to highlight a few things that you should know as you rush to register before the February 13th early registration deadline.

1) Register before February 13th and save $100. If you aren't already a SHEA member - become a member at least 48 hours before registering for the meeting to save even more! Hope to see you in Orlando - May 14-17, 2015.

2) This year, there are two certificate courses that you can select when registering. In addition to the annual SHEA/CDC Training Certificate Course in Healthcare Epidemiology, there is a new SHEA Certificate Course in Post-Acute and Long-Term Care Track. When you register and attend either course, you will receive a certificate in addition to CME/CE. Specific sessions for the SHEA/CDC course (purple) and LTC course (orange) are in the grid below.

3) Finally, I wanted highlight the Friday afternoon (May-15th) Pro-Con session titled "Does Pay for Performance Reduce HAI?" In this session the "Con" side saying the policy doesn't work will be discussed by Grace Lee, MD MPH. As you know, she published an important study on the topic in the NEJM (2012). In that quasi-experimental study, she showed that there were no changes in CLABSI, CAUTI or VAP rates before/after the 2008 nonpayment policy implementation in 398 NHSN hospitals. You can read my blogpost on the study here. On the "Pro" side, Teresa Waters, PhD will discuss her recent JAMA-Internal Medicine study (2015) that showed that the CMS policy was associated with reduced HAI. Using a quasi-experimental design and data from 1381 US hospitals participating in the National Database of Nursing Quality Indicators (NDNQI), she showed that the same CMS policy was associated with an 11% reduction in CLABSI and a 10% reduction in CAUTI but no change in falls or pressure ulcers. So did the policy work or not? Gotta attend SHEA 2015 to find out!

2015 Agenda - Click to enlarge

Does pay for performance in HAI pay off?

The data is piling up suggesting that the CMS policy for nonpayment for HAIs have had little impact on reducing preventable HAIs in acute-care settings. The straw that might break the camel's back is a study in this week's NEJM by Grace Lee and colleagues.  Using a quasi-experimental design and time-series analysis, this AHRQ-funded study looked to see if there was a change in HAI rates after (vs before) the October 2008 nonpayment policy went into effect. 398 NHSN hospital provided data. The results are pretty conclusive: there were no changes in CLABSI, CAUTI or VAP after the implementation of the policy.  In the figures below you can see that things are getting better, just not due to nonpayment.

Of course this is not surprising. Peter McNair published a very nice study in Health Affairs (2009) that estimated that the total financial impact across the entire US would be about $1.1 million annually for six avoidable conditions. When you divide that amount by the number of US hospitals you get...about nothing per hospital. I think CMS might need a bigger stick.

Source: Lee GM et al. NEJM 2012; 367: 1428-37

Did the CMS no-payment rule impact hospital HAI prevention practice?

Beginning in October 2008 CMS stopped reimbursing hospitals for excess costs attributable to CLABSI or CAUTI.  While numerous studies and surveys have linked high compliance with HAI prevention bundles for CLABSI and VAP to reduced infection rates, few studies have looked at whether CMS no payment rules improved HAI prevention process measures.

To answer that question, Sarah Krein at the VA Ann Arbor Healthcare System completed surveys of VA and non-VA hospital HAI prevention practices in 2005 and again in 2009.  Their hypothesis was that if adoption of HAI bundles differed between non-VA and VA facilities, some of this difference could be do to the CMS no payment rules since VA facilities aren't directly affected by CMS rules.

The results are pretty interesting and don't really support any impact from the CMS no payment rules.  For CLABSI, both VA and non-VA hospitals reported significant increases in bundle component use with VA having higher use in both 2005 and 2009 (see graph below).

Similar results were reported for VAP and CAUTI.  The authors conclude by saying that "the CMS payment rule is likely not the primary driver of the increased use of infection prevention practices among US hospitals over the past several years."

Source: Krein et al. JGIM July 2012

My new VAP definition is unstoppable!

As we have blogged on numerous occasions, existing ventilator-associated pneumonia (VAP) definitions (for both clinical and surveillance purposes) are craptastic. In Mike’s recent post about this problem, he calls for CDC to collaborate with IPs and hospital epidemiologists to help develop better definitions. Well, the CDC is doing just that. They have been working with critical care and ID physicians, as well as with some of the CDC Epicenters, to develop and assess a new definition for “VALORI” (Ventilator Associated Lower Respiratory Infection). A simple algorithmic summary of the approach is below, courtesy of Dr. Shelley Magill, who gave an excellent talk at a recent CDC/HHS meeting I attended in DC:

The major objection voiced to the draft VALORI definition is that by removing some aspects that introduce subjectivity, the definition becomes more of a severity of illness measure than a description of what we know clinically to be VAP. The definition also retains some elements that are subjective (or hinge on clinician behavior, such as use of antibiotics), so it isn’t clear if it will have better performance characteristics than the current NHSN definitions.

In my view, we should not use VAP as a quality measure, period. VAP rates should not be compared across hospitals, publicly disclosed, or used in any pay-for-performance schemes. For as soon as they are, hospitals will quickly learn to reduce their rates without doing anything that actually improves patient outcomes (e.g. by narrowly interpreting clinical signs or CXR findings, by seeking consensus among multiple IPs for each case, or by incorporating clinician’s opinions regarding the diagnosis).

In the meantime, we can probably agree on some practices that could be selected for public reporting and benchmarking (i.e. process measures). The practices chosen should be those that are demonstrated to improve meaningful patient outcomes in controlled clinical trials. A great example is this 4-center study of spontaneous awakening + spontaneous breathing trials. The investigators, recognizing the futility of defining VAP, instead demonstrated reductions in ICU days, vent days, hospital days, and mortality in the intervention group.

Obesity and surgical site infections

Abstracts being presented at a national GI meeting this week demonstrate the impact of obesity on surgical complications. One study found that patients with a waist circumference of 45 inches or more were three times more likely to develop a surgical site infection after rectal cancer surgery. The authors of another study demonstrate increased surgical complications in obese patients and go on to criticize pay-for-performance programs that reward surgeons for better outcomes given that a patient's obesity is out of the surgeon's control. Moreover, they claim that since obesity is more common among minority patients, these policies may have adverse unintended consequences that result in discrimination.