Getting rid of the white coat

I was just given a copy of the DecisionHealth publication Inside the Joint Commission.  The March 21 issue includes an article (posted below) that mentions our old white coat contamination study (free full text AJIC 2008). We reported that 23% of white coats were contaminated with S. aureus and 64% of physicians had not washed their white coats in more than a week.

The IJC article quotes the CEO of a healthcare consulting firm who suggests that many clinics have eliminated laundering services for cost-cutting reasons and didn't consider infection control.  The money quote:

"The best solution from an infection-control perspective may be to get rid of the white coat altogether, but “it’s part of the old culture,” Searfoss says, and may be difficult for some physicians to part with."

I couldn't agree more.

Should we track sepsis trends using administrative data?

A: Maybe, but only with extreme caution after adjusting for the influence of policy changes

One of the topics that our group at the University of Iowa is very interested in is the use of administrative databases for tracking the epidemiology of healthcare-associated infections, including those caused by resistant pathogens. Marin Schweitzer reported (open access) in 2011 that the ICD-9 code V09, which was commonly used for tracking MRSA trends, was a poor predictor of actual MRSA infection. More recently, Michi Goto completed a systematic review (free full text) that determined the accuracy of administrative data for surveillance of CAUTI, Clostridium difficile infection (CDI), CLABSI, VAP/VAE, postprocedure pneumonia, MRSA, and surgical site infections (SSIs). He found that administrative data detected CDI and SSI with moderate sensitivity and high specificity. For all other conditions, ICD-9 based algorithms had limited accuracy and utility.

Which brings us to a condition that we haven't much explored - sepsis. Sepsis has been in the news lately, since the Third International Consensus Definitions of Sepsis and Septic Shock (Sepsis-3) were published in February. I've included an image of a monument to a different Third International above for historical purposes. We would expect that these new definition might alter the incidence of sepsis as measured using administrative databases - but only time will tell.

Fortunately, Shruti Gohil and colleagues working with the CDC Prevention Epicenter program just published (free text in CID) an important evaluation of how previous changes in sepsis coding criteria, definitions and reimbursement might have altered sepsis rates. Using retrospective data (2000-2010) from California they determine the association between the release of CMS guidelines of sepsis coding in October 2003 along with the introduction in the MS-DRG reimbursement changes  for sepsis care in October 2007 and sepsis incidence. I've included two figures that showed (A) the change in incidence after each CMS change and (D) mortality per 1000 cases over the same period.

As appears obvious in the top figure, the marked increase in sepsis incidence, 3.6 fold over the study period, is temporally associated changes in CMS coding guidance and reimbursement. And fortunately, mortality appears to be decreasing. The authors suggest that some up-capture of less severely ill septic patients may be driving these findings. They also posit that background increases in sepsis, separate from those associated with CMS changes, could be driven by early recognition programs, such as Surviving Sepsis Campaign (2004), and improved diagnosis. The most important conclusion is this: "it is imperative that reported sepsis rates based on administrative data account for policy-related effects...interpretation of recent epidemiologic trends in sepsis based on administrative data should be approached with caution." 

Guest Post: The National Hand Hygiene Initiative in Australia

This is a guest post by Nicholas Graves, Professor of Health Economics at Institute of Biomedical and Health Innovation, School of Public Health, Queensland University of Technology Queensland Health, Australia. Nick is currently the Academic Director for The Australian Centre for Health Services Innovation (AusHSI) and the Academic Director for the Centre of Research Excellence in Reducing Healthcare Associated Infections (CRE-RHAI), Queensland University of Technology / Institute of Health and Biomedical Innovation.

Between 2009 and 2012 Hand Hygiene Australia implemented an initiative to improve hand hygiene compliance in all Australian hospitals. Federal and state governments provided the funding and there was political support for this high profile patient safety program. My research group at QUT obtained funding of almost $1M in 2012 to evaluate whether it was cost-effective and here are the results just published in PLoS ONE.

We found the annual maintenance costs to be $2.9M per year. This investment of scarce resources prevented 67 cases of S. aureus bloodstream infection and 96 years of life were gained. The cost per one life year gained was $29,700. Hand Hygiene Australia have indicated the program is today likely to be less costly, due to a 50% reduction in their own running costs and that compliance auditors now spend 50% less time on their tasks. Testing these scenarios in our cost-effectiveness model suggest the cost per one life year gained falls to $25,094 and then $18,960.

The only outcome measure for which reliable data were available was S. aureus bloodstream infection. Because SAB is very expensive to treat and has large mortality risk it is a good outcome measure to demonstrate cost-effectiveness. We did evaluate other infection outcomes in a separate paper and found a statistically significant reduction in 11/23 rates, no change for 9/23 and increases for 3/23. Whether we underestimated the health benefits of the initiative by only including SAB outcomes is uncertain.

This was a challenging and difficult study, but that made it interesting. Now that the project has finished, what do I think?

Estimating the value for money of infection prevention programmes is important. Particularly in today's climate where health funding is tight, and there are multiple competing demands on scarce resources. If this Hand Hygiene initiative displaced other infection prevention programmes that deliver larger health benefits for the same or less money, then has been an opportunity cost measurable in health benefits lost.

Rolling out a national program of this complexity requires massive energy. Hand Hygiene Australia did a remarkable job achieving improvements in hand hygiene compliance. They were successful by being single minded and building momentum for the initiative. They did not let obstacles get in the way. Hand Hygiene Australia achieved the task they set themselves.

The timing of our evaluation was wrong. If it were done during a pilot phase then the results might have been useful to change the national initiative. Presenting the study and results after the programme had gained momentum and had political support reduced the usefulness of the findings. 

Doing this project has been interesting and I learned a lot, and I hope the papers and talks I have given are valuable for others interested in estimating the cost-effectiveness of infection prevention programs.

This blog presents my views alone.

Guest Post: Social Media Survey

This is a guest post from Dr. Jon Otter, an epidemiologist focused on Infection Prevention and Control at Imperial College Healthcare NHS Trust in London. Jon has a degree in Microbiology and a PhD in epidemiology. His research interests include the epidemiology of MRSA, CDI and MDR-GNR, the role of contaminated surfaces in transmission, and molecular typing methods including whole genome sequencing. If you're interested in reading more of Jon's excellent musings, he's a blogger at the Reflections on Infection Prevention and Control blog.

Social media (in all its guises) is being used increasingly in our personal and professional lives. The advent of social media brings with it a number of challenges (time-consuming, unhelpful interactions, new liabilities) but also some important potential benefits for healthcare professionals and patients (principally unique opportunities for reaching colleagues and patients). I've been asked to do a talk at ECCMID in Amsterdam next month on the use of social media among healthcare professionals. I was able to find some reasonable data on the use of social media among scientists, but I could find very little data on the use of social media among healthcare professionals in general, and IPC/micro/ID folks in particular. So, I've produced a simple survey to fill this gap, and ask that you share the link (https://www.surveymonkey.co.uk/r/KWYMDPM) with your colleagues so that they can complete it too. It is important that the survey is circulated outside of social media channels, for obvious reasons! I’ll be including the results of the survey in my ECCMID talk, and will make the slides available afterwards here. Many thanks to the Controversies bloggers for the opportunity to tell you about this survey.

(Editor's note: Survey takes 30 seconds so please help Jon out if you can, Thanks!)

Germ theory always wins

This just happened:

"Some West Virginia lawmakers and Capitol staffers had a very bad weekend after drinking raw milk to celebrate a law loosening restrictions on the product. Now state health officials are investigating whether the milk was to blame for their fever, vomiting and diarrhea, and weighing allegations the raw-milk party broke the law."

While public health authorities investigate this mysterious outbreak, let’s take the opportunity to celebrate the life and work of Louis Pasteur.

For more on raw milk, check out this classic from Stephen Colbert.

Moving Beyond the 0.05 p-value

One of my common refrains in research conference and here is that the misuse of p-values has negative public health consequences, a phenomenon I call "death by p-value." Of course my level of frustration with p-values pales in comparison to what well-trained statisticians must feel. This week, the American Statistical Association Board of Directors led by Ronald Wasserstein released a Statement on Statistical Significance and P-values which include six principles on the use and interpretation of p-values. These are:

1.  P-values can indicate how incompatible the data are with a specified statistical model. 
2.  P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone. 
3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold. 
4. Proper inference requires full reporting and transparency. A p-value, or statistical significance, does not measure the size of an effect or the importance of a result. 
5. By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis. 

In addition to the ASA statement I highly recommend the coverage in FiveThirtyEight and Retraction Watch's interview of Professor Wasserstein. We often talk about the post-antibiotic era but even more important for public health is that researchers and journals happily embrace the post p=0.05 era.

Endoscope Reprocessing Practices Survey

The International Society for Chemotherapy (ISC) Infection Prevention & Control Working Group has developed a survey on current endoscope reprocessing practices and they need your help. The working group leadership includes Andreas Voss, Andreas Widmer, Ermira Tartari and Peter Collignon. With the survey they are particularly interested in comparing practices across the globe.

Please consider taking a few minutes and completing the survey for them.

Show me the data!

The following post is from Scott Fridkin, MD, about the new public availability of NHSN antibiotic resistance data:

Finally, some NHSN antibiotic resistance (AR) data for easy access to all! 

Use the HAI Antibiotic Resistance Patient-Safety Atlas to get metrics of AR for the U.S., your region, or your state. It’s currently limited to NHSN defined HAIs, and aggregate measures; but it is dynamic and will grow in size and functionality. Hopefully this will help public health, the public, providers, and researchers to improve patient care. 

Given the public health priority of preventing antibiotic resistance in healthcare, even before the National Action Plan to Combat Antibiotic Resistance was in place, there was a recognition by CDC that it was imperative to make HAI data reported to CDC more accessible to the public, including the public health community, consumers, the press, and industry partners. In addition, academic researchers could benefit from easier access to generate specific hypotheses to test with more definitive research.

Toward this end, CDC finally has expedited the availability of antibiotic resistance data to allow for more time-sensitive evaluations independent of publishing timelines, to allow diverse approaches to ecologic assessments such as geographic comparisons, and to allow evaluation of subsets of data not previously explored in-depth. This month CDC launched the first version of the HAI Antibiotic Resistance Patient Safety Atlas:

As CDC’s National Healthcare Safety Network has migrated from a sentinel surveillance program to a national performance measurement system, the number of facilities reporting has surpassed 4,000 for acute care hospitals, and 15,000 when including dialysis facilities, long term care, inpatient rehabilitation, and long term acute care. The “events” reported into the system have skyrocketed as well. When you consider that the antibiotic resistance data can include up to four pathogens per infection, there is a huge amount of antibiotic resistance data that rarely sees the light of day. In fact, historically all of the antibiotic resistance data reported to NHSN have been released mostly as peer reviewed papers, with very two-dimensional views of the data. This model provided very limited access to the data, diminished relevance when publication lagged several years behind the reporting year, and limited amounts of data presented given the constraints of the paper-based publication model. Although this first version of the Atlas is fairly limited in one’s ability to create customizable queries, it does allow for temporal and geographic evaluation of trends at a superficial level. For now, the identities of facilities are protected and the data are presented at only the national or state level. However, in future iterations more national customized queries will be possible, and perhaps more granular geographic divisions. For now, I urge anyone to access the maps and query functions and let CDC know how to make the site more useful to your professional endeavors.

Exactly how useful these data will be to the public, press, public health, and most importantly patients – is still uncertain. It is a starting point for improved access, transparency, and innovation to advance antibiotic resistance infection prevention – I hope the users of this Atlas can help us make it better over time.

Our slow motion pandemic

    “We keep fantasizing about what will be the next biothreat, the next pandemic. It’s actually already here! We’re going to save our grandparents with triple bypass, but they’re going to die from pneumonia, because we will not have the right antibiotics to save them.”

Dr. Joanne Liu, International President of MSF, on Here’s the Thing.

Today the CDC releases it’s latest edition of Vital Signs, which is dedicated to the problem of antibiotic resistance (AR) among healthcare-associated pathogens. Using data from NHSN, CDC investigators estimate that the likelihood an HAI is caused by a targeted AR pathogen is one in seven in acute care facilities, and one in four in long term acute care.

There's good news in the report—the figure below shows impressive progress in reducing CLABSI rates, and to a lesser extent SSI and C. difficile. CAUTI, though, is a mixed bag (pun intended), and Mike’s covered this ground before. For reasons that Eli and our colleague Dan Livorsi outline here, it’s a shame that CAUTI has become such a prevention focus. Ironically, an unhealthy focus on CAUTI can drive testing and treatment practices that can result in antibiotic overuse, worsening the AR epidemic.

Today the CDC is also releasing the “AR Patient Safety Atlas”, a new web app with interactive data on HAIs caused by AR bacteria. I am about to post a more detailed item from Scott Fridkin about this exciting new development. Stay tuned!