Month: July 2011

5% of Patients Spend 50% of Our Healthcare Dollars

Per-capita spending doubled from 1997 through 2009 from $4100 to $8100 – with 5% of patients spending $35,800 on average annually to account for 47.5% of healthcare spending.  Overall, the five most expensive conditions are heart disease, cancer, trauma, mental disorders, and pulmonary conditions.

Unsurprisingly, people over 55 made up the majority of the high spending groups.  Unhappily enough, the authors note a “flattening” of the distribution of spending, where younger individuals are responsible for a greater proportion of the spending.  This is not due to more cost-effective care in the elderly, it’s a result of increasing disease prevalence in the young, primarily attribute to obesity-related diseases such as hypertension, diabetes, hyperlipidemia.

May you live in interesting times, indeed.

“Understanding U.S. Health Care Spending – NIHCM Foundation Data Brief July 2011”
http://www.nihcm.org/images/stories/NIHCM-CostBrief-Email.pdf

Send Children With Negative CTs Home

We should all love PECARN.  I love PECARN (Pediatric Emergency Care Applied Research Network) – and not just because I helped set it up as a research assistant peon before medical school.  I love it because it takes multicenter enrollment cohorts to conduct adequately powered research in a population that is rarely affected by serious morbidity and mortality.

Of 13,543 children with GCS 14 or 15 and a normal CT scan, none needed neurosurgical intervention in their follow-up period.  A small handful of these patients had a repeat CT or MRI for some reason, and between 10-25% of the hospitalized patients and 2-10% of the discharged patients had an abnormal result on repeat imaging.  None led to any intervention…which then, of course, begs the question whether it was appropriate to perform a test that did not result in meaningful change in management.  But, there’s not enough patients in this group to draw conclusions as to whether repeat scans should or should not be performed.

My only caveat – when you take an over-utilized test in which nearly all patients are certainly fine and will continue to be fine, you actually dilute its external validity to the patient population that really matters.  However, even in a higher-risk patient population in which CTs are used far more conservatively, the clinically relevant answer is still going to be same – the only reasonable practice is still going to be to discharge these patients home.

“Do children with blunt head trauma and normal cranial tomography scan results require hospitalization for neurologic observation?”
www.ncbi.nlm.nih.gov/pubmed/21683474

Babesiosis – Scourge of the Lower Hudson Valley

Fascinatingly, babesiosis has suddenly become endemic to New York.  From 6 cases per year between 2001-08, it’s now up to 100+ cases per year in the region.  Still nothing compared to the 4600 cases of Lyme disease, but nearly rivaling the 213 cases of ehrlichiosis.

Hospitalized patients had fever and hemolytic anemia, and were treated with azithromycin and atovaquone.  5.6% case-fatality rate, although, the parasitemia in these cases was exacerbated by underlying medical conditions.  Won’t see this down here in Texas, but the public health surveillance responsibility of Emergency Medicine is always important to remember.

“Babesiosis in Lower Hudson Valley, New York, USA.”
www.cdc.gov/eid/content/17/5/pdfs/10-1334.pdf

If You Don’t Reperfuse STEMI, That’s Bad

I’m not sure why this is earthshaking news – other than some good statisticians had access to some good data.  Of course, that’s pretty much what research is about – have data, will travel.

This JAMA article looks at door-in-door-out time for STEMI at transferring hospitals – and they suggest an association between between quicker transfer times and unadjusted mortality.  There is still some debate regarding how much time to primary PCI matters, but, if you say this in-and-out time is a surrogate marker for time to primary PCI, you could presumably support the hypothesis of rapid PCI mattering.

There are a few interesting nuggets of information in the article – particularly looking at patients for whom the transfer time was exceptionally prolonged.  Essentially, left bundle and patients with ambiguous or non-obvious STEMI were delayed.  I.e., when the diagnosis is hard, it’s hard to make the diagnosis.

As usual, time matters to the individual, but system factors affect many patients.  Mortality for STEMI is improved by faster transport, but you still need to consider the consequences of faster transport.  Reckless abandon towards shoving a semi-stable patient out the door won’t always lead to better outcomes, but, then again, I have worked in some of those hospitals….

“Association of Door-In to Door-Out Time With Reperfusion Delays and Outcomes Among Patients Transferred for Primary Percutaneous Coronary Intervention.”
http://www.ncbi.nlm.nih.gov/pubmed/21693742

Electronic Health Records & Patient Safety

Shameless self-promotion, regretfully.

From my other life as a clinical informatician working on patient safety and human factors as it relates to electronic medical records – my commentary on how electronic medical records might be applied to the 2011 JCHAO National Patient Safety Goals was published today in JAMA.

“Application of Electronic Health Records to the Joint Commission’s 2011 National Patient Safety Goals.”
I am also the spotlight author for the current issue, and you can hear my interview at:

Regression To The Mean

To bias is to be human, and this is a nice review of some of our own intrinsic publication biases.  It’s fun to get excited about a new biomarker promising more sensitive or specific identification of disease, promising to streamline our medical decision making.  And then you get stuck with something like d-Dimer or BNP that gives us information people rarely use appropriately.

These authors pulled “highly-cited” articles evaluating biomarker utility, examined the reported findings, and then pooled the results of subsequent, larger follow-up studies and meta-analyses.  83% of their “highly cited” studies had effect sizes larger than the corresponding meta-analyses, and only 7 of the 35 biomarkers they reviewed even had RR estimates greater than 1.37 in the meta-analyses.

Jerry Hoffman likes to say on Emergency Medical Abstracts that if you just sit back and skeptically critique everything – you’ll end up being right most of the time.  This article demonstrates just how frequently you’ll look smart by not getting overexcited by the most recent fantastic discovery.

“Comparison of Effect Sizes Associated With Biomarkers Reported in Highly Cited Individual Articles and in Subsequent Meta-analyses.”
http://www.ncbi.nlm.nih.gov/pubmed/21632484

CCTA Only Predicts Revascularizations

This is an interesting systematic review of coronary computer tomography angiography that, I think, shows mostly that the endpoints for cardiology studies need to be re-evaluated.  The conclusion that circulates in the new has been that positive CCTA was highly predictive of coronary events – patients with >1 segment of >50% stenosis on CCTA had an 11.9% annualized rate of coronary “events” when compared to the 1.1% annualized rate of patients without any >50% stenosis.  This generates the 10.74 hazard ratio that has been circulating through the press releases trumpeting the predictive value of CCTA.

Unfortunately, this predictive value is a self-fulfilling prophecy because 62% of their “events” were revascularizations.  If you subtract out the portion that went for revascularization, the remaining all-cause mortality, cardiovascular death, nonfatal MI, UA requiring hospitalization, that’s 5% annualized rate.  Still higher than folks without any coronary stenoses at all, but you have to wonder – could we have predicted the population with a 5% cardiovascular morbidity risk without a CCTA?  Does the management decision to perform revascularization confer upon this population a cardiovascular morbidity/mortality benefit?  We are seeing a lot more in the literature showing that medical management is as advantageous as stenting, so, again, I’m not sure what the role of CCTA is – particularly from the Emergency Department.

“Meta-analysis and systematic review of the long-term predictive value of assessment of coronary atherosclerosis by contrast-enhanced coronary computed tomography angiography.”
http://www.ncbi.nlm.nih.gov/pubmed/21658564

Ambulance Diversion Kills People? Maybe?

This article got a ton of press – but it tries to take far too simple an approach to far too complicated an issue.  I’ve done research like this, where you use zip code centroids and calculated distances to nearest hospitals, and it’s just one way a blind man describes an elephant.

These authors look retrospectively at all the acute MIs in four California counties, then looked at hospital daily diversion logs for each day from each of those hospitals – and tried to merge them together to prove that if your nearest hospital was on diversion for a lot of the day you had your acute MI, you had worse outcomes.

Their final analysis says, basically, there’s a 3-5% difference in 30-day, 90-day, and 1-year mortality if your nearest hospital is on diversion >12 hours in a day vs. if your nearest hospital is on diversion <6 hours per day.  The between 6-12 hour diversion cohort performed identically to the <6 hour per day cohort.  So, I don’t know exactly what to make of this.  Their 95% CI almost crosses zero.  Something magical happens at 12 hours that changes your acute MI mortality risk.  So, yes, what the authors are trying to prove is probably true – but this article’s data mining and massage can only hypothesize the association, and doesn’t prove anything.

“Association Between Ambulance Diversion and Survival Among Patients With Acute Myocardial Infarction.”
http://www.ncbi.nlm.nih.gov/pubmed/21666277

Algorithmic Approach To Detect Sepsis Fails

I was asked to blog about this little article – since it lies at the intersection of Emergency Medicine and informatics.

So, that feeling you get when you look at a patient who is obviously ill?  Computers don’t have that yet.  These folks tried to encapsulate that feeling of “sick” vs. “not sick” into the criteria for severe sepsis, which includes SIRS and hypotension.  The hope was that an algorithmic approach that automatically recognized the vital sign and physiologic criteria for SIRS would trigger reminders to clinicians that would spark them to initiate certain quality care processes sooner.
Out of 33,460 patients processed by the system, 398 triggered the system.  Less than half (46%) of those were true positives.  To follow that up, they tried to evaluate their system for sensitivity and specificity by pulling 1 week’s worth of data (1,386 patients) for closer review – and they found the system generated 6 false positives, 7 true positives, and 4 false negatives.  And those numbers speak for themselves.
Looking back at their four quality measures, they all showed a trend towards improvement – unfortunately three of their four quality measures don’t even have a theoretical connection to improved outcomes.  Chest x-ray, blood cultures, and measuring a serum lactate are all clinically relevant in certain situations, but they are all diagnostic and management decisions independent of “quality”.  Antibiotic administration, however, is part of EGDT for sepsis (for what it’s worth), and that trended towards improvement (OR 2.8, CI 0.9 to 8.6).  
But the final killer?  “In approximately half of patients electronically detected, patients had been detected by caregivers earlier”.  So, clinicians were receiving automated pages suggesting they might consider an infectious cause to hypotension, probably while already placing central lines for septic shock.
Great concept – but automated systems just don’t yet have robust, rapid, high-quality inputs like those a clinician gets just by walking in the room.  But, EM physicians in busy departments overlook things – and a well-designed system might in the future help catch some of those misses.
“Prospective Trial of Real-Time Electronic Surveillance to Expedite Early Care of Severe Sepsis.”