Your New Career in “Waiting Room Medicine”

A few years back, a facetious advertisement in the Canadian Journal of Emergency Medicine promoted the availability of fellowship positions in “Waiting Room Medicine”, a comedic take on the struggles of the specialty to manage increasing patient volume with limited resources. While there are certainly Emergency Departments with ample space and “white glove”-type service – see the for-profit expansion of free-standing EDs in states like Texas – there are also publicly-funded and other EDs that struggle with physical bed space for patients for a variety of reasons.

This study attempts to quantify the effect of an intervention utilized by many overburdened or otherwise saturated EDs – starting the initial evaluation in triage with either provider-directed or protocolized orders. At UCLA/Olive-View, all patients presenting to an already-full ED received an initial rapid evaluation by an attending physician or nurse practitioner. During their 10-month study period, non-pregnant adults with abdominal pain were randomized to either receiving initial evaluation orders following this evaluation, or to be returned to the waiting room to await full evaluation at a later time pending bed availability.

There were 1,691 enrolled and randomized, with approximately 10% excluded from analysis mostly because they left the ED before their evaluation was complete. Overall, the initiation of the work-up in triage saved patients approximately a half-hour, on average, of bedded time in the ED. This was reflected by a similar absolute decrease in overall ED length-of-stay. There were a couple other interesting tidbits unique to their execution:

  • The most profound difference associated with WR medicine was simply blood and urine testing. While imaging could be ordered up front, it was rarely done.
  • Some of the advantages related to the WR blood testing were minimized by ~13% of patients receiving further testing after being bedded in the ED.
  • Patients randomized to WR medicine received, on average, a greater number of diagnostics per patient, probably representing resource waste.

So – yes, this probably accurately reflects the impact of orders placed in triage: some wasted resources based on the initial, incomplete evaluation, with a trade-off of potential time savings. The extent to which your system might benefit from a similar set-up is probably related to your level of chronic bed scarcity.

“Initiating Diagnostic Studies on Patients With Abdominal Pain in the Waiting Room Decreases Time Spent in an Emergency Department Bed: A Randomized Controlled Trial”
http://www.annemergmed.com/article/S0196-0644(16)30360-2/abstract

Excitement and Ennui in the ED

It goes without saying some patient encounters are more energizing and rewarding than others.  As a corollary, some chief complaints similarly suck the joy out of the shift even before beginning the patient encounter.

This entertaining study simply looks for any particular time differential relating to physician self-assignment on the electronic trackboard between presenting chief complaints.  The general gist of this study would be that time-to-assignment reflects a surrogate of a composite of prioritization and/or desirability.

These authors looked at 30,382 presentations unrelated to trauma activations, and there were clear winners and losers.  This figure of the shortest and longest 10 complaints is a fairly concise summary of findings:

door to eval times

Despite consistently longer self-assignment times for certain complaints, the absolute difference in minutes is still quite small.  Furthermore, there are always issues with relying on these time stamps, particularly for higher-acuity patients; the priority of “being at the patient’s bedside” always trumps such housekeeping measures.  I highly doubt ankle sprains and finger injuries are truly seen more quickly than overdoses and stroke symptoms.

Vaginal bleeding, on the other hand … is deservedly pulling up the rear.

“Cherry Picking Patients: Examining the Interval Between Patient Rooming and Resident Self-assignment”
http://www.ncbi.nlm.nih.gov/pubmed/26874338

How Many ED Visits are Truly Inappropriate?

I’ve seen quite a bit of feedback on social media regarding this research letter in JAMA Internal Medicine.

This study evaluated, using National Hospital Ambulatory Medical Care Survey data, the incidence of hospital admission stratified by triage Emergency Severity Index.  They analyzed 59,293 representative visits from the sample and found 7.5% of them, on a weighted basis, were categorized as “non-urgent” – an ESI level 5 or presumed equivalent.  The typical assumption regarding these non-urgent visits is they represent inappropriate Emergency Department utilization.  This study found, however:

“… a nontrivial proportion of ED visits that were deemed nonurgent arrived by ambulance, received diagnostic services, had procedures performed, and were admitted to the hospital, including to critical care units.”

There are always limitations regarding the NHAMCS data, particularly with missing and imputed data.  Based on this, I tend to feel these data lack face validity.  The weighted incidence of admission for non-urgent patients was 4.4% compared with 12.8% of urgent visits, while 0.7% of non-urgent visits were to critical care units compared with 1.3% of urgent visits.  I certainly do not see similar relative proportions of admission, and then to critical care, for level 5 patients in my multiple practice environments.

Regardless, the general implication made by these authors is probably reasonable, refuting usage of ESI triage level 5 to accurately represent inappropriate Emergency Department visits.  However, left equally unstated, is an acknowledgement that ESI also fails to accurately categorize urgent visits – which ties to the rhetoric of trying to conflate “non-urgent” as “inappropriate and “urgent” as “appropriate”.

ESI, as currently implemented, will not be a reliable tool for directing patients to other sources of care – but, with some fuzziness, probably still gives a reasonable estimate of the overall burden of inappropriate ED visits for some policy applications.

“Urgent Care Needs Among Nonurgent Visits to the Emergency Department”
https://www.ncbi.nlm.nih.gov/pubmed/27089549

Patients Packin’ Heat

Does your Emergency Department have a metal detector?  No?  Then, read on.

These authors describe the installation of a typical arch-style metal detector at a single, Midwest, urban teaching hospital.  Between 2011 and 2013, security personnel screened all walk-in guests during hours of operation, ranging from 8h per day at initiation to 16h by the end of the study period.  In just two years of limited operation, they collected:

  • 268 firearms
  • 4,842 knives
  • 512 chemical sprays
  • 275 other weapons (brass knuckles, stun guns, box cutters)

Hospital maintenance also reported finding additional discarded weapons in the landscaping just outside the Emergency Department after the implementation of screening, while triage personnel also anecdotally noted some potential visitors turned away whence they came upon the security station.

Thus, the authors reasonably speculate their findings are representative – or even under-representative – of the weapons present, and concealed, inside their Emergency Department when security screening was absent.  The authors do not simultaneously evaluate any change in reduction in violent events in the Emergency Department, but it’s a fair conclusion their department is now a much safer workplace.

“Weapons retrieved after the implementation of emergency department metal detection.”
http://www.ncbi.nlm.nih.gov/pubmed/26153030

Get to the Choppa! Or … Maybe Not?

Helicopter transport is entrenched in our systematic management of trauma.  It is glamorized on television, and retrospective National Trauma Data Bank studies seem to suggest survival improvement – and those with head injury seem to benefit most.

But, these NTDB studies encompass heterogenous populations and are challenged in creating truly equivalent control groups.  This study, on the other hand, is a single-center experience, allowing greater consistency across divided cohorts.  In a novel approach, these authors collected all HEMS trauma transfer requests to their facility across their 30-county catchement area – and specifically looked at occasions when weather precluded HEMS.  This therefore created two cohorts of patients eligible for HEMS, with a subset that was transported by ALS due to chance events.  The paramedic crews manning the HEMS and ALS transfers were staffed by the same company, and therefore had roughly equivalent training.

This created a cohort of 2,190 HEMS transports and 223 ground transports.  Across ISS, GCS, initial transfusion requirements, and vital signs, the two groups had generally minor differences.  However, there was some potentially important variability of initial operative intervention upon arrival at the Level 1 trauma center – 27.4% of HEMS underwent craniotomy, compared with 15.4% of ALS transfers.  Based on multivariable logistic regression, type of transport did not enter into a best fit model of survival – and, thus, there was no difference (9.0% vs 8.1% mortality) between HEMS or ALS transport of trauma patients, despite the additional hour added from call time to arrival at the Level 1 trauma center.

Unfortunately, there are potentially critical flaws in their methods for patient selection.  They report 3,901 patients had a request for trauma transfer – but the number of patients transferred by HEMS or ALS only sums to 2,398.  An additional 49 were transported by BLS.  Then, another 208 died while awaiting transfer.  How many of these 208 died during weather delays awaiting ALS?  Are those deaths, in some fashion, related to the paucity of craniotomies performed on ALS transports?  And, what of the other 965 patients?

I tend to agree with their conclusion – HEMS is expensive and far over-utilized for patients who receive no particular benefit from the time savings.  However, I’m not sure this analysis includes all the data needed to be reliable evidence.

“When birds can’t fly: An analysis of interfacility ground transport using advanced life support when helicopter emergency medical service is unavailable”
http://www.ncbi.nlm.nih.gov/pubmed/25058262

Why Patients Stop Waiting

“Left without being seen” rates are tracked by every medical director – with fluctuations in this rate frequently resulting in knee-jerk interventions.  However, it’s not necessarily well-understood which patients are actually at risk for LWBS, and why they leave.

This is a Wharton professor who took an operations modeling look at ED LWBS rates, stratified by Emergency Severity Index.  Using timestamp data from 150,000 ED visits, this approach derived four reasonable conclusions:

  • For patients with moderate severity, observing additional patients in the queue lead to increased abandoment.
  • Additional arrivals into the waiting room increased abandonment, while departures decreased abandonment.
  • Watching an arrival “queue-jump” due to higher acuity level increased chance of abandonment.
  • Initiation of diagnostic testing – such as triage protocols – reduced abandonment even if overall wait time was unchanged.

Overall, it’s fascinating to see an somewhat agnostic perspective on the influences on waiting room patients.  The entire report is available as PDF directly from Wharton.

“Waiting Patiently: An Empirical Study of Queue Abandonment in an Emergency Department”
http://knowledge.wharton.upenn.edu/papers/download/06182013_Terwiesch-paper.pdf

Computers – Probably Better Doctors for UTI

Uncomplicated urinary tract infections are probably one of the diagnoses that Emergency Physicians handle the worst – if they come to the ER, they’re likely to get some sort drawn-out testing, whereas, if they went to their regular physician or called the nurse hotline, there would be antibiotics waiting for them at the pharmacy before they finished talking.

This is a prospective study in which patients with possible UTI were referred to a triage kiosk to complete a standardized computer questionnaire.  624 patients with possible UTI interacted with the kiosk – and unfortunately, only 103 qualified for the study by having enough features of typical, low-risk illness.  Patients were then randomized to protocolized antibiotic prescription as reviewed by a triage physician or usual care.

The good news – the kiosk saved a lot of time (89 minutes vs. 146 minutes).  The bad news – there were only 41 patients  followed-up in the intervention group and 26 followed-up in the control group, so we end up with only a tiny number of patients in each arm.  The kiosk group received more antibiotics for negative urine cultures than the control group (93% vs. 67%), so there is some additional element of harm secondary to antibiotic exposure – and, with a limited protocol, there are potential misses – and this study isn’t large enough to identify them.

But, really, uncomplicated, typical UTI symptoms in women shouldn’t be rocket science – and you shouldn’t necessarily be doing any testing.  I would say the computer is a better physician – except, it would be absolutely simple for a physician to simply narrow their approach to match the efficiency of the kiosk with, in theory, some added skill.

“A Randomized Trial of Computer Kiosk–expedited Management of Cystitis in the Emergency Department”

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

Pediatric Septic Shock Protocol

Another sort of goal-directed sepsis study, this time in Pediatrics at Primary Children’s.  They implemented a protocolized triage system in their ED designed explicitly identify more cases of sepsis – which led to increased percentages getting early fluid resuscitation, early lactate level measurements, and more frequently antibiotics in the first three hours.

But the net effect of all these interventions…the only detectable difference in their 345 patient cohort was improved length-of-stay for survivors, from IQR 103-328 hours pre-intervention to IQR 86-214 post-intervention.  Total hospital costs were not significantly different.  No change in mortality – which was already low at 7%.
So, yet again – adherence to “quality measures” has debatable clinical significance.

Massachusetts Health Reform Is “Working”

By some measures, at least, you can claim that the Health Reform is working.  I’ve seen a few articles out there saying it failed, because ED visits continue to rise.  But, if this study is reliable, the increases in ED utilization are a result in increased illness severity, not inability to access a physician.

Non-acute visits for the uninsured/low-income cohort in Massachusetts went down, from 43.8% to 41.2% – a greater decrease as compared to their “control” group of private insurance that is supposedly unaffected by health reform, which decreased from 35.7% to 34.9%.  So, one way to interpret this is that increased access has kept some of the non-urgent uninsured out of the ED.

…but they’re still seeing, by their definition, a solid nearly 40% of patients in our EDs that have less than a 25% of requiring true Emergency Department care.  So things have incrementally improved – but the problem is not simply that a patient has nominal access to a PMD, they actually need to be able to access that PMD on a semi-urgent basis to truly reduce ED utilization…and that PMD needs to be more than simply a revolving door back to the ED.

http://www.ncbi.nlm.nih.gov/pubmed/21570157