All posts by TheTraumaPro

The Next Generation 3D Bioprinter For Skin

3D printing for medical purposes (bioprinting) continues to evolve, and I’ve written a number of posts on this topic over the past 7 years. Skin bioprinting has been around for some time, but it keeps getting more and more sophisticated. Now, appropriate cell lines for the “ink” tanks can be grown in just a few days, and laid down in layers that are getting closer to real skin.

Take a look at this video to see the state of the art:

The next step: adding hair, being able to print large sheets, and ultimately printing directly onto the body!

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Value Of The “Delay To Operating Room” Trauma PI Filter: Part 2

Yesterday, I discussed a paper that tried to show that the “delay to OR” trauma performance improvement (PI) filter was not cost effective. As I mentioned, I’m dubious that the outcomes and information reviewed could realistically demonstrate this.

Today, I’m going to list the parts of the system that this PI filter helps to monitor:

  • Was the patient appropriately triaged as a trauma activation?
  • Was the trauma surgeon called / involved in a timely manner?
  • Was an appropriate physical exam carried out?
  • If needed, was the CT scanner accessible?
  • Did the surgeon make an appropriate clinical decision?
  • If needed, did the backup trauma surgeon arrive in a timely manner?
  • Were there any transport delays to the OR?
  • Was an OR room promptly available?
  • Did the OR backup team arrive within the required time, if needed?
  • Were anesthesia services promptly available?
  • If a failure of nonoperative management occurred:
    • Was the practice guideline followed?
    • Were repeat vitals and physical exam performed and documented?
    • Did any of the other issues listed above occur?

And you may be able to think of even more!

Bottom line: As you can see, this seemingly innocuous filter tests many components within the trauma center. And even if one particular patient who triggers the “delay to OR” filter is lucky enough to escape unharmed, many of the areas listed above can harm other patients who may not trigger it. Actively looking for these issues and fixing them makes your entire trauma program better!

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Value Of The “Delay to Operating Room” Trauma PI Filter: Part 1

This post is a little longer than usual. However, if you have any interest in trauma PI, I recommend you read it through to the very end.

I’ve written a lot about trauma performance improvement (PI) over the years. As many of you know, good PI is complicated yet necessary to run a trauma center that provides optimal care. There are many areas of trauma care that are scrutinized by the PI program on a daily basis. Some of those items are termed “audit filters”, and consist of specific action criteria. If not met, the filter is triggered and the PI program must investigate it.

One of those time-honored filters is “delay to operating room.” Actually, there are two parts to it. One is “trauma laparotomy > 4 hours after patient arrival.” And the other is “trauma laparotomy > 1 hour after patient arrival if hypotensive.”

A paper was recently published questioning the value of the first filter. The contention is that it takes time and money for someone (trauma registrar, nurses, or APPs) to recognize and record the violation, and more time for the trauma program manager, trauma medical director, and Trauma PI Committee to analyze and discuss.

The authors were concerned that this time and money may be mis-spent if the filter violation doesn’t have any real impact on clinical care and outcomes. They looked at 9 years of registry and PI data on initial trauma laparotomies (not reoperations) at their Level I center. They specifically compared the incidence of mortality, complications, and identification of opportunities for improvement in the PI program.

Here are the factoids:

  • 472 patients underwent primary trauma laparotomy during the study, and 23% were flagged as delay to OR (!)
  • There was no difference in mortality or complications between delayed and non-delayed patients
  • There was a trend toward longer hospital length of stay in the delay group (p=0.05)
  • Transfer to a higher level of care was significantly higher (7%) in the delayed patients vs non-delayed (2%).  The authors do not explain this further, although it usually means an unanticipated transfer from ward to ICU.
  • Other audit filters were triggered significantly more often in the delay group, including failed nonoperative management of spleen or liver, delay in diagnosis, and delay in presentation
  • There were significant differences in which surgeons experienced delay to OR, although the incidence of complications was not different

Bottom line: The authors interpret this information one way, and state their belief that these types of filters may no longer be relevant at well-established trauma centers. However, I disagree!

Here is my rationale:

  • The study assumes that deaths, complications, and the presence of identified opportunities for improvement are sensitive enough outcomes. They are not. Hospital length of stay is the only measure that the authors examined that might be related, and it was very close to being significantly higher. And in this day and age of team care, it’s very difficult to say exactly who or what did or did not produce a complication.
  • It also assumes that the adverse outcome would only occur to the involved patient. What if an OR scheduling problem occurred in the audited case, but the patient’s injuries were not severe enough that there was any impact? But the next patient was more severely injured, and the same type of OR scheduling delay occurred. And in this case, significant and severe complications occurred even though they made it into the room in 3 hours and 45 minutes. System problems can hurt other patients, too!
  • The entire study is based on the assumption that the trauma center’s trauma PI program was very effective during the study period. Yet a delay to OR occurred in nearly a quarter of all cases. This is higher than most other centers. It is notoriously difficult to get a sense of how strong the PI program is, other than via verification visits.
  • It also suggests that some practice guidelines either need to be implemented or updated. The “delay to OR” filter was associated with other audit filter violations, especially with failure in nonop management of solid organs and diagnosis delay. Was the approach to liver/spleen management and diagnostic imaging consistent and effective?
  • The differences in delay to OR among the surgeons (range 12-38%) is also unusual. These high and variable numbers suggest the need for further analysis of their cases and performance.

This illustrates my request that you always read the paper, not just the title and conclusion, and think hard about it. I believe that the authors have shown that use of this PI audit filter didn’t make a difference in the outcomes they measured. However, I don’t think they looked at all the right ones. 

My experience has been that this filter is extremely valuable in identifying and fixing system problems. Tomorrow, I’ll provide a list of (nearly) everything that it can measure, and add a few more comments. Click here to read it.

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Reference: “Delay to operating room: fails to identify adverse outcomes at a Level I trauma center. J Trauma 82(2):334-337, 2017.

Amaze Your Friends! The “Greasy Blood” Sign

Today, I’m writing about a clinical observation that I’ve not seen documented in the doctor books. Maybe it has and I’ve missed it. You be the judge.

I call this particular observation the “greasy blood” sign. You have probably seen it before in your practice as a trauma professional. It is present when you see blood (usually venous) coming from an extremity puncture wound or laceration. What makes it unique is the presence of what looks like drops of oil floating on the surface of the blood.

Here are some learning points about this “greasy blood” sign:

  • What you are actually seeing is fat from bone marrow issuing from an underlying fracture
  • It is most commonly seen in blunt trauma with an open fracture
  • It generally comes from femur or tib/fib fractures, although I’ve seen it a few times from upper extremity fractures
  • If it is associated with a penetrating injury, it is always a gunshot and typically the underlying fracture is very comminuted

Have you seen this sign in your practice? If so, tweet or comment and share any nuances you’ve experienced.

Geriatric Week 6: Effect Of An In-Hospital Falls Prevention Program

The Centers for Disease Control (CDC) has developed a neatly packaged falls prevention program that clinicians can apply to their elderly patients. Of course, there’s a cute acronym (STEADI = Stopping Elderly Accidents, Deaths, and Injuries), and a lot of slickly packaged reference material. The trauma group at Parkland wondered if the application of this outpatient program on an inpatient population would be helpful.

They looked at elderly patients (age>65) who were admitted for falls. The patients went through STEADI evaluation and interventions, and were compared with a group of historical controls from the prior year.

Here are the factoids:

  • 218 patients went through the STEADI process, and were compared with 194 controls
  • The usual demographics appeared to be the same in both groups
  • The fall rate in-hospital was 4.1% for both groups (!)
  • The fall recidivism rate (fell after discharge) was also the same (2.8% STEADI vs 2.1% controls)

STEADI consists of a number of assessments, including looking for medical conditions and medications that may

impair mobility, visual problems, gait and balance testing, footwear evaluation, cognitive screening, and home evaluation. This program was modified by the authors for inpatient use, although the exact modifications were not listed in the abstract.

Bottom line: The application of the CDC STEADI program did not appear to affect falls in-hospital or those after discharge. The authors question whether maintaining the resources ($) to implement this program is justified. The paper does raise that question, but it is not clear what modifications were made to the full program to tailor it to an inpatient population. The fact that nearly 1 in 20 elderly patients are falling in the hospital is concerning, with or without STEADI. What the abstract does confirm is that elderly falls are a huge problem. The CDC notes that 1 in every 3 patients age 65 and older will fall each year! Further evaluation of STEADI and other similar programs is essential to decrease the morbidity and mortality of falls in this age group.

Reference: UnSTEADI: Implementation of the CDC fall prevention program does not prevent in-hospital falls or reduce fall recidivism rates. Presented at EAST 2015, Paper 16.