Using POCUS in the emergency department (ED) to scan patients with suspected deep vein thrombosis (DVT) cut their length of stay in the ED in half.
Reducing hospital length of stay is one of the holy grails of healthcare quality improvement.
- It’s not only more expensive to keep patients in the hospital longer, but it can expose them to morbidities like hospital-acquired infections.
Patients admitted with suspected DVT often receive ultrasound scans performed by radiologists or sonographers to determine whether the blood clot is at risk of breaking off – a possibly fatal result.
- But this requires a referral to the radiology department. What if emergency physicians performed the scans themselves with POCUS?
To answer this question, researchers at this week’s European Emergency Medicine Conference presented results from a study of 93 patients at two hospitals in Finland.
- From October 2017 to October 2019, patients presenting at the ED received POCUS scans from emergency doctors trained on the devices.
Results were compared to 135 control patients who got usual care and were sent directly to radiology departments for ultrasound.
- Researchers found that POCUS reduced ED length of stay from 4.5 hours to 2.3 hours, a drop of 52%.
Researchers described the findings as “convincing,” especially as they occurred at two different facilities. The results also answer a recent study that found POCUS only affected length of stay when performed on the night shift.
Radiology might not be so happy to see patient referrals diverted from their department, but the results are yet another feather in the cap for POCUS, which continues to show that – when in the right hands – it can have a big impact on healthcare quality.
Performing routine third-trimester ultrasound scans on pregnant women could help identify breech pregnancies, giving women the opportunity to consider alternative birth options. UK researchers in PLOS Medicine said the impact was found with both conventional and POCUS ultrasound scanners.
While the incidence of breech presentation at full term is only 3-4%, when breech births do occur they can result in higher morbidity and mortality for both babies and mothers.
In the UK, third-trimester ultrasound scans aren’t routinely performed for low-risk women, missing a chance to give them other options like Cesarean birth.
- Therefore, researchers investigated the effectiveness and impact of these scans at two hospitals, one that used conventional ultrasound scanners and the other employing POCUS units (GE HealthCare’s Vscan Air).
- At the POCUS facility, scans were typically performed by trained midwives. Women were scanned between 2016 to 2021 at both hospitals.
Performing routine ultrasound scans at 36 weeks reduced the incidence of undiagnosed breech presentation by 71% at the hospital using conventional ultrasound and 69% at the POCUS hospital.
- The rate of undiagnosed breech presentation dropped from 14.2% to 2.8% with conventional ultrasound and from 16.2% to 3.5% with POCUS.
- The scans also had an impact on babies’ health. Infants born at either facility had less likelihood of a lower Apgar score (<7) five minutes after birth, and babies were less likely to be sent to the neonatal care unit.
The researchers believe their findings suggest a revision of the UK’s clinical guidelines, which don’t currently call for routine third-trimester ultrasound scans for low-risk women. With respect to POCUS, they said their research was the first to investigate the technology for diagnosing fetal presentation, and their findings support wider use of POCUS in areas where conventional ultrasound isn’t available.
What’s really exciting about this study are the findings about POCUS. Maternal-fetal complications are a huge problem in developing countries and places with less access to imaging technology. POCUS scanners could be used by trained personnel like midwives – perhaps with AI assistance – to identify problems before birth.
Exo took a big step towards making its handheld ultrasounds easier to use and adopt, acquiring AI startup Medo AI. Although unexpected, this is a logical and potentially significant acquisition that deserves a deeper look…
Exo plans to integrate Medo’s Sweep AI technology into its ultrasound platform, forecasting that this hardware-software combination will streamline Exo POCUS adoption among clinicians who lack ultrasound training/experience.
- Medo’s automated image acquisition and interpretation software has clearance for two exams (thyroid nodule assessments, developmental hip dysplasia screening), and it has more AI modules in development.
Exo didn’t disclose acquisition costs, but Medo AI is relatively modest in size (23 employees on LinkedIn, no public info on VC rounds) and it’s unclear if it had any other bidders.
- Either way, Exo can probably afford it following its $220M Series C in July 2021 (total funding now >$320m), especially considering that Medo’s use case directly supports Exo’s core strategy of expanding POCUS to more clinicians.
Some might point out how this acquisition continues 2022’s AI shakeup, which brought three other AI acquisitions (Aidence & Quantib by RadNet; Nines by Sirona) and at least two strategic pivots (MaxQ AI & Kheiron).
- That said, this is the first AI acquisition by a hardware vendor and it doesn’t represent the type of segment consolidation that everyone keeps forecasting.
Exo’s Medo acquisition does introduce a potential shift in the way handheld ultrasound vendors might approach expanding their AI software stack, after historically focusing on a mix of partnerships and in-house development.
Handheld ultrasound is perhaps the only medical imaging product segment that includes an even mix of the industry’s largest OEMs and extremely well-funded startups, setting the stage for fierce competition.
That competition is even stronger when you consider that the handheld ultrasound segment’s primary market (point-of-care clinicians) is still early in its adoption curve, which places a big target on any products that could make handheld ultrasounds easier to use and adopt (like Medo AI).