Somewhere along the way, someone looked me in the eye and said,
“You’re a mover and a shaker.”

I don’t remember who said it.
I don’t remember where we were or what prompted the comment.
I remember the words.

They landed with the weight of truth. Not the heavy, burdensome kind—but the kind that gently nudges something asleep inside of you and says, “Wake up! This is who you are.”

At the time, I wasn’t particularly feeling like a mover. Or a shaker. I think I was just trying to keep the wheels turning—balancing work, kids, deadlines, laundry. There was nothing glamorous about it. But for whatever reason, that person saw something in me that I hadn’t fully claimed yet. And they named it.




The kind of person who doesn’t just live in the world—they move something in it.

Those words stayed with me. They still do. They became a quiet permission slip I still carry around, reminding me that I can create change, challenge systems, and build something better. Even when I don’t feel bold, even when I feel tired.

And the more I think about it, the more I realize that one sentence shaped something within me that has led me to succeed time and time again. All because someone once spoke life-giving words into my sleeping soul.

There’s a kind of magic in the words we speak over others—not the flattery kind, but the kind that calls people into who they’re becoming.

We all remember words that changed us.
Maybe it was a teacher who said, “You’re a writer.”
Maybe a supervisor who told you, “People follow you, even when you don’t realize it.”
Maybe it was a friend who simply whispered, “You’re stronger than you know.”

Those words stick not because they’re fancy, but because they’re formative. They shape how we begin to see ourselves.

And the truth is, we all have that power. To speak into someone’s life. To point to a small seed in their soil and say, “Look. Something is growing here.”

It doesn’t take a grand gesture to change someone’s trajectory. More often than not, it’s a simple, intentional sentence—spoken at the right time—that becomes a turning point. Whether you’re a leader, a colleague, a parent, or just a person passing through someone else’s day, you all have the power to change lives through speaking into those lives. The steps below aren’t a script. They’re an invitation—a way to approach everyday interactions with just a little more presence—and a lot more impact.

Look for what’s true and emerging in others.

Most of us walk around with gifts we haven’t named yet—strengths we’ve never noticed. But when someone else names what they see in us, it sows within us a seed of potential; the potential of becoming. Be the kind of person who notices what’s becoming.

We assume people already know. We think that they hear it all the time. However, the truth is that most of us are starving for encouragement. So, if you see it, speak it. Please don’t wait for someone else to catalyze their growth. Please don’t assume they already know what’s there.

Generic praise is nice. But true and targeted encouragement is powerful. Instead of “You’re doing great,” try:

“The way you stayed calm and asked that question in the meeting—it shifted the whole tone of the room.”

You might never know what your words did for someone. Say them anyway. Encouragement works like water on dry ground. You don’t see the roots grow—but they do.

What Does Any of This Have to Do With Infection Prevention?

You might be wondering to yourself, “What does any of this have to do with health care or infection prevention?” Well, in a word, 

In our roles as infection preventionists, we often spend so much time correcting, redirecting, and reminding. “Please wear your PPE correctly.” “Don’t forget to sanitize between rooms.” “We need better hand hygiene compliance on 3 West.”

Necessary? Yes.
Powerful? Not always.

What if, alongside the endless corrections, we offered specific encouragement? What if we named the good in others?

“You have a remarkable way of commanding a room. People listen to you when you speak.”
“I admire your commitment to protecting our patients. Your actions are inspiring to others.” 
“Your consistency is what keeps this place safe, and it leads others to do the same.”

When we speak the truth in

, people listen differently. They stand taller. They start to 

 that they are part of something meaningful because they

I still don’t know who first called me a mover and a shaker. But I know I’ve never forgotten those words. When work is difficult and challenges arise, I quietly think to myself, “You are a mover and a shaker. You 

 move this mountain.”
That person and their words had a profound impact on my career and life. Now, I try to be that person for others because the world is loud with criticism and far too quiet when it comes to naming what’s good.

So today, someone out there needs your words. Can you find them? Can you name what you see within them that they might not yet see within themselves?

“You light up a room.”
“You make people feel safe.”



Say the words. Plant the seed. Watch them grow.

Articles

In a world full of corrections and checklists, don’t underestimate the quiet power of encouragement. One sentence—spoken with sincerity—can spark confidence, courage, and change. Infection preventionists do more than monitor safety; they shape culture. So today, go beyond reminders. Speak life. Name the good. Someone’s future may depend on it.

IP LifeLine: You're a Mover and a Shaker 

 remains a problematic bug in hospital settings, contributing to a range of nosocomial infections. In the US, multidrug-resistant 

 causes 13% to 19% of health care–acquired infections (HAIs) annually.

 The pathogen can survive harsh conditions, and it has devised virulence mechanisms and resistance to a broad range of antibiotics. This is particularly the case for the strains that carry the Verona integron–encoded metallo-β-lactamase (VIM), an enzyme that confers resistance to carbapenems, often reserved as last-line antibiotic therapy. Multiple cases of VIM-positive 

VIM-PA), have been reported in intensive care units (ICUs), raising concerns for the patients and the staff. The mortality rate of these infections is quite alarming, usually exceeding 30%, depending on the site of infection and the underlying condition of the patient.

The nature of the clinical cases often managed in the ICU and the therapeutic procedures carried out in this setting can create a breeding ground for formidable disease-causing microorganisms, such as 

. Long hospital stays, severe illnesses, and deranged immune defenses are characteristic features of the typical ICU patient. These may encourage infection with VIM-producing 

 or even silent colonization, which can remain undetected until clinical deterioration or transmission to other patients occurs.

To develop effective guidelines for infection prevention and manage outbreaks, a deeper understanding of the risk factors that specifically lead to VIM-PA colonization and infection is needed. This piece highlights some of the environmental, patient-related, and provider-related issues in the ICU that can contribute to the growth of these superbugs.

The environment in the ICU is a key contributor to colonization and infection by VIM-PA. In a retrospective study conducted in the Netherlands, researchers found that persistent environmental contamination by 

 was the primary source of bacterial transmission. In the study, 86.3% of the transmissions were attributed to a contaminated environment, compared with 13.7% of the cases that were attributed to cross-transmission.

, routine disinfection protocols are sometimes insufficient, primarily due to the virulence and antimicrobial resistance patterns exhibited by these bacteria, particularly in biofilm formation. 

 can adhere to surfaces and employ other mechanisms such as quorum sensing and growth inhibition to perpetuate the biofilm and promote tolerance to antibacterial agents.

In the ICU environment, numerous high-touch surfaces can serve as reservoirs for VIM-producing 

. Most health care workers will be concerned about countertops and medical trolleys, while ventilator buttons, bed rails, and infusion stands may receive less attention during routine cleaning despite being potent niches for these bugs.Ventilator circuits, bronchoscopes, urinary catheters, and extracorporeal membrane oxygenation lines can also harbor biofilms that protect VIM-PA from both immune clearance and disinfectants. If not rigorously sterilized or replaced, these devices can act as persistent sources of infection.

 thrives in a wet environment, and sink drains provide a preferred niche for these bacteria, with splashes traveling a distance of up to 1 m from the basin.

 A study in a Swedish hospital established that sink drains harbored VIM-PA, and dispersing the biofilms in the drainage system led to control of an outbreak.

In another study in Switzerland, the researchers went a step further and removed all sinks near the patients in the ICU, adopting a completely waterless model.

 They decided to go completely waterless after the initial attempts to replace the sink siphons led to reinfections in just a few weeks. In the waterless model, a handwashing sink was placed outside the ICU rooms, and disposable wipes and single-use hygiene kits were used. Oral medication was dissolved in spring water. Only after these interventions was the outbreak of the multidrug-resistant 

These studies underscore the importance of reconsidering the drainage architecture of ICUs and hospitals at large.

High patient-to-nurse ratios, poor hand hygiene, and a lack of adherence to personal protective equipment regulations among health care workers contribute to horizontal transmission. Additionally, family members and other visitors, especially in neonatal or long-term ICUs, can serve as vectors if proper infection control measures are not enforced.

Prior Antibiotic Use and Prior Hospitalization

Patients with prior antibiotic exposure, especially to carbapenems or fluoroquinolones, are at a higher risk of VIM-PA colonization and infection. This is because overuse or prolonged use of these broad-spectrum antibacterial agents favors the colonization by resistant strains. The use of these drugs often leads to the elimination of susceptible strains, leaving behind undetectable and resistant strains that are then spread from patient to patient or colonize the environment. Antibiotic use within 3 months of admission to the ICU puts patients at risk of developing carbapenem-resistant 

Patients previously admitted to a hospital before their current ICU admission are more likely to develop VIM-PA infection and colonization due to the increased risk of exposure to these bacteria.

 Similarly, longer admission periods in the ICU can lead to a higher risk of colonization and infection. In the same breadth, long-term care facilities are also known to harbor many drug-resistant bacteria.

Patients coming to the ICU with an already established 

 colonization are more likely to have positive cultures later. In a study at the University of Maryland Medical Center, patients were tested for 

 colonization at admission and monitored. Patients colonized with 

 were over 6 times more likely to have a subsequent positive clinical culture than patients who were initially not colonized.

Advanced age is a known risk factor for developing HAIs mainly because of weakened immune function. Additionally, people of advanced age are more likely to have comorbidities and frequent exposure to health care settings, which directly translates to more exposure to disease-causing microorganisms. A 2010 study found that people above 86 years of age in a long-term care facility were more likely to develop drug-resistant strains of bacteria.

In the ICU, older patients often spend longer periods on the ventilator. They are also likely to undergo more invasive procedures, leading to a higher risk of exposure to pathogens such as VIM-PA.

A study conducted in 2 district hospitals in the United Kingdom identified anemia as a risk factor for 

 infection, with 53% of cases having hemoglobin levels below 11.5 g/dL.

This can be attributed to the fact that anemia is often associated with other factors, such as poor nutritional status, which can compromise the immune system. Anemia can also be caused by conditions such as bone marrow suppression, inflammatory conditions, and even cancer, which can all predispose patients to infections by drug-resistant bacteria.

The severity of a patient’s illness correlates with the risk of acquiring VIM-PA. Patients with severe disease are more likely to undergo more invasive procedures, stay longer on the ventilator in the ICU, and receive more broad-spectrum antibiotics, all of which can increase the risk of colonization by VIM-PA.

Studies have shown that specific clinical conditions are more likely to be associated with 

 colonization. A 2006 study established that neurological disease, urinary tract infections, and renal failure were significant risk factors for metallo-β-lactamase(MBL) 

Chronic wounds, surgical sites, and burns provide a direct entry point for 

. The organism’s ability to form biofilms on necrotic or moist tissue surfaces allows it to persist despite topical or systemic treatment. This is particularly problematic in ICUs, where pressure ulcers and surgical wounds are common.

Posttransplant patients are also at higher risk of developing carbapenem-resistant 

 infections when they are admitted to the ICU. This is due to their immunosuppressed states and the prolonged use of antibiotics. Studies have established that both solid organ and stem cell recipients are at a higher risk of colonization and infection by drug-resistant bacteria.

Breast Milk Feeding Practices in Neonatal ICUs

Breast milk is a rich source of nutrition that also helps boost a newborn’s immune system. However, in cases where breast milk is expressed, proper handling and hygiene should be observed to protect the baby from exposure to pathogens. In the neonatal ICU (NICU), for example, improper handling of expressed breast milk can lead to colonization by bacteria.

In a study conducted in an Italian NICU, breast milk feeding was associated with colonization by a well-defined, imipenem-resistant, MBL-

Colonization and infection with VIM-PA in the ICU are driven by an interplay of patient factors and environmental persistence, as well as clinical practice gaps, including inadequate handwashing techniques and suboptimal disinfection protocols. The nature of care offered in the ICU is inherently risky, meaning patients are constantly at risk of developing infections with resistant strains of bacteria. The invasive procedures and prolonged hospital stays, in addition to the nature of diseases, call for vigilance and appropriate infection prevention and control measures to disrupt the growth of disease-causing organisms that might be lurking.

1. Raman G, Avendano EE, Chan J, Merchant S, Puzniak L. Risk factors for hospitalized patients with resistant or multidrug-resistant 

 infections: a systematic review and meta-analysis. 

. 2018;7:79. doi:10.1186/s13756-018-0370-9

2. Peña C, Suarez C, Ocampo-Sosa A, et al; Spanish Network for Research in Infectious Diseases (REIPI). Effect of adequate single-drug vs combination antimicrobial therapy on mortality in 

 bloodstream infections: a post hoc analysis of a prospective cohort. 

. 2013;57(2):208-216. doi:10.1093/cid/cit223

3. Pham TM, Büchler AC, Voor In ‘t Holt AF, et al. Routes of transmission of VIM-positive 

 in the adult intensive care unit-analysis of 9 years of surveillance at a university hospital using a mathematical model. 

. 2022;11(1):55. doi:10.1186/s13756-022-01095-x

4. Hota S, Hirji Z, Stockton K, et al. Outbreak of multidrug-resistant 

 colonization and infection secondary to imperfect intensive care unit room design. 

5. Fraenkel C-J, Starlander G, Tano E, Sütterlin S, Melhus Å. The first Swedish outbreak with VIM-2-producing 

, occurring between 2006 and 2007, was probably due to contaminated hospital sinks. 

. 2023;11(4):974. doi:10.3390/microorganisms11040974

6. Schärer V, Meier MT, Schuepbach RA, et al. An intensive care unit outbreak with multi-drug-resistant 

. 2023;139:161-167. doi:10.1016/j.jhin.2023.06.013

7. Chiotos K, Tamma PD, Flett KB, et al. Multicenter study of the risk factors for colonization or infection with carbapenem-resistant 

. 2017;61(12):e01440-17. doi:10.1128/AAC.01440-17

8. Harris AD, Jackson SS, Robinson G, et al. 

 colonization in the intensive care unit: prevalence, risk factors, and clinical outcomes. 

. 2016;37(5):544-548. doi:10.1017/ice.2015.346

9. Ghibu L, Miftode E, Teodor A, Bejan C, Dorobăţ CM. Factori de risc pentru infecţiile cu 

10. Zavascki AP, Barth AL, Gaspareto PB, et al. Risk factors for nosocomial infections due to 

 producing metallo-beta-lactamase in two tertiary-care teaching hospitals. 

. 2006;58(4):882-885. doi:10.1093/jac/dkl327

11. Giannella M, Bartoletti M, Conti M, Righi E. Carbapenemase-producing Enterobacteriaceae in transplant patients. 

. 2021;76(suppl 1):i27-i39. doi:10.1093/jac/dkaa495

12. Freire MP, Camargo CH, Bubach L, et al. Recurrent outbreak of carbapenem-resistant IMP-1-producing 

 in kidney transplant recipients: the impact of prolonged patient colonization. 

. 2025;27(1):e14414. doi:10.1111/tid.14414

13. Mammina C, Di Carlo P, Cipolla D, et al. Nosocomial colonization due to imipenem-resistant 

 epidemiologically linked to breast milk feeding in a neonatal intensive care unit. 

. 2008;29(12):1486-1492. doi:10.1111/j.1745-7254.2008.00892.x

VIM-producing Pseudomonas aeruginosa isn’t just surviving in ICUs; it’s thriving. With mortality rates exceeding 30%, colonization risks hiding in drains, devices, and even donor milk, IPs must take proactive steps to outsmart this pathogen. Now is the time to double down on environmental controls, risk factor recognition, and surveillance strategies. Let’s break the biofilm cycle before the next outbreak takes root.

Unmasking VIM Pseudomonas aeruginosa: Threats in Critical Care

Artificial intelligence (AI) and machine learning (ML) software have experienced significant growth across various industries, including health care. These developing technologies already have the potential to detect complications caused by infection quickly and accurately. However, integrating these new devices into an established regulatory process has proven challenging. Additionally, there are concerns about trusting devices that produce unpredictable outputs. Due to their distinct characteristics, specific medical devices utilizing AI/ML technology must undergo an adjusted regulatory process to be marketed.

AI-based software within the medical device industry is on the rise, with over 1,015 devices with AI-enabled software authorized for marketing in the US by the FDA as of March 25, 2025.

 Included on the FDA’s AI/ML-Enabled Medical Devices List

 is the Sepsis ImmunoScore. Approved in April 2024, this was the first FDA-authorized AI software designed to aid in the prediction and diagnosis of sepsis.

 The Sepsis ImmunoScore uses AI/ML software to pull inputs that include demographic data, vital signs, and blood culture results from the electronic medical record, enabling the ImmunoScore to output the risk for the presence or development of sepsis for that patient within 24 hours.

In a prospective study published in November 2024, it was explained that the AI algorithm for ImmunoScore was developed through a derivation cohort of patients and was assessed for accuracy on both internal and external cohorts.

 The results of this study concluded that the ImmunoScore had a “high overall diagnostic accuracy for predicting sepsis” and was “highly predictive” of secondary outcomes, including “in-hospital mortality, length of stay, ICU [intensive care unit] admission within 24 hours, use of mechanical ventilation within 24 hours, and use of vasopressors within 24 hours.” The ImmunoScore is just 1 example of AI’s potential to assist health care professionals through informed decision-making. Although the capabilities of these devices seem promising, concerns regarding their trustworthiness must be addressed by regulatory bodies and standardization organizations.

Artificial Intelligence/Machine Learning Software

Understanding the differences among various types of AI software is essential for recognizing the need for heightened regulation of devices that utilize these systems. In its second white paper, the Association for the Advancement of Medical Instrumentation (AAMI)/British Standards Institution (BSI) Initiative on AI provides an overview of AI systems used in the medical device industry.

 This includes rules-based AI, systems that “mimic human behavior-making decisions by applying static rules to arrive at predictable decisions,”

 compared with data-driven machine learning systems that can learn from inputs and make judgments.

 Data-driven ML systems can be further categorized into locked ML models and continuous learning models.

 In locked machine learning models, the algorithms and outputs will not change automatically and require external approval to change,

 whereas continuous learning models can automatically adjust their algorithms and update outputs based on changes.

 From a regulatory perspective, these continuous learning models are the most challenging, as the algorithms may change automatically, making it difficult to predict outcomes.

A significant concern with AI in the medical device industry, particularly with continuous learning models, is trusting these unpredictable systems with tasks that were previously performed by humans, which can pose a risk to patient safety if they fail to perform as expected. The AAMI/BSI Initiative recognizes this unique situation by describing how, in the medical device industry, trust is generally gained not only by an overview of the device’s mechanisms and technologies but also by validating that the device produces “reliable and predictable outputs.”

 This is where concern arises for many: If AI/ML devices can change their outputs after validation, how can they be trusted to produce those reliable and predictable outputs?

Some considerations from AAMI and BSI addressing this concern include that the input data used to train algorithms should be “predefined, relevant, and appropriate” and that performance metrics should be implemented to allow for live monitoring against predicted outputs.

 Guidance from the FDA has also suggested that developers describe anticipated algorithm changes before marketing the device,

 reducing the potential of unknown and unpredictable outputs once in use.

Regulation of AI/ML-based Medical Devices

Just as there are different types of AI technologies, from a regulatory perspective, there are also other types of software that can be used in (or as) medical devices. According to the FDA, the primary types of software within the medical device industry include Software 

 medical devices, and software used in the manufacturing process of a device.

 When AI/ML software is “intended to treat, diagnose, cure, mitigate, or prevent disease or other conditions,” it is considered a medical device and referred to as SaMD by the FDA and International Medical Device Regulators Forum .

Furthermore, medical devices (including SaMD) can be categorized into 3 classes by the FDA. These classifications give insight into the risk the device poses to the patient. For example, a Class I device poses a low risk to the patient, whereas a Class III device poses the greatest risk. The FDA has different premarket submission requirements depending on the device’s classification. If a device is classified as Class I or II, a 510(k) submission is required to market the device (excluding exemptions).

 However, because Class III devices “support or sustain human life, are of substantial importance in preventing impairment of human health, or present a potential, unreasonable risk of illness or injury,”

and pose the highest risk to the patient, these devices require a different type of premarket submission. Class III devices require a premarket approval application (PMA) by the FDA, providing scientific evidence that the device would be safe for use.

The unique capabilities of AI/ML SaMD to adapt and change its algorithms after the PMA process has been completed present new challenges for regulating these devices. In 2019, the FDA released a discussion paper and requested feedback reviewing the process for modifications to AI/ML-based SaMD.

 The paper notes that the FDA expects algorithm changes to be anticipated and described in the premarket submission.

 Additionally, some of these algorithm changes would still require a premarket review.

Based on the feedback provided in response to the request from the discussion paper, the FDA released an action plan for AI/ML SaMD.

 In this action plan, predetermined change control plans (PCCPs) were discussed, specifically, how anticipated and prespecified changes may be captured in a PCCP, which may avoid the need for a new PMA every time an algorithm change occurs.

 This approach can be more efficient, allowing changes to be anticipated and described where a PMA may not be needed. Of course, changes that would pose heightened risk or differ from those described in a PCCP may still require a PMA, as previously noted. The action plan also mentions that “FDA liaisons participate in the standardization efforts of [the AAMI] AI Committee to address the risk management of AI-driven medical devices,”

 and that the FDA is committed to continue working with organizations such as AAMI and BSI to address AI/ML developments.

In 2023, the FDA published a set of guiding principles for PCCPs.

 According to AAMI Array author Eric Henry, as of October 2024, the only AI/ML-specific guidance published by the FDA was the draft guidance for PCCPs.

 In December 2024, the FDA published its final guidance for marketing submission recommendations for PCCPs for AI-enabled devices.

In January 2025, the FDA published an additional draft guidance intended to “[provide] lifecycle management and marketing submission recommendations consistent with a TPLC [Total Product Life Cycle] approach for AI-enabled devices,”

which also references the final guidance for submission recommendations for PCCPs. The FDA requested comments for this draft guidance to be submitted by April 7, 2025.

AI and ML technology have the potential to become an important asset for use in future medical devices. As the use of this technology grows, health care professionals must continue to advocate for the appropriate regulation of these devices. Advocacy for an adjusted regulatory process for these devices enables industry professionals to continually embrace evolving technology while maintaining confidence that these devices are safe and reliable for use.

Artificial intelligence and machine learning (AI/ML)-enabled medical devices. FDA. March 25, 2025. Accessed May 22, 2025. 

https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices

Device classification under Section 513(f)(2)(de novo). Updated June 2, 2025. Accessed May 22, 2025. 

https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/denovo.cfm?id=DEN230036

Bhargava A, López-Espina C, Schmalz L, et al. FDA-authorized AI/ML tool for sepsis prediction: development and validation. 

Machine Learning AI in Medical Devices: Adapting Regulatory Frameworks and Standards to Ensure Safety and Performance

Reddy S. Global harmonization of artificial intelligence-enabled software as a medical device regulation: addressing challenges and unifying standards. 

. 2024;3(1):100191. doi:10.1016/j.mcpdig.2024.100191

Software as a Medical Device (SAMD). FDA. December 4, 2018. Accessed May 22, 2025. 

https://www.fda.gov/medical-devices/digital-health-center-excellence/software-medical-device-samd

Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD)

https://www.fda.gov/media/122535/download?attachment

Classify your medical device. FDA. February 7, 2020. Accessed May 22, 2025. 

https://www.fda.gov/medical-devices/overview-device-regulation/classify-your-medical-device

Premarket approval (PMA). FDA. May 16, 2019. Accessed May 22, 2025. 

https://www.fda.gov/medical-devices/premarket-submissions-selecting-and-preparing-correct-submission/premarket-approval-pma

Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan

https://www.fda.gov/media/145022/download?attachment

Henry E. AI/ML in medical devices: US & EU regulatory perspectives. AAMI

October 23, 2024. Accessed May 22, 2025. 

https://array.aami.org/content/news/ai-ml-medical-devices-us-eu-regulatory-perspectives

Predetermined change control plans for machine learning-enabled medical devices: guiding principles. FDA. December 3, 2024. Accessed May 22, 2025. 

https://www.fda.gov/medical-devices/software-medical-device-samd/predetermined-change-control-plans-machine-learning-enabled-medical-devices-guiding-principles

Marketing submission recommendations for a predetermined change control plan for artificial intelligence-enabled device software functions. FDA. December 3, 2024. Accessed May 22, 2025. 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/marketing-submission-recommendations-predetermined-change-control-plan-artificial-intelligence

Artificial intelligence-enabled device software functions: lifecycle management and marketing submission recommendations. FDA. January 7, 2025. Accessed May 22, 2025. 

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/artificial-intelligence-enabled-device-software-functions-lifecycle-management-and-marketing

Artificial intelligence-enabled device software functions: lifecycle management and marketing submission recommendations; draft guidance for industry and food and drug administration staff; availability. 

https://www.federalregister.gov/documents/2025/01/07/2024-31543/artificial-intelligence-enabled-device-software-functions-lifecycle-management-and-marketing

Artificial intelligence may be revolutionizing sepsis detection and diagnosis, but can we trust it without strong regulatory guardrails? As AI/ML-enabled medical devices rapidly evolve, IPs must stay informed and involved to ensure safety keeps pace with innovation. Let’s take a closer look at how to advocate for innovative safe implementation.

Balancing Regulation and Risk of AI and Machine Learning Software in Medical Devices

Let’s face it—Infection prevention can be serious business. From health care-associated infections to hand hygiene adherence and everything in between, your daily work keeps patients safe and hospitals running. But who says we can’t have a little fun along the way?

Whether you're a word nerd, a crossword connoisseur, or just someone who loves a good challenge, we’ve got something for you: The very first 

! It’s your chance to test your infection prevention IQ, unwind from your day, and maybe even pick up a new acronym or 2! 

This puzzle is packed with clues covering all things infection prevention—sterile processing, isolation precautions, antimicrobial stewardship, and yes, even a little personal protection equipment fashion. It's a fun, brain-boosting way to review key terms, share a laugh with your team, and maybe even spark a few debates over whether “contact time” really deserves 9 across.

No need for scrubs or gloves—just grab a pen, pull up a chair, and dive in.

Download the crossword now and challenge your colleagues.


See who finishes first, who gets stumped by “biofilm,” and who’s secretly a puzzle prodigy. Bonus points if you print it out for the break room!

Let’s connect through a bit of competition—and remind ourselves that even in a world of compliance checklists and policy updates, there’s always room for a little play.

Because at the end of the day, staying sharp helps us stay safe—and there’s no better way to do that than with a few clever clues and a well-earned smile.

Check out our first IPC Crossword Challenge.

Infection Prevention Connection: An IPC Crossword Challenge

This article is the first in a series of the discussion 

 had about this study with Cori L. Ofstead, MSPH; Brandon M. Gantt, MHA, CRCST, CHL, CER, LSSGBH; and Jill E. Holdsworth, MS, CIC, FAPIC, NREMT, CRCST, CHL.

In a collaborative research effort between hospital-based infection preventionists (IPs), sterile processing professionals, and epidemiologists, the Lumen 2.0 study revealed unsettling truths about the hidden state of surgical instrument cleanliness. Using borescope technology, the research team visually inspected orthopedic and neurosurgical instruments and found retained debris, corrosion, and physical defects in every instrument studied, regardless of whether the manufacturers’ instructions for use (IFUs) had been followed.

This research, presented at the 2025 Healthcare Sterile Processing Association (HSPA) Annual Conference & Expo held in Louisville, Kentucky, from April 26 to 29, builds on earlier studies and raises serious questions about the adequacy of current cleaning validation standards and the feasibility of real-world implementation of IFUs. The study’s findings echo previous pilot research conducted at LifeBridge Health in Baltimore, Maryland, which also discovered widespread contamination in arthroscopic shavers and suction tips, even after cleaning.

The current study extended the investigation to different institutions and manufacturers, using a rigorous multistep cleaning protocol followed by repeated inspections. The results showed not only persistent contamination but also degradation of instruments after only a few uses.

To learn more about the presentation and the study behind it, 

) interviewed Cori L. Ofstead, MSPH, the president and CEO of Ofstead & Associates, Inc, Bloomington, Minnesota; Brandon M. Gantt, MHA, CRCST, CHL, CER, LSSGBH, manager of the sterile processing department education and training at Emory Healthcare; and Jill E. Holdsworth, MS, CIC, FAPIC, NREMT, CRCST, CHL, infection preventionist in Atlanta, Georgia.

Other authors of the study are Abigail G. Smart, MPH, and Larry A. Lamb, AGTS, both with Ofstead & Associates, Inc; and Kevin M. Bush, Jr, DHSc, EdD, FACHE, CPPS, CPHRM, CPHQ, CIC, Perioperative Enterprise Department, Emory Healthcare, Tucker, Georgia.

: What was your presentation about at the HSPA Annual Conference? How does it differ from the one you will give with Jill Holdsworth at the Association for Professionals in Infection Control and Epidemiology (APIC) 2025 Annual Conference & Expo?

 My colleagues from Emory [University Hospital Midtown] and I were presenting case studies from the 

 At the APIC conference, we’ll present case studies and share numerical data findings from the study. [The name of the APIC presentation was “Infection Preventionists Using Borescopes: New Discoveries in Ortho and Neurosurgery Instruments.”]

The study itself, “Unseen Threats: Lumens 2.0 Study Reveals the Hidden Challenges of Cleaning Lumened Surgical Instruments,” explored the architecture and cleanliness of instruments used for orthopedic neurosurgery and [ear, nose, and throat] surgeries. We accomplished this by inspecting lumens using borescopes. An important aspect of this study is that we aimed to engage in a collaborative effort with my team, which includes research epidemiologists working closely with hospital-based infection preventionists (IPs) and sterile processing professionals, to conduct groundbreaking research that combines all 3 domains. It turned out beautifully, achieving something none of us could have done alone. That was a particularly cool feature of the study.

: What inspired the Lumens 2.0 study, and what specific gaps in cleaning validation were you aiming to address?

, PhD. Conventional wisdom has been that endoscopes are the most difficult instruments to clean, but Terra has been doing some work recently, where she suggests that other instruments also have device design features that impact their cleanability. She has 

: the lumens, the dead ends, rough surfaces, nooks and crannies, holes, hinges, all those things.

 This raised an issue for us regarding the architecture of instruments that aren’t endoscopes, which aren’t visible. Are they as complex? Are they as difficult, or maybe more difficult, to clean?

We’re using her research as a springboard, and we began by conducting a small pilot study in collaboration with Steven Adams, BA, RN, CER, CHL, CRCST, CIS. He was the president of HSPA [then IAHCSMM] from 2016 to 2018, and he’s an operating room nurse by training. However, he has been running sterile processing for a long time and teaches at the community college, where he developed his own program to get sterile processing technicians certified within his institution.

Two years ago, we looked at arthroscopic shavers and suction tips. We did that because 

A groundbreaking study presented at HSPA25 and APIC25 exposed hidden contamination lurking inside orthopedic and neurosurgical instruments—even after cleaning. The Lumens 2.0 research highlights why infection prevention must look deeper than surface-level protocols.

Infection Control Today, July/August 2025 (Vol. 29 No.4)

IP LifeLine: You're a Mover and a Shaker

Unmasking VIM Pseudomonas aeruginosa: Threats in Critical Care

Balancing Regulation and Risk of AI and Machine Learning Software in Medical Devices

Infection Prevention Connection: An IPC Crossword Challenge

Lumens 2.0 Study Results: Borescopes Reveal Hidden Challenges of Cleaning Lumened Surgical Instruments