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PATIENT CONNECTION OPERATING ROOM


Predicting pressure injury in critical care patients: A machine-learning model Big data and machine learning helped develop a model for predicting risk for pressure injuries in critical care patients, according to new research published in American Journal of Critical Care (AJCC). In “Predicting Pressure Injury in Critical Care


Patients: A Machine-Learning Model,” the research team examined five years of data on patients admitted to the adult surgical or surgi- cal cardiovascular intensive care units at the University of Utah Hospital in Salt Lake City. Among the sample of 6,376 patients, hospital- acquired pressure injuries of stage 1 or greater developed in 516 patients, and injuries of stage 2 or greater developed in 257 patients. With these two outcome variables identi-


fied, the researchers used machine learning to effectively and efficiently look at the large amount of clinical data readily available in the patient records and examine the relationships among the available predictor variables. They used a technique called random forest, which is relatively unaffected by moderate correlations among variables, an important characteristic because correlations among clinical variables are common in health research. The researchers believe their study is the


only one in which machine learning was used to predict development of pressure injuries in critical care patients. “Current risk-assessment tools classify most


critical are patients as high risk for developing pressure injuries and therefore do not provide a way to differentiate among critical care patients in terms of pressure injury risk,” said Principal investigator Jenny Alderden, PhD, APRN, CCRN, CCNS. “Eventually, our model may offer ad- ditional insight to clinicians as they develop a plan of care for patients at highest risk and identify those who would benefit most from interventions that are not financially feasible for every patient.” Among the variables that were most impor-


tant according to the model’s mean decrease in accuracy was time required for surgery, an element that has not been well studied as a potential contributor to risk for pressure injury. Body mass index, hemoglobin level, creatinine level and age were also ranked as important variables. The mean decrease in accuracy, which reflects complex relationships among variables, is assessed by temporarily removing a variable from the analysis and evaluating the change in model performance. Eventually, the model could help identify


which patients are at the greatest risk for devel- oping pressure injuries and would benefit from interventions such as specialty beds or more frequent skin inspection.


Clean and clear Clinicians create better outcomes with proper


air and water quality management by Valerie J. Dimond


ir- and water-borne diseases are on a sharp increase according to the Centers for Disease Control and Prevention (CDC). One in four patients who contract the serious respiratory ill- ness called Legionaires’ disease during a hospital stay, for example, ends up dying. This is according to CDC’s latest Vital Signs report. But the report also states that most problems leading to U.S. healthcare- associated outbreaks of Legionnaires’ disease could be prevented with effective water management.


A


“Unfortunately for the patients, em- ployees and guests of these facilities who are by nature the susceptible population — aged, immunosuppressed — exposure to these waters inoculated with Legionella can cause this ever more prevalent ill- ness,” said John Baum, CWT, President, Craft Products Company, Inc. Pathogens in the air are also of grave concern and a major reason why patients develop surgical site infections, one of the leading causes of longer hospital stays and preventable readmissions. “Airborne pathogens are a well-doc- umented source of surgical site infections, accounting for 20 percent of hospital- acquired infections (HAIs), including in the operating room,” said Kas- sandra Keller, Senior Vice Presi- dent, Business Development, WellAir. “Influ- enza, norovirus, MRSA, C. diff, A. niger, and formalde- hyde are just some of the


viruses, bacteria, mold, and VOCs that healthcare facilities have to tackle. Given that pathogens are continually entering the air, it’s important to implement a solu- tion that can be deployed on a 24/7 basis.


16 December 2018 • HEALTHCARE PURCHASING NEWS • hpnonline.com


Airing on the side of caution Where does your facility stand in the fight against these air and water invad- ers? Hopefully in the proactive category in which healthcare organizations make it a top priority to invest in products and practices that have been proven to keep patients safe from air- and water-borne pathogens, especially those who are most vulnerable to exposure. What follows are a few examples of how to stay protected from the potential dangers of contami- nated air and water.


”WellAir’s plasma technology disin-


fects the air safely, down to the DNA level, 24 hours a day, with no human effort’” explained Keller about her com- pany’s air quality improvement product. “Thus, it is the ideal complement to solutions such as HEPA filtration that a healthcare facility may already have in place. All of our products require little to no maintenance and effectively reduce viruses, bacteria, fungal spores, and neutralize odor-causing VOCs.” She said researchers in Sweden are conduct- ing the first double-blind, randomized, controlled trial to validate the WellAir technology’s ability to significantly reduce incidence of surgical site in- fections over a three-year pe- riod on mostly orthopedic surgical pa-


tients across six hospitals. Keller also


WellAir’s plasma technology portfolio


discussed other solutions includ- ing a new product


called the Defend 1050 which “uses ultra-low energy plasma technology and a multi-stage high performance filter system from Camfil to reduce infection, adsorb odors, neutralize volatile organic


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