Faculty Bibliography

GENERAL PURPOSE/UNASSIGNED:To present the 2021 update of the Wound Bed Preparation paradigm. TARGET AUDIENCE/BACKGROUND:This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES/UNASSIGNED:After participating in this educational activity, the participant will: 1. Apply wound assessment strategies. 2. Identify patient concerns about wound care. 3. Select management options for healable, nonhealable, and maintenance wounds.

Patients in critical care units have a multitude of diseases and conditions that contribute to their illness and as such are susceptible to comorbid conditions such as heel pressure injuries. Prevention is a key strategy to avoid heel pressure injury occurrence. Risk factor identification can help a clinician identify those patients at risk for a heel pressure injury requiring timely prevention strategies. The purpose of this article is to raise awareness regarding the critical care patient's vulnerability to heel pressure injuries and strategies that can help avoid their occurrence or expedite their healing if occur.

Pediatric pressure injuries continue to be a worldwide healthcare problem. Studying pediatric pressure injury point prevalence may provide more insight into the problem and drive prevention strategies for at-risk pediatric patients, a truly vulnerable population. This article reports 10 years of longitudinal pediatric pressure injury prevalence data and demographics from around the world.

OBJECTIVE:To assess pressure injury knowledge of Skin Care Council nursing members using the Pieper-Zulkowski Pressure Ulcer Knowledge Test (PZ-PUKT), to design an educational intervention informed by the results of the baseline assessment, and to evaluate the effect of the intervention. METHODS:This was a single-group pretest-posttest project conducted in an urban, academic, tertiary medical center from January to August 2017. Participants were measured on the pretest, received the intervention, and then were reevaluated on the posttest 3 months later. Pretest results informed the design of the intervention, which was a 1-day interactive, targeted educational program referred to as the "Skin Care Council Boot Camp." Paired-samples t tests were conducted to examine differences between pretest and posttest scores on the PZ-PUKT overall and in each test section. RESULTS:Seventy-seven participants enrolled in the project and completed the pretest. Of those, 58 (75.3%) were retained through the intervention and the posttest evaluation. Participants had a mean pretest score of 78.9 and a mean posttest score of 85.3. There were significant mean differences among pretest and posttest PZ-PUKT scores: 6.4 (t = 9.419, P < .001) overall; 4.6 (t = 5.356, P < .001) in the Prevention/Risk category; 4.1 (t = 3.668, P < .001) in the Staging category; and 10.5 (t = 7.938, P < .001) in the Wound Description category. CONCLUSIONS:By testing pressure injury knowledge before developing a program, investigators created a tailored, education program that addressed knowledge gaps. Posttest results provided insight into the program's success and opportunities for future improvement.

OBJECTIVE:The purpose of this research was to build on previous work regarding predictive factors of acute skin failure (ASF) in the critically ill population. METHODS:Researchers conducted a retrospective case-control study with a main and validation analysis. Data were extracted from the New York Statewide Planning and Research Cooperative System. For the main analysis, there were 415 cases with a hospital-acquired pressure injury (HAPI) and 194,872 controls without. Researchers then randomly selected 100 cases with a HAPIs and 300 controls without for the validation analysis. A step-up logistic regression model was used. Researchers generated receiver operating characteristic curves for both the main and validation analyses, assessing the overall utility of the regression model. RESULTS:Eleven variables were significantly and independently related to ASF: renal failure (odds ratio [OR], 1.4, P = .003), respiratory failure (OR, 2.2; P = < .001), arterial disease (OR, 2.4; P = .001), impaired nutrition (OR, 2.3; P = < .001), sepsis (OR, 2.2; P = < .001), septic shock (OR, 2.3; P = < .001), mechanical ventilation (OR, 2.5; P = < .001), vascular surgery (OR, 2.2; P = .02), orthopedic surgery (OR, 3.4; P = < .001), peripheral necrosis (OR, 2.5; P = .003), and general surgery (OR, 3.8; P = < .001). The areas under the curve for the main and validation analyses were 0.864 and 0.861, respectively. CONCLUSIONS:The final model supports previous work and is consistent with the current definition of ASF in the setting of critical illness.

Objective Hospital-acquired pressure injuries harm over 2.5 million patients at a U.S. cost of $26.8 billion. Sub-epidermal moisture scanning technology supports clinicians to anatomically identify locations at-risk of developing hospital-acquired pressure injuries. Our objective was to evaluate the cost-effectiveness of adopting sub-epidermal moisture scanners in comparison to existing hospital-acquired pressure injury prevention guidelines structured around subjective risk assessments. Methods A Markov cohort model was developed to analyze the cost-effectiveness of sub-epidermal moisture scanners in comparison to existing prevention guidelines, based on current clinical trial data from the U.S. health care sector perspective in the acute, acute rehabilitation and skilled nursing facility settings. A hypothetical cohort was simulated over a time horizon of one year. An incremental cost-effectiveness ratio was measured using U.S. dollars per quality-adjusted life year at a willingness-to-pay threshold of $100,000/quality-adjusted life year, and uncertainty was tested using probabilistic sensitivity analysis. Results Integration of sub-epidermal moisture scanners yielded cost-savings of $4054 and 0.35 quality-adjusted life years gained per acute care admission, suggesting that sub-epidermal moisture scanners are a dominant strategy compared to standard care and producing a net monetary benefit of $39,335. For every 1000 admissions in high-risk acute care, sub-epidermal moisture scanners could avert around seven hospital-acquired pressure injury-related deaths and decrease hospital-acquired pressure injury-related re-hospitalization by approximately 206 bed-days. Conclusions Acute care, acute rehabilitation and skilled nursing settings that adopt sub-epidermal moisture technology could achieve a return on investment in less than one year. Providers may want to consider these types of technology that aid clinical judgment with objective measures of risk in quality improvement bundles

OBJECTIVE:To replicate previous research that found four independent and significant predictors of heel pressure injuries (HPIs) in hospitalized patients using a larger and more diverse patient population. METHODS:Researchers conducted a retrospective, case-control study with a main and a validation analysis (N = 1,937). The main analysis had 1,697 patients: 323 patients who had HPIs and 1,374 who did not. The validation analysis had 240 patients: 80 patients who developed HPIs and 160 who did not. Researchers used a series of diagnosis codes to define variables associated with an HPI. Data were extracted from the New York Statewide Planning and Research Cooperative System for January 2014 to June 2015. Study authors conducted a series of forward stepwise logistic regression analyses for both samples to select the variables that were significantly and independently associated with the development of an HPI in a multivariable setting. Researchers generated a receiver operating characteristic curve using the final model to assess the regression model's ability to predict HPI development. RESULTS:Seven variables were significant and independent predictors associated with HPIs: diabetes mellitus, vascular disease, perfusion issues, impaired nutrition, age, mechanical ventilation, and surgery. The receiver operating characteristic curve demonstrated predictive accuracy of the model. CONCLUSIONS:Beyond a risk assessment scale, providers should consider other factors, such as comorbidities, which can predispose patients to HPI development.