American Journal of Critical Care最新文献

Background: Critical care nurses are responsible for titration of intravenous vasoactive medications. Before the 2017 publication of The Joint Commission standards requiring nurses to titrate medications within specific protocols, nurses mostly titrated medications autonomously according to clinical judgment. Little is known about how nurses make decisions when titrating vasoactive medications. Additional research on this area of nursing practice is needed to optimize patient outcomes.

Objectives: To better understand critical care nurses' practices, perceptions, and decision-making processes when titrating vasoactive medications.

Methods: The study used a prospective, single-site, convergent mixed-methods, descriptive design. Nurse surveys using the Clinical Decision-Making in Nursing Scale and the Confidence Scale provided data for quantitative analysis. Semistructured interviews provided results for thematic, qualitative analysis.

Results: Nurses' scores for decision-making and confidence when titrating vasoactive medications did not differ significantly between demographic groups. Survey saturation was achieved after 10 interviews, resulting in 4 themes: using the protocol, using knowledge and critical thinking, considering patient history, and collaborating professionally.

Conclusions: Titration protocols are valued but have limitations based on patients' responses and medical history. Vasoactive medication titration requires a robust knowledge base, experience, and collaboration with physicians and coworkers. Similar confidence levels despite different years of experience may be attributed to a strong unit support system or accelerated experiences during the COVID-19 pandemic, when nurses were exposed to more patients receiving vasoactive medications.

Background: Access to complete patient sociodemographic data in a hospital's electronic health record is important for identifying and understanding health inequities and designing interventions to close health care gaps. Through participation in a national safety collaborative, this team identified many patients in intensive care units (ICUs) for whom sociodemographic data (race and ethnicity) were incomplete or missing.

Objectives: To describe the processes the team used to understand how sociodemographic data were being ascertained for children admitted to hospital ICUs; demonstrate how interprofessional care teams can collaborate to create solutions for vulnerable patients; and provide steps that can be used at other hospitals to decrease missing sociodemographic data and deliver equitable care.

Methods: A plan-do-study-act framework guided this initiative to improve collection of data on the race and ethnicity of ICU patients. Via 4 plan-do-study-act cycles, care vulnerabilities and implemented tests of change were evaluated to achieve the goal of capturing sociodemographic data within 72 hours of patient admission.

Results: A new process was developed for patient experience representatives to collect, enter, and track sociodemographic data accurately. Through education and use of a script, documentation rates reached 80% to 100%.

Conclusions: Overcoming barriers in the electronic health record and creating new processes supported the collection of sociodemographic data for children admitted to ICUs. Engaging and acknowledging the value of interprofessional teams was important in this successful groundwork to help deliver equitable care.

Background: Oral bacteria can be pathogenic and may change during hospitalization, potentially increasing risk for complications for older adults, including residents of skilled nursing facilities (SNFs).

Objectives: To compare the oral microbiome at hospital admission by prehospital residence (SNF vs home) in older adults not receiving mechanical ventilation and to assess changes in their oral microbiome during hospitalization.

Methods: This prospective, observational study included 46 hospitalized adults (≥65 years old) not receiving mechanical ventilation, enrolled within 72 hours of hospitalization (15 admitted from SNF, 31 from home). Oral health was assessed with the Oral Health Assessment Tool at baseline and days 3, 5, and 7. Genomic DNA was extracted from unstimulated oral saliva specimens for microbiome profiling using 16S ribosomal RNA sequencing. Taxonomic composition, relative abundance, α-diversity (Shannon Index), and β-diversity (Bray-Curtis dissimilarity) of bacterial communities were determined.

Results: Most patients were female (70%) and White (74%) or Hispanic (11%). Mean age was 78.7 years. More patients admitted from SNFs than from home had cognitive impairment (P < .001), delirium (P = .01), frailty (P < .001), and comorbidities (P = .04). Patients from SNFs had more oral bacteria associated with oral disease, lower α-diversity (P < .001), and higher β-diversity (P = .01). In the 28 study completers, α-diversity altered over time (P < .001). A significant interaction was found between groups after adjusting for covariates (P < .001).

Conclusions: Hospitalized older adults admitted from SNFs experience oral microbial and oral health disparities.

Background: Bedside nurse turnover in the United States is 22.5%, representing a national challenge that has been attributed to poor work environments. Poor work environments result in decreased nurse satisfaction and retention as well as poor patient outcomes. Healthy work environments have the opposite effects.

Objectives: To evaluate the impact of implementation of the American Association of Critical-Care Nurses (AACN) healthy work environment framework in an intensive care unit on work environment scores, turnover, and tenure during a 6-year period.

Methods: A prospective, longitudinal design was used to evaluate implementation of the healthy work environment framework in an intensive care unit in a large academic medical facility. Interventions for each of the 6 healthy work environment standards were carried out. The AACN Healthy Work Environment Assessment Tool was used to measure each standard in 2017, 2019, 2021, and 2023.

Results: No statistically significant differences were found between cohorts. The score for each healthy work environment standard and the overall score increased significantly from 2017 to 2023. Nurse turnover increased during the COVID-19 pandemic but restabilized within 2 years.

Conclusions: Findings from this study suggest that targeted interventions addressing the healthy work environment standards are associated with improved staff satisfaction and reduced turnover. Furthermore, the findings highlight the value of the healthy work environment framework in improving nurse retention.

Unplanned readmissions after sepsis, rates of which range from 17.5% to 32%, pose substantial challenges for health care systems. Associated costs for sepsis surpass those for other critical conditions. Existing readmission risk models rely primarily on clinical indicators, which limits their predictive accuracy for patients with sepsis. This review explores how integrating social determinants of health into readmission models can enhance model precision and applicability for predicting 30-day readmission among sepsis survivors. Although socioeconomic status, neighborhood deprivation, and access to health care are known to influence postdischarge outcomes, these social determinants of health are underused in current risk algorithms. Evidence shows that incorporating social determinants of health into predictive models significantly improves model performance. Furthermore, failure to account for health disparities driven by social determinants of health in high-risk populations can exacerbate existing inequities in health care outcomes. The integration of social determinants of health into sepsis readmission risk models offers a promising avenue for improving prediction accuracy, reducing readmissions, and optimizing care for vulnerable populations. Future research should focus on refining these models and exploring postdischarge monitoring strategies to further mitigate the burden of sepsis readmissions.