Critical care clinics
-
Critical care clinics · Oct 2024
ReviewHealth Disparities in the Management and Outcomes of Critically Ill Children and Neonates: A Scoping Review.
To date, health disparities in critically ill children have largely been studied within, not across, specific intensive care unit (ICU) settings, thus impeding collaboration which may help advance the care of critically ill children. The aim of this scoping review is to summarize the literature intentionally designed to examine health disparities, across 3 primary ICU settings (neonatal ICU, pediatric ICU, and cardiac ICU) in the United States. We included over 50 studies which describe health disparities across race and/or ethnicity, area-level indices, insurance status, socioeconomic position, language, and distance.
-
Critical care clinics · Oct 2024
ReviewAssessing Social Determinants of Health During Critical Illness: Implications and Methodologies.
A growing body of literature has identified social determinants of health (SDoH) as potential contributors to health disparities in pediatric critical illness. Pediatric critical care providers should use validated screening tools to identify unmet social needs and ensure appropriate referral through multisector partnerships. Pediatric critical care researchers should consider factors outside of race and insurance status and explore the association between neighborhood-level factors and disparate health outcomes during critical illness. Measuring and addressing the SDoH at the individual and neighborhood level are important next steps in mitigating health disparities for critically ill pediatric patients.
-
Critical care clinics · Oct 2024
ReviewA Clinician's Guide to Understanding Bias in Critical Clinical Prediction Models.
This narrative review focuses on the role of clinical prediction models in supporting informed decision-making in critical care, emphasizing their 2 forms: traditional scores and artificial intelligence (AI)-based models. Acknowledging the potential for both types to embed biases, the authors underscore the importance of critical appraisal to increase our trust in models. The authors outline recommendations and critical care examples to manage risk of bias in AI models. The authors advocate for enhanced interdisciplinary training for clinicians, who are encouraged to explore various resources (books, journals, news Web sites, and social media) and events (Datathons) to deepen their understanding of risk of bias.
-
Critical care clinics · Oct 2024
ReviewRacial, Ethnic, and Socioeconomic Differences in Critical Care Near the End of Life: A Narrative Review.
Patients from groups that are racially/ethnically minoritized or of low socioeconomic status receive more intensive care near the end of life, endorse preferences for more life-sustaining treatments, experience lower quality communication from clinicians, and report worse quality of dying than other patients. There are many contributory factors, including system (eg, lack of intensive outpatient symptom management resources), clinician (eg, low-quality serious illness communication), and patient (eg, cultural norms) factors. System and clinician factors contribute to disparities and ought to be remedied, while patient factors simply reflect differences in care and may not be appropriate targets for intervention.
-
Critical care clinics · Oct 2024
ReviewDisparities in Access, Management and Outcomes of Critically Ill Adult Patients with Trauma.
Despite legal protections guaranteeing care for patients with trauma, disparities exist in patient outcomes. We review disparities in patient management and outcomes related to insurance status, race and ethnicity, and gender for patients with trauma in the preadmission, in-hospital, and postdischarge settings. We highlight groups understudied and either underrepresented or unrepresented in national trauma databases-including American Indians/Alaska Natives, non-English preferred patients, and patients with disabilities. We call for more study of these groups and of upstream factors affecting the reviewed demographics to measure and improve outcomes for these vulnerable populations.