Browsing by Subject "Safety-net"

Now showing 1 - 3 of 3
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    MELD-Na Is More Strongly Associated with Risk of Infection and Outcomes Than Other Characteristics of Patients with Cirrhosis
    (Springer Nature, 2021) Fricker, Zachary P.; Mukthinuthalapati, V. V. Pavan Kedar; Akinyeye, Samuel; Chalasani, Naga; Attar, Bashar M.; Balakrishnan, Maya; Ghabril, Marwan; Long, Michelle T.; Medicine, School of Medicine
    Background and aims: The nature and outcomes of infection among patients with cirrhosis in safety-net hospitals are not well described. We aimed to characterize the rate of and risk factors for infection, both present on admission and nosocomial, in this unique population. We hypothesized that infections would be associated with adverse outcomes such as short-term mortality. Methods: We used descriptive statistics to characterize infections within a retrospective cohort characterized previously. We used multivariable logistic regression models to assess potential risk factors for infection and associations with key outcomes such as short-term mortality and length of stay. Results: The study cohort of 1112 patients included 33% women with a mean age of 56 ± 10 years. Infections were common (20%), with respiratory and urinary tract infections the most frequent. We did not observe a difference in the incidence of infection on admission based on patient demographic factors such as race/ethnicity or estimated household income. Infections on admission were associated with greater short-term mortality (12% vs 4% in-hospital and 14% vs 7% 30-day), longer length of stay (6 vs 3 days), intensive care unit admission (28% vs 18%), and acute-on-chronic liver failure (10% vs 2%) (p < 0.01 for all). Nosocomial infections were relatively uncommon (4%), but more frequent among patients admitted to the intensive care unit. Antibiotic resistance was common (38%), but not associated with negative outcomes. Conclusion: We did not identify demographic risk factors for infection, but did confirm its morbid effect among patients with cirrhosis in safety-net hospitals.
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    Poverty, Comorbidity, and Ethnicity: COVID-19 Outcomes in a Safety Net Health System
    (Ethnicity & Disease, Inc., 2022-04-21) Smith, Joseph P.; Kressel, Amy B.; Grout, Randall W.; Weaver, Bree; Cheatham, Megan; Tu, Wanzhu; Li, Ruohong; Crabb, David W.; Harris, Lisa E.; Carlos, William G.; Medicine, School of Medicine
    Objective: To determine if race-ethnicity is correlated with case-fatality rates among low-income patients hospitalized for COVID-19. Research design: Observational cohort study using electronic health record data. Patients: All patients assessed for COVID-19 from March 2020 to January 2021 at one safety net health system. Measures: Patient demographic and clinical characteristics, and hospital care processes and outcomes. Results: Among 25,253 patients assessed for COVID-19, 6,357 (25.2%) were COVID-19 positive: 1,480 (23.3%) hospitalized; 334 (22.6%) required intensive care; and 106 (7.3%) died. More Hispanic patients tested positive (51.8%) than non-Hispanic Black (31.4%) and White patients (16.7%, P<.001]. Hospitalized Hispanic patients were younger, more often uninsured, and less likely to have comorbid conditions. Non-Hispanic Black patients had significantly more diabetes, hypertension, obesity, chronic kidney disease, and asthma (P<.05). Non-Hispanic White patients were older and had more cigarette smoking history, COPD, and cancer. Non-Hispanic White patients were more likely to receive intensive care (29.6% vs 21.1% vs 20.8%, P=.007) and more likely to die (12% vs 7.3% vs 3.5%, P<.001) compared with non-Hispanic Black and Hispanic patients, respectively. Length of stay was similar for all groups. In logistic regression models, Medicaid insurance status independently correlated with hospitalization (OR 3.67, P<.001) while only age (OR 1.076, P<.001) and cerebrovascular disease independently correlated with in-hospital mortality (OR 2.887, P=.002). Conclusions: Observed COVID-19 in-hospital mortality rate was lower than most published rates. Age, but not race-ethnicity, was independently correlated with in-hospital mortality. Safety net health systems are foundational in the care of vulnerable patients suffering from COVID-19, including patients from under-represented and low-income groups.
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    Sensitivity and Specificity of Real-World Social Factor Screening Approaches
    (SpringerLink, 2021-11-12) Vest, Joshua R.; Wu, Wei; Mendonca, Eneida A.; Health Policy and Management, School of Public Health
    Health care organizations are increasingly documenting patients for social risk factors in structured data. Two main approaches to documentation, ICD-10 Z codes and screening questions, face limited adoption and conceptual challenges. This study compared estimates of social risk factors obtained via screening questions and ICD-10 Z diagnoses coding, as used in clinical practice, to estimates from validated survey instruments in a sample of adult primary care and emergency department patients at an urban safety-net health system. Financial strain, transportation barriers, food insecurity, and housing instability were independently assessed using instruments with published reliability and validity. These four social factors were also being collected by the health system in screening questions or could be mapped to ICD-10 Z code diagnosis code concepts. Neither the screening questions nor ICD-10 Z codes performed particularly well in terms of accuracy. For the screening questions, the Area Under the Curve (AUC) scores were 0.609 for financial strain, 0.703 for transportation, 0.698 for food insecurity, and 0.714 for housing instability. For the ICD-10 Z codes, AUC scores tended to be lower in the range of 0.523 to 0.535. For both screening questions and ICD-10 Z codes, the measures were much more specific than sensitive. Under real world conditions, ICD-10 Z codes and screening questions are at the minimal, or below, threshold for being diagnostically useful approaches to identifying patients' social risk factors. Data collection support through information technology or novel approaches combining data sources may be necessary to improve the usefulness of these data.