Long Stay Nursing Home Residents with A Urinary Infection Among Black Patients.
According to Cohen et al. (2022), chronically ill people in the United States opt to stay in nursing homes residents because care is assured and easier to deliver in a controlled environment. Nursing home residents take care of all races, ethnicities, and minorities depending on location and cost. Studies show that compared to other races, minority races receive care from low-quality nursing homes that do not meet safety and quality metrics. Therefore, the measure of urinary infections among black patients determines how bad the situation often gets. Data from the Institute of Medicine (IOM) highlights that different components within nursing resident facilities decide racial and ethnic disparities.
Using undeniable data, the white-black gap created by disparities, used in quality measures, shows that the poor care delivered in nursing homes might reflect what is going on in the healthcare sector. The Institute of Medicine uses domains like socioeconomic status, education, community engagement, health and healthcare, and the state of the neighborhood to predict the quality of care delivered. Using these quality measures to disintegrate disparities across facilities in the United States has revealed solutions to eradicate racial and ethnic disparities.
How The Measure Depicts An Existing Disparity And Provide A Clear Explanation Of The Values That Defined The Measure
Urinary tract infections, commonly known as CAUTIs, when acquired within hospital stays, have become common occurrences in nursing homes, often resulting in negative outcomes like hospitalization. Data by Shaikh et al. (2022) highlights that nursing homes transfer more than 25% of their long-stay residents to healthcare facilities to be treated for UTIS at least once. The cost of care is over $14.3 billion, paid using government-funded Medicare programs. The Office of Inspector General has raised concern because most of these cases reveal the quality of care gap affecting the sector. Additionally, researchers from the University of Missouri have shown that repeated transfers are much higher among the black community.
More data revealed that demographics affect repeated transfers because black residents are four times more likely to be transferred to a hospital to be treated for UTIs annually. Repeated hospitalization is harmful because of antibiotic resistance and the weakening of the immune system due to blood infections. It is important to identify the patterns causing the high rate of infections and equip nurses in all facilities with high-level equipment and necessary skills to prevent UTIs.
Analysis Of All the Factors (The 5 SDOH Domains) That Have Contributed to The Disparity.
Economic Stability.
Economic status has become a big predictor of racial and ethnic disparities because minority races are likely to be uninsured, exposed to facilities that are not equipped, or forced to seek low-quality care. After all, that is what is available and accessible. The economic status of an individual can lead to seeking care in under-resourced facilities that do not have the capacity or skill to provide quality care.
Education.
When patients are not exposed to education, they are required to take responsibility for their health; they are likely to fall into the gap of self-care deficiency. The lack of self-care can lead to contracting UTIs and other infections during their stay in nursing homes. Patient and healthcare professional education and skills are a requirement for high-quality care. When they are not available, low-quality care is likely to be delivered.
Health and Healthcare
There is a population-specific difference in care delivery systems, allocation of resources, access and availability of care, and care outcomes. This gap determines an individual’s health and the healthcare services they are likely to receive. When one is in poor health, they are more likely to be vulnerable to infections. With a weakened immunity, the condition is expected to recur when they do not receive proper healthcare. When poor health and factors contributing to poor healthcare collide, those in disadvantaged demographics will likely experience negative outcomes.
Neighborhoods and Built Environments.
Data has shown that environmental stressors like crime, violence, stress, culture, lifestyle, and level of care accessible can determine an individual’s health. The black community finds itself disadvantaged because of the neighborhoods they receive, the culture, and the stress they are exposed to. The care they can access simply because of geographical disparities is likely low quality, which leads to the possibility of catching infections.
Social And Community Context.
The social and community context might look like little to consider, but how people interact with each other creates a connection that improves care quality. When social and community relations are absent, self-care and community care are likely to cause a rise in diseases, infections, and poor health. When that extends to healthcare facilities, it worsens because patients cannot participate in their care or give constructive feedback to improve care.
2 SDOH That Could Be Addressed, Which Would Result in Reducing the Disparity.
Using social and community context coupled with education, the community can use the resources they already have to improve care. With the help of available healthcare leaders, the community can come together to enhance the atmosphere within the facilities and the community at large. They can use their resources to generate policymakers’ support and ensure that education is improved and community engagement is used to influence change. With a united and educated community, changes can be made from the ground up.
References.
Cohen, C. C., Powell, K., Dick, A. W., Stone, P. W., & Alexander, G. L. (2022). The Association Between Nursing Home Information Technology Maturity and Urinary Tract Infection Among Long-Term Residents. Journal of Applied Gerontology: the official journal of the Southern Gerontological Society, 41(7), 1695–1701. https://doi.org/10.1177/07334648221082024
Khor, S., Haupt, E. C., Hahn, E. E., Lyons, L. J. L., Shankaran, V., & Bansal, A. (2023). Racial and Ethnic Bias in Risk Prediction Models for Colorectal Cancer Recurrence When Race and Ethnicity Are Omitted as Predictors. JAMA network open, 6(6), e2318495. https://doi.org/10.1001/jamanetworkopen.2023.18495
Shaikh, N., Lee, M.C., Stokes, L.R. (2022). Reassessment of the Role of Race in Calculating the Risk for Urinary Tract Infection: A Systematic Review and Meta-analysis. JAMA Pediatrics,176(6):569–575. doi:10.1001/jamapediatrics.2022.0700
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