The Local Market of Major Teaching Hospitals.

OBJECTIVE: The purpose of this study was to describe the local communities served by major teaching hospitals. METHODS: Using a dataset of hospitals around the United States provided by the Association of American Medical Colleges, we identified major teaching hospitals (MTHs) using the Association of American Medical Colleges' definition of those with an intern-to-resident bed ratio above 0.25 and more than 100 beds. We defined the local geographic market surrounding these hospitals as the Dartmouth Atlas hospital service area (HSA). Using MATLAB R2020b software, data from each ZIP Code Tabulation Area from the US Census Bureau's 2019 American Community Survey 5-Year Estimate Data tables were grouped by HSA and attributed to each MTH. One-sample t tests were used to evaluate for statistical differences between the HSAs and the US average data. We further stratified the data into regions as defined by the US Census Bureau: West, Midwest, Northeast, and South. One-sample t tests were used to evaluate for statistical differences between MTH HSA regional populations with their respective US regional population. RESULTS: The local population surrounding 299 unique MTHs covered 180 HSAs and was 57% White, 51% female, 14% older than 65 years old, 37% with public insurance coverage, 12% with any disability, and 40% with at least a bachelor's degree. Compared with the overall US population, HSAs surrounding MTHs had higher percentages of female residents, Black/African American residents, and residents enrolled in Medicare. In contrast, these communities also showed higher average household and per capita income, higher percentages of bachelor's degree attainment, and lower rates of any disability or Medicaid insurance. CONCLUSIONS: Our analysis suggests that the local population surrounding MTHs is representative of the wide-ranging ethnic and economic diversity of the US population that is advantaged in some ways and disadvantaged in others. MTHs continue to play an important role in caring for a diverse population. To support and improve policy related to the reimbursement of uncompensated care and care of underserved populations, researchers and policy makers must work to better delineate and make transparent local hospital markets.

What Should "Shopping" Look Like in Actual Practice?

In health care, lack of transparency about the cost of health care services to patients during clinical encounters has contributed to increased costs and high out-of-pocket expenses. Federal policy has responded to the need for more transparency and spurred discussion about ethics and the clinician's role in being transparent with patients at the point of service. This article investigates and encourages state, private market, and federal policy efforts to address what health care costs patients. This article also applies the ethical framework of principlism to cases and considers what a "shoppable service" model would demand of clinicians in practice.

All That Coughs Is Not COVID.

We report the case of a woman from the Bronx, New York, who presented to the emergency department (ED) in June 2020 with a febrile respiratory illness resembling coronavirus disease 2019 (COVID-19) but was ultimately diagnosed with Legionnaires' disease (LD). New York City (NYC) rapidly became an epicenter of the global COVID-19 pandemic in 2020. In the years since the pandemic started, variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have recurred in multiple waves and remain an important cause of viral respiratory illness. The bacteria Legionella pneumophila is often under-recognized as a cause of community-acquired pneumonia, yet it recurs each year in clusters, outbreaks, or as sporadic infections. Pneumonia caused by SARS-CoV-2 and Legionella can present similarly and may not be readily distinguished in the absence of diagnostic testing.

Quantitative analysis of competitive cytokine signaling predicts tissue thresholds for the propagation of macrophage activation.

Toll-like receptor (TLR) signaling regulates macrophage activation and effector cytokine propagation in the constrained environment of a tissue. In macrophage populations, TLR4 stimulates the dose-dependent transcription of nuclear factor κB (NF-κB) target genes. However, using single-RNA counting, we found that individual cells exhibited a wide range (three orders of magnitude) of expression of the gene encoding the proinflammatory cytokine tumor necrosis factor-α (TNF-α). The TLR4-induced TNFA transcriptional response correlated with the extent of NF-κB signaling in the cells and their size. We compared the rates of TNF-α production and uptake in macrophages and mouse embryonic fibroblasts and generated a mathematical model to explore the heterogeneity in the response of macrophages to TLR4 stimulation and the propagation of the TNF-α signal in the tissue. The model predicts that the local propagation of the TLR4-dependent TNF-α response and cellular NF-κB signaling are limited to small distances of a few cell diameters between neighboring tissue-resident macrophages. In our predictive model, TNF-α propagation was constrained by competitive uptake of TNF-α from the environment, rather than by heterogeneous production of the cytokine. We propose that the highly constrained architecture of tissues enables effective localized propagation of inflammatory cues while avoiding out-of-context responses at longer distances.