"Top Performing" US Hospitals and the Health Status of Counties they Serve.

This study (a) examined the relationships between "top performing" US hospitals and the health status of counties they serve and (b) compared the health status of "top performing" US hospital counties versus that of remaining US counties. Statistical analyses considered US News and World Report Honor Roll ranking data, as a measure of hospital performance, and County Health Rankings (CHR) data, as a measure of county health status. "Top performing" hospital Honor Roll scores were correlated with measures of Clinical Care (p < 0.001). Counties with "top performing" US hospitals presented greater health status with regard to All Health Outcomes (p < 0.001), Length of Life (p < 0.001), Quality of Life (p < 0.001), All Health Factors (p < 0.001), Health Behaviors (p < 0.001), and Clinical Care (p < 0.001), than compared to remaining US counties. Hospital impact on county health status remains primarily recognized in clinical care and not in overall health. Also, counties that contain a "top performing" US hospital tend to present lower health risks to their citizens than compared to other US counties.

A probabilistic method for the estimation of residual risk in donated blood.

The residual risk (RR) of transfusion-transmitted infections, including the human immunodeficiency virus and hepatitis B and C viruses, is typically estimated by the incidence[Formula: see text]window period model, which relies on the following restrictive assumptions: Each screening test, with probability 1, (1) detects an infected unit outside of the test's window period; (2) fails to detect an infected unit within the window period; and (3) correctly identifies an infection-free unit. These assumptions need not hold in practice due to random or systemic errors and individual variations in the window period. We develop a probability model that accurately estimates the RR by relaxing these assumptions, and quantify their impact using a published cost-effectiveness study and also within an optimization model. These assumptions lead to inaccurate estimates in cost-effectiveness studies and to sub-optimal solutions in the optimization model. The testing solution generated by the optimization model translates into fewer expected infections without an increase in the testing cost.

Comparison of Quality Measures From US Hospitals With Physician vs Nonphysician Chief Executive Officers.

Importance: Patient experience and patient safety are 2 major domains of health care quality; however empirical data on the association of physician vs nonphysician chief executive officers (CEOs) with public and private quality measures are rare but critical to evaluate as hospitals increasingly seek out physician CEOs. Objectives: To evaluate whether there is an association of CEO background with hospital quality and to investigate differences in hospital characteristics between hospitals with a physician CEO vs those with a nonphysician CEO. Design, Setting, and Participants: This cross-sectional study used 2019 data from 3 sources (ie, the American Hospital Association [AHA] Annual Survey, the Hospital Consumer Assessment of Healthcare Providers and Systems [HCAHPS], and the Leapfrog Hospital Safety Grades) to identify statistical differences in hospital characteristics and outcomes. Data were analyzed from April to December 2021 . Main Outcomes and Measures: Multivariable ordinal logistic regression was used to examine the association of physician CEOs with hospital quality assessment outcomes while controlling for other confounding factors. Characteristics from the AHA Annual Survey database were assessed as potential confounders, including hospital control, bed size, region, teaching status, and patient volume. Results: The AHA database contained 6162 hospitals; 1759 (29%) had HCAHPS ratings, 1824 (30%) had Leapfrog grades, and 383 (6%) had physician CEOs. A positive Spearman correlation coefficient was found between physician CEOs and HCAHPS patient willingness to recommend the hospital (ρ = 0.0756; P = .002), but the association between CEO medical background and Leapfrog safety grades or HCAHPS ratings did not reach a level of significance in the multivariable ordinal logistic regression models. Conclusions and Relevance: In this study, a positive correlation was found between physician CEOs and HCAHPS patient willingness to recommend the hospital, but the multivariable analysis did not find an association between hospital physician CEOs and the examined quality and safety outcomes.

State-level child health system performance and the likelihood of readmission to children's hospitals.

OBJECTIVES: To assess the relationship between children's hospital readmission and the performance of child health systems in the states in which hospitals are located. STUDY DESIGN: We conducted a retrospective cohort study of 197,744 patients 2 to 18 years old from 39 children's hospitals located in 24 states in the United States in 2005. Subjects were observed for a year after discharge for readmission to the same hospital. The odds of readmission were modeled on the basis of patient-level characteristics and state child health system performance as ranked by the Commonwealth Fund. RESULTS: A total of 1.8% of patients were readmitted within a week, 4.8% within a month, and 16.3% within 365 days. After adjustment for patient-level characteristics, the probability of readmission varied significantly between states (P=.001), and the likelihood of readmission during the ensuing year increased as the states' health system performance ranking improved. States in the best ranking quartile had a 2.03% higher readmission rate than states in the lowest quartile (P=.02); the same directional relationship was observed for readmission intervals from 1 to 365 days after discharge. CONCLUSIONS: Hospital readmission rates are significantly related to the performance of the surrounding health care system.

Pediatric patients hospitalized with myocarditis: a multi-institutional analysis.

The objective of this study was to identify the patient, institutional, and utilization characteristics associated with outcome in hospitalized pediatric patients with myocarditis. This was a nonconcurrent cohort study of all consecutive pediatric discharges from the 35 academic children's hospitals that are members of the Pediatric Health Information System (PHIS): patients from birth through age 21 years discharged from participating hospitals between January 1, 2005, and December 31, 2005. Patient-level, institution-level, and utilization variables were examined. A total of 427,615 patients were discharged, and 216 (0.05%) were diagnosed with myocarditis. Common etiologies were idiopathic (82%), related to other diseases (6%), and bacterial or viral (3%). Myocarditis patients required considerable support including intravenous immunoglobulin (IVIG; 49.1%), milrinone (45%), epinephrine (35%), mechanical ventilation (25%), extracorporeal membrane oxygenation (7%), and cardiac transplantation (5%). Even in patients with extreme illness scores, IVIG use did not impact survival (P = 0.67). Overall survival of myocarditis patients was 92%. Myocarditis patients who died presented with a higher severity of illness and required frequent use of extracorporeal membrane oxygenation and other ICU therapies. In conclusion, pediatric patients with myocarditis have considerable variability in their presentations and outcomes, use more resources, and die more often than children with other diagnoses. Attempts at using characteristics that uniformly predict illness severity or survival were not successful. Despite increased use in the sickest patients, IVIG conferred no survival advantage.

Challenges confronting rural hospitals accentuated during COVID-19.

The Balanced Budget Act of 1997 created a designation for critical access hospitals (CAHs) to sustain care for people living in rural communities who lacked access to care due to hospital closures over the preceding decade. Twenty-five years later, 1350 CAHs serve approximately 18% of the US population and a systematic policy evaluation has yet to be performed. This policy analysis serves to define challenges faced by CAHs through a literature review addressing the four major categories of payment, quality, access to capital, and workforce. Additionally, this analysis describes how current challenges to maintain sustainability of CAHs over time are accentuated by gaps in public health infrastructure and variability in individual health care plans exhibited during the COVID-19 pandemic.