Douglas O. Staiger

Using data from approximately 7,800 school districts, we show that test score declines during the pandemic were large and highly variable. We find that test score declines were larger in lower-income and minority districts, but that within districts, White students and non–economically disadvantaged students lost about the same amount of ground as Black, Hispanic, and economically disadvantaged students. We find that the test score declines were larger in districts where more of the 2020–2021 school year was spent in remote or hybrid instructional modalities, where students had less access to broadband access at home, where the pandemic led to larger disruptions to local social and economic activity, and in communities where trust in government institutions was low.

Background: A structurally fluent workforce is essential to demonstrate structural competency—the ability to recognize and address how social, political, and economic structures affect health. Such a workforce understands the role of external factors and social determinants in health inequities. Evidence shows that minority patients receive better care from a diverse workforce. The racial composition of hospital nurses and its correlation to patients remains unreported. Objective: The aim of this study was to evaluate patient–nurse racial concordance at the hospital level in a large geographically representative hospital sample. Methods: A cross-sectional descriptive study design was employed using the 2015 Annual Registered Nurse Survey of the National Database of Nursing Quality Indicators and 2019 Medicare patient data. Concordance was measured by subtracting the hospital nurse percentage from the patient percentage. We defined Black-serving hospital (BSH) status by classifying hospitals into categories (25/50/25) by low, medium, and high representation of Black patients. Descriptive and correlation statistics were calculated on nurse and patient race and their concordance at the hospital and BSH levels. Results: Among 574 hospitals, the proportion of Black nurses was significantly lower than that of Black patients, with considerable variation across hospitals. The representation of Black nurses and patients was strongly associated with hospitals that served more Black patients and generally employed more Black nurses. When grouped into low, medium, and high BSHs, the percentage of Black nurses differed considerably across the categories. High BSH had the greatest discordance. Discussion: Although Black nurses and Black patients are often clustered in the same hospitals, there are relatively few Black nurses in hospitals where Black patients primarily receive care. This study underscores the urgent need for healthcare institutions and policymakers to prioritize building structural competency and diversifying the nursing workforce, particularly in hospitals serving higher Black patient populations. Future research is warranted on whether patient–nurse racial concordance or a nursing workforce more reflective of the patient population it serves reduces disparities.

Background: In hospitals that serve disproportionately patients of Black race, here termed Black-serving hospitals (BSH), nurse staffing is worse, mortality rates are higher, and nursing-sensitive indicators may be worse than in other hospitals, but this evidence has not been compiled. Objective: The study objective was to examine whether nursing-sensitive indicators, which measure changes in patient health status directly affected by nursing care, differ in hospitals where Black patients predominantly access their care, as compared to other hospitals. Methods: To fulfill the objective, a cross-sectional design using publicly available 2019 to 2022 Hospital Compare, 2019 Medicare Provider Analysis and Review (MEDPAR), and case mix index (CMI) file databases were used. Four nursing-sensitive indicators were evaluated: pressure ulcer, postoperative sepsis, perioperative pulmonary embolus/deep vein thrombosis, and death rate among surgical inpatients with serious treatable complications (“failure to rescue”) in hospitals classified into high, medium, and low BSHs according to the percentage of patients of Black race in the MEDPAR data. Mean outcome differences across BSH categories were assessed through analyses of variance and regression models, which controlled for hospital CMI. Results: The 3,101 hospitals were predominantly urban nonteaching hospitals in metropolitan areas. Although 12% of hospitals had Magnet designation, BSHs were disproportionately Magnet (14%). The outcome rates were 0.59 for pressure ulcers, 3.38 for perioperative pulmonary embolus/deep vein thrombosis, 143.58 for failure to rescue, and 4.12 for sepsis. Rates were significantly higher for pressure ulcers, perioperative pulmonary embolus/deep vein thrombosis, and sepsis in high BSHs. The mean failure to rescue rate was similar across low-to-high BSHs and did not show significant differences. These results were unchanged in models adjusting for CMI. Discussion: The evidence suggests that several nursing-sensitive indicators are worse in high BSHs. Research linking nursing-sensitive indicators to nursing resources such as staffing is needed to explicate the mechanism underlying these findings. Poorer nursing-sensitive indicators in combination with poorer nurse staffing in high BSHs presents a priority for policy and management intervention.

Background: Patients in hospitals that serve disproportionately patients of Black race have worse outcomes than patients in other hospitals, but the modifiable nursing factors that may contribute to such disparities have not been explored. Objective: The study objective was to examine whether nurse staffing differs in hospitals that serve predominantly patients of Black race (Black-serving hospitals) as compared to other hospitals. Methods: A cross-sectional correlational design using a nurse survey in a national hospital sample was used to fulfill the study objective. Nurse staffing was measured as the maximum number of patients cared for on the last shift from the 2015 annual registered nurse survey conducted in National Database of Nursing Quality Indicators hospitals. Hospitals were classified into subgroups of low, medium, and high percentages of patients of Black race using the 2019 Medicare Provider Analysis and Review database. Results: In survey data from 179,336 registered nurses in 574 hospitals, nurse staffing was significantly worse in high-Black-serving hospitals as compared to medium- and low-Black-serving hospitals. In Poisson regression models that adjusted for nursing unit type and hospital characteristics, nurses in high-Black-serving hospitals and medium-Black-serving hospitals had more patients-per-nurse than did nurses in low-Black-serving hospitals. Discussion: Small, statistically significant differences in nurse staffing that are worse in hospitals where Black patients disproportionately access their care were found using nurse survey data accounting for nursing unit type. The poorer nurse staffing in Black-serving hospitals may compromise the care and outcomes of the seven in 10 hospitalized Black older adults who receive care in Black-serving hospitals. The consequences for patient outcome disparities of poorer nurse staffing in Black-serving hospitals deserve investigation. Policies to increase nurse staffing in hospitals serving a higher proportion of patients of Black race are needed to contribute to efforts to reduce health disparities.

Background: The pandemic profoundly stressed practicing nurses and could have thereby affected trends in nursing-sensitive quality indicators (NSIs), measures that detect changes in patient health status directly affected by nursing care. Objectives: The aim of the study was to determine if NSIs have worsened in response to the pandemic and then returned to prepandemic levels using data from 2019 through 2022. Methods: We conducted a cross-sectional descriptive study of annual trends, examining unit data from the National Database of Nursing Quality Indicators (NDNQI) from 2019 through 2022 for five indicators: rates of falls, central line-associated bloodstream infections (CLABSI), catheter-associated urinary tract infections (CAUTI), hospital-acquired pressure injuries (HAPI), and ventilator-associated events (VAE). The NDNQI is the largest repository of nursing quality indicators, which are derived from patient-level events, reported at the nursing unit level, and submitted quarterly by over 2,000 member hospitals. Adult medical-surgical or critical care inpatient nursing units with complete data for the 4 years were included, with samples ranging from 456 to 5,818 nursing units in 2,346 hospitals. Analysis of variance was conducted by comparing the 2019 rates to each subsequent year. Results: In decreasing order of prevalence, the mean prepandemic rates were 6.58 VAE per 1,000 ventilator days (critical care only), 2.41 HAPI per 1,000 device days, 2.20 falls per 1,000 patient days, 0.96 CAUTI per 1,000 catheter days, and 0.68 CLABSI per 1,000 central line days for medical-surgical and critical care units combined. The rates for all five nurse-sensitive indicators increased significantly beginning in 2020 and have begun to decline but have not returned to baseline by 2022. The maximum rate was observed in 2020 for falls and 2021 for the remaining indicators. These increases to the maximum ranged from a 12% increase in CAUTI to 49% for CLABSI. Discussion: NSIs increased during the pandemic and are now returning to baseline. The pandemic underscored the importance of nursing practice. The pandemic’s enduring negative effects on the nursing workforce must be addressed to preserve patient safety.

Background: Because of small sample sizes and low event rates, risk-adjusted surgical outcomes often do not meet reliability benchmarks for distinguishing hospital performance. Nonetheless, it is unclear whether these measures may still be useful for predicting future hospital surgical performance. Methods: We used national Medicare data to analyze patients undergoing colectomy from 2007 to 2010 (n=462,959 patients). We first quantified 2007–2008 outcome reliability (ability to differentiate quality differences) and ranked hospitals based on their 2007–2008 risk-adjusted outcome rates. To assess the ability of adjusted outcomes to predict true performance, we evaluated future (2009–2010) outcomes across quintiles of past performance. We then systematically sampled 2007–2008 cases to evaluate performance prediction when hospitals’ past performance was measured with progressively lower reliability levels. Results: Outcomes in 2007–2008 were good predictors of outcomes in the next 2 years (2009–2010), but predictive strength depended upon reliability. With progressive sampling of 2007–2008 caseloads, outcome reliability and predictive strength decreased. With 100% sampling of 2007–2008 caseloads, the worst versus best hospital quintile based on past performance had 1.52 [95% confidence interval (CI), 1.44–1.60] times the odds of mortality and 1.50 (95% CI, 1.44–1.56) times the odds of complications in 2009–2010. With 10% sampling, outcome reliability was well below commonly accepted benchmarks, but the worst quintile of hospitals in 2007–2008 still had 1.12 (95% CI, 1.06–1.19) times the odds of mortality and 1.16 (95% CI, 1.11–1.21) times the odds of complications in 2009–2010 compared with the best quintile of hospitals. Conclusions: Even at very low reliability levels, risk-adjusted outcome measures may distinguish best and worst hospitals’ surgical performance. This study suggests that commonly accepted reliability thresholds may be too high, especially in the context of selective referral.