BACKGROUND: Persistent racial and ethnic disparities in tuberculosis incidence exist in the USA, however, less is known about disparities along the tuberculosis continuum of care. This study aimed to describe how race and ethnicity are associated with tuberculosis diagnosis and treatment outcomes. METHODS: In this analysis of national surveillance data, we extracted data from the US National Tuberculosis Surveillance System on US-born patients with tuberculosis during 2003-19. To estimate the association between race and ethnicity and tuberculosis diagnosis (diagnosis after death, cavitation, and sputum smear positivity) and treatment outcomes (treatment for more than 12 months, treatment discontinuation, and death during treatment), we fitted log-binomial regression models adjusting for calendar year, sex, age category, and regional division. Race and ethnicity were defined based on US Census Bureau classification as White, Black, Hispanic, Asian, American Indian or Alaska Native, Native Hawaiian or Pacific Islander, and people of other ethnicities. We quantified racial and ethnic disparities as adjusted relative risks (aRRs) using non-Hispanic White people as the reference group. We also calculated the Index of Disparity as a summary measure that quantifies the dispersion in a given outcome across all racial and ethnic groups, relative to the population mean. We estimated time trends in each outcome to evaluate whether disparities were closing or widening. FINDINGS: From 2003 to 2019, there were 72 809 US-born individuals diagnosed with tuberculosis disease of whom 72 369 (35·7% women and 64·3% men) could be included in analyses. We observed an overall higher risk of any adverse outcome (defined as diagnosis after death, treatment discontinuation, or death during treatment) for non-Hispanic Black people (aRR 1·27, 95% CI 1·22-1·32), Hispanic people (1·20, 1·14-1·27), and American Indian or Alaska Native people (1·24, 1·12-1·37), relative to non-Hispanic White people. The Index of Disparity for this summary outcome remained unchanged over the study period. INTERPRETATION: This study, based on national surveillance data, indicates racial and ethnic disparaties among US-born tuberculosis patients along the tuberculosis continuum of care. Initiatives are needed to reduce diagnostic delays and improve treatment outcomes for US-born racially marginalised people in the USA. FUNDING: US Centers for Disease Control and Prevention.

OBJECTIVES: Tracking trends in the testing of latent tuberculosis infection (LTBI) can help measure tuberculosis elimination efforts in the United States. The objectives of this study were to estimate (1) the annual number of persons tested for LTBI and the number of LTBI tests conducted, by type of test and by public, private, and military sectors, and (2) the cost of LTBI testing in the United States. METHODS: We searched the biomedical literature for published data on private-sector and military LTBI testing in 2013, and we used back-calculation to estimate public-sector LTBI testing. To estimate costs, we applied Medicare-allowable reimbursements in 2013 by test type. RESULTS: We estimated an average (low-high) 13.3 million (11.3-15.4 million) persons tested for LTBI and 15.3 million (12.9-17.7 million) LTBI tests, of which 13.2 million (11.1-15.3 million) were tuberculin skin tests and 2.1 million (1.8-2.4 million) were interferon-gamma release assays (IGRAs). Eighty percent of persons tested were in the public sector, 18% were in the private sector, and 2% were in the military. Costs of LTBI tests and of chest radiography totaled $314 million (range, $256 million to $403 million). CONCLUSIONS: To achieve tuberculosis elimination, millions more persons will need to be tested in all sectors. By targeting testing to only those at high risk of tuberculosis and by using more specific IGRA tests, the incidence of tuberculosis in the United States can be reduced and resources can be more efficiently used.

OBJECTIVE: To estimate the number and cost of hospitalizations with a diagnosis of active tuberculosis (TB) disease in the United States. METHODS: We analyzed the 2014 National In-Patient Sample using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9) codes to identify hospitalizations with a principal (TB-PD) or any secondary discharge (TB-SD) TB diagnosis. We used a generalized linear model with log link and gamma distribution to estimate the cost per TB-PD and TB-SD episode adjusted for patient demographics, insurer, clinical elements, and hospital characteristics. RESULTS: We estimated 4985 TB-PD and 6080 TB-SD hospitalizations nationwide. TB-PD adjusted averaged $16 695 per episode (95%CI $16 168-$17 221). The average for miliary/disseminated TB ($22 498, 95%CI $21 067-$23 929) or TB of the central nervous system ($28 338, 95%CI $25 836-$30 840) was significantly greater than for pulmonary TB ($14 819, 95%CI $14 284-$15 354). The most common principal diagnoses for TB-SD were septicemia (n = 965 hospitalizations), human immunodeficiency virus infection (n = 610), pneumonia (n = 565), and chronic obstructive pulmonary disease and bronchiectasis (COPD-B, n = 150). The adjusted average cost per TB-SD episode was $15 909 (95%CI $15 337-$16 481), varying between $8687 (95%CI $8337-$9036) for COPD-B and $23 335 (95%CI $21 979-$24 690) for septicemia. TB-PD cost the US health care system $123.4 million (95%CI $106.3-$140.5) and TB-SD cost $141.9 million ($128.4-$155.5), of which Medicaid/Medicare covered respectively 67.2% and 69.7%. CONCLUSIONS: TB hospitalizations result in substantial costs within the US health care system.

OBJECTIVE: We estimated the reduction in number of hospitalizations for acute myocardial infarction and stroke as well as the associated health care costs resulting from reducing the number of smokers in the US federal workforce during a 5-year period. METHODS: We developed a 5-year spreadsheet-based cohort model with parameter values from past literature and analysis of national survey data. We obtained 2015 data on the federal workforce population from the US Office of Personnel Management and data on smoking prevalence among federal workers from the 2013-2015 National Health Interview Survey. We adjusted medical costs and productivity losses for inflation to 2015 US dollars, and we updated future productivity losses for growth. Because of uncertainty about the achievable reduction in smoking prevalence and input values (eg, relative risk for acute myocardial infarction and stroke, medical costs, and absenteeism), we performed a Monte Carlo simulation and sensitivity analysis. RESULTS: We estimated smoking prevalence in the federal workforce to be 13%. A 5 percentage-point reduction in smoking prevalence could result in 1106 fewer hospitalizations for acute myocardial infarction (range, 925-1293), 799 fewer hospitalizations for stroke (range, 530-1091), and 493 fewer deaths (range, 494-598) during a 5-year period. Similarly, estimated costs averted would be $59 million (range, $49-$63 million) for medical costs, $332 million (range, $173-$490 million) for absenteeism, and $117 million (range, $93-$142 million) for productivity. CONCLUSION: Reductions in the prevalence of smoking in the federal workforce could substantially reduce the number of hospitalizations for acute myocardial infarction and stroke, lower medical costs, and improve productivity.