Lung Cancer Staging at Diagnosis in the Veterans Health Administration: Is Rurality an Influencing Factor? A Cross-Sectional Study.

PURPOSE: To evaluate the association between rurality and lung cancer stage at diagnosis. METHODS: We conducted a cross-sectional study using Veterans Health Administration (VHA) data to identify veterans newly diagnosed with lung cancer between October 1, 2011 and September 30, 2015. We defined rurality, based on place of residence, using Rural-Urban Commuting Area (RUCA) codes with the subcategories of urban, large rural, small rural, and isolated. We used multivariable logistic regression models to determine associations between rurality and stage at diagnosis, adjusting for sociodemographic and clinical characteristics. We also analyzed data using the RUCA code for patients' assigned primary care sites and driving distances to primary care clinics and medical centers. FINDINGS: We identified 4,220 veterans with small cell lung cancer (SCLC) and 25,978 with non-small cell lung cancer (NSCLC). Large rural residence (compared to urban) was associated with early-stage diagnosis of NSCLC (OR = 1.12; 95% CI: 1.00-1.24) and SCLC (OR = 1.73; 95% CI: 1.18-1.55). However, the finding was significant only in the southern and western regions of the country. White race, female sex, chronic lung disease, higher comorbidity, receiving primary care, being a former tobacco user, and more recent year of diagnosis were also associated with diagnosing early-stage NSCLC. Driving distance to medical centers was inversely associated with late-stage NSCLC diagnoses, particularly for large rural areas. CONCLUSIONS: We did not find clear associations between rurality and lung cancer stage at diagnosis. These findings highlight the complex relationship between rurality and lung cancer within VHA, suggesting access to care cannot be fully captured by current rurality codes.

Racial segregation and disparities in health care delivery: conceptual model and empirical assessment.

OBJECTIVE: This study examines two dimensions of racial segregation across hospitals, using a disease for which substantial disparities have been documented. DATA SOURCES: Black (n=32,289) and white (n=244,042) patients 67 years and older admitted for acute myocardial infarction during 2004-2005 in 105 hospital markets were identified from Medicare data. Two measures of segregation were calculated: Dissimilarity (i.e., dissimilar distribution by race across hospitals), and Isolation (i.e., racial isolation within hospitals). For each measure, markets were categorized as having low, medium, or high segregation. STUDY DESIGN: The relationship of hospital segregation to residential segregation and other market characteristics was evaluated. Cox proportional hazards regression was used to evaluate disparities in the use of revascularization within 90 days by segregation level. RESULTS: Agreement of segregation category based on Dissimilarity and Isolation was poor (kappa=0.12), and the relationship of disparities in revascularization to segregation differed by measure. The hazard of revascularization for black relative to white patients was lowest (i.e., greatest disparity) in markets with low Dissimilarity, but it was unrelated to Isolation. CONCLUSIONS: Significant racial segregation across hospitals exists in many U.S. markets, although the magnitude and relationship to disparities depends on definition. Dissimilar distribution of race across hospitals may reflect divergent cultural preferences, social norms, and patient assessments of provider cultural competence, which ultimately impact utilization.

Iowa Case Management for Rural Drug Abuse.

OBJECTIVE: The purpose of this research was to evaluate the effectiveness of a comprehensive, strengths-based model of case management for clients in drug abuse treatment. METHOD: 503 volunteers from residential or intensive outpatient treatment were randomly assigned to one of three conditions of Iowa Case Management (ICM) plus treatment as usual (TAU), or to a fourth condition of TAU only. All were assessed at intake and followed at 3, 6, and 12 months. RESULTS: Clients in all four conditions significantly decreased substance use by 3 months after intake and maintained most gains over time. However, the addition of ICM to TAU did not improve substance use outcomes. CONCLUSION: Overall, the addition of case management did not significantly improve drug treatment as hypothesized by both researchers and clinicians. Some results were mixed, possibly due to the heterogeneous sample, wide range of case management activities, or difficulty retaining participants over time.

Limitations of hospital volume as a measure of quality of care for coronary artery bypass graft surgery.

BACKGROUND: While prior research has found an inverse relationship between hospital volume and mortality after coronary artery bypass graft surgery (CABG), the use of volume as a proxy for quality and a means for selecting hospitals is controversial. The objective of this study is to quantify the relationship between hospital volume alone and CABG mortality. METHODS: A retrospective cohort of 948,093 Medicare patients undergoing CABG in 870 US hospitals from 1996 to 2001 was categorized into quintiles, based on hospital CABG volume. Hospitals were also classified by volume criterion proposed by the Leapfrog Group. Logistic regression was used to adjust hospital mortality rates (in-hospital or within 30 days after CABG) for patient characteristics; discrimination of the volume categories was assessed by the c statistic. RESULTS: The range in risk-adjusted mortality for hospitals within the quintiles was substantial: 1% to 17% at very low, 2% to 12% at low, 2% to 10% at medium, 2% to 9% at high, and 3% to 11% at very high volume hospitals. Moreover, volume alone was a poor discriminator of mortality (c statistic = 0.52). Similar variation in adjusted mortality was seen within the Leapfrog low-volume (1% to 17%) and high-volume groups (2% to 11%), and the Leapfrog criterion was a poor discriminator of mortality (c statistic = 0.51). Of the 660 low-volume Leapfrog hospitals, 253 (38%) had risk-adjusted mortality rates that were similar to or lower than the overall risk-adjusted mortality of high-volume hospitals (5.2%). CONCLUSIONS: Volume alone, as a discriminator of mortality, is only slightly better than a coin flip (c statistic of 0.50).