This paper explores the effect of equity volatility on corporate bond yields. Panel data for the late 1990's show that idiosyncratic firm-level volatility can explain as much cross-sectional variation in yields as can credit ratings. This finding, together with the upward trend in idiosyncratic equity volatility documented by Campbell, Lettau, Malkiel, and Xu (2001), helps to explain recent increases in corporate bond yields.

This paper explores the effect of equity volatility on corporate bond yields. Panel data for the late 1990s show that idiosyncratic firm‐level volatility can explain as much cross‐sectional variation in yields as can credit ratings. This finding, together with the upward trend in idiosyncratic equity volatility documented by Campbell, Lettau, Malkiel, and Xu (2001), helps to explain recent increases in corporate bond yields.

Objective We sought to characterize temporal trends in hospitalizations with heart failure as a primary or secondary diagnosis. Background Heart failure patients are frequently admitted for both heart failure and other causes. Methods Using the Nationwide Inpatient Sample (NIS), we evaluated trends in heart failure hospitalizations between 2001 and 2009. Hospitalizations were categorized as either primary or secondary heart failure hospitalizations based the location of heart failure in the discharge diagnosis. National estimates were calculated using the sampling weights of the NIS. Age- and gender-standardized hospitalization rates were determined by dividing the number of hospitalizations by the United States population in a given year and using direct standardization. Results The number of primary heart failure hospitalizations in the United States decreased from 1,137,944 in 2001 to 1,086,685 in 2009, while secondary heart failure hospitalizations increased from 2,753,793 to 3,158,179 over the same period. Age- and gender-adjusted rates of primary heart failure hospitalizations decreased steadily over 2001–2009, from 566 to 468 per 100,000 people. Rates of secondary heart failure hospitalizations initially increased, from 1370 to 1476 per 100,000 from 2001–2006, then decreased to 1359 per 100,000 in 2009. Common primary diagnoses for secondary heart failure hospitalizations included pulmonary disease, renal failure, and infections. Conclusions Although primary heart failure hospitalizations declined, rates of hospitalizations with a secondary diagnosis of heart failure were stable in the past decade. Strategies to reduce the high burden of hospitalizations of heart failure patients should include consideration of both cardiac disease and non-cardiac conditions.

BACKGROUND: Understanding resource utilization patterns among high-cost patients may inform cost reduction strategies. OBJECTIVE: To identify patterns of high-cost healthcare utilization and associated clinical diagnoses and to quantify the significance of hot-spotters among high-cost users. DESIGN: Retrospective analysis of high-cost patients in 2012 using data from electronic medical records, internal cost accounting, and the Centers for Medicare and Medicaid Services. K-medoids cluster analysis was performed on utilization measures of the highest-cost decile of patients. Clusters were compared using clinical diagnoses. We defined Bhotspotters^as those in the highest-cost decile with ≥4 hospitalizations or ED visits during the study period. PARTICIPANTS AND EXPOSURE: A total of 14,855 Medicare Fee-for-service beneficiaries identified by the Medicare Quality Resource and Use Report as having received 100 % of inpatient care and ≥90 % of primary care services at Cleveland Clinic Health System (CCHS) in Northeast Ohio. The highest-cost decile was selected from this population. MAIN MEASURES: Healthcare utilization and diagnoses. KEY RESULTS: The highest-cost decile of patients (n = 1486) accounted for 60 % of total costs. We identified five patient clusters: BAmbulatory,^with 0 admissions; BSurgical,^with a median of 2 surgeries; BCritically Ill,^with a median of 4 ICU days; BFrequent Care,^with a median of 2 admissions, 3 ED visits, and 29 outpatient visits; and BMixed Utilization,^with 1 median admission and 1 ED visit. Cancer diagnoses were prevalent in the Ambulatory group, care complications in the Surgical group, cardiac diseases in the Critically Ill group, and psychiatric disorders in the Frequent Care group. Most hot-spotters (55 %) were in the Bfrequent care^clus-ter. Overall, hot-spotters represented 9 % of the high-cost population and accounted for 19 % of their overall costs. CONCLUSIONS: High-cost patients are heterogeneous; most are not so-called Bhot-spotters^with frequent admissions. Effective interventions to reduce costs will require a more multi-faceted approach to the high-cost population.

BACKGROUND:In the United States, black males have an annual death rate from prostate cancer that is 2.4 times that of white males. The reasons for this are poorly understood. METHODS: Using the Surveillance, Epidemiology, and End Results-Medicare database, 77,038 black and white males aged >65 years were identified with a first primary diagnosis of prostate cancer between 1995 and 2005, as well as 49,769 controls. The racial gap in mortality was decomposed to differential incidence and stage-specific prostate cancer mortality. The importance of various clinical and socioeconomic factors to each of these components was then examined. RESULTS: The estimated mortality gap for prostate cancer-specific mortality was 1320 more cases per 100,000 males among black than white men. This gap was due to higher prostate cancer incidence among black males (76%) and higher stage-specific mortality once diagnosed (24%). Differences in prostate-specific antigen testing, comorbidities, and income explained 29% of the difference in metastatic cancer incidence but none of the racial gap for local/regional incidence. Conditional on diagnosis, tumor characteristics explained 50% of the racial gap, comorbidities an additional 4%, choice of treatment and physician 17%, and socioeconomic factors 15%. Overall, approximately 25% of the racial gap in mortality and 86% of the gap in mortality conditional on diagnosis could be explained. CONCLUSIONS: More frequent prostate-specific antigen testing for black and low-income males could potentially reduce the prostate cancer mortality gap through earlier diagnosis of tumors that otherwise may become metastatic. More aggressive treat-