scholarly journals Sex disparities in COVID-19 mortality vary considerably across time: The case of New York State

Author(s):  
Ann Caroline Danielsen ◽  
Marion MN Boulicault ◽  
Annika Gompers ◽  
Tamara Rushovich ◽  
Katharine MN Lee ◽  
...  

In order to characterize how sex disparities in COVID-19 mortality evolved over time in New York State (NY), we analyzed sex-disaggregated data from the US Gender/Sex COVID-19 Data Tracker from March 14, 2020 to August 28, 2021. We defined six different time periods and calculated mortality rates by sex and mortality rate ratios, both cumulatively and for each time period separately. As of August 28, 2021, 19 227 (44.2%) women and 24 295 (55.8%) men died from COVID-19 in NY. 72.7% of the cumulative difference in the number of COVID-19 deaths between women and men was accrued between March 14 and May 4, 2020. During this period, the COVID-19 mortality rate ratio for men compared to women was 1.56 (95% CI: 1.52-1.61). In the five subsequent time periods, the corresponding ratio ranged between 1.08 (0.98-1.18) and 1.24 (1.15-1.34). While the cumulative mortality rate ratio of men compared to women was 1.34 (1.31-1.37), the ratio equals 1.19 (1.16-1.22) if deaths during the initial COVID-19 surge are excluded from the analysis. This article shows that in NY the magnitude of sex disparities in COVID-19 mortality was not stable across time. While the initial surge in COVID-19 mortality was characterized by stark sex disparities, these were greatly attenuated after the introduction of public health controls.

2020 ◽  
Vol 13 (Suppl_1) ◽  
Author(s):  
Swathi Raman ◽  
Ashwin Nathan ◽  
Sameed Ahmed M Khatana ◽  
Nimesh D Desai ◽  
Pavan Atluri ◽  
...  

Purpose: Public reporting of surgical outcomes can promote quality improvement. However, this could also incentivize surgeons to avoid high-risk patients. Senior surgeons, with established referral networks, may select lower-risk cases than their junior colleagues. This study aimed to assess the relationship between surgeon experience and expected mortality rate of cases performed. Methods: Publicly available data on coronary artery bypass graft (CABG) surgeries between 2011-2013 were obtained from the New York State Department of Health. The 30-day expected mortality rate (EMR) for each CABG was calculated from validated models. Additionally, we obtained data on each surgeon’s medical school gradation year and board certification status from Internet sources, such as Doximity. Surgeon experience was calculated by subtracting the medical school graduation year from 2011, the start of the study period. A multivariable linear regression model was used to estimate the association between EMR and surgeon experience, adjusting for case volume and board certification status. Results: Between 2011-2013, there were 132 cardiac surgeons that performed CABG at 39 hospitals across New York State. The mean surgeon experience was 25.1 years (SD 9.1 years) and the overall mean EMR of CABG surgeries was 1.46% (SD 0.38%). The unadjusted analysis showed a 0.005% increase in EMR per additional year of surgeon experience. However, this was not statistically significant (p=0.25, 95% CI -0.0036 to 0.0013). Through the multivariable linear regression model, we did not find evidence of a significant association between operator experience and the EMR of cases performed (0.0040% per year, p=0.35, 95% CI -0.0044 to 0.012%). There was a significant association between the number of cases performed during the study period and the EMR, with an increase in EMR by 0.0005% per additional case performed (p=0.04, 95% CI 0.00004 to 0.001). There was no significant association between board certification status and EMR (p=0.10). Conclusion: Despite public reporting of CABG outcomes, our findings suggest that more experienced surgeons may not be exhibiting risk-avoidant behavior. Future research could focus on supplementing publicly reported physician-level data with patient-level datasets to better understand the association between surgeon experience and expected mortality rate of cases performed.


Author(s):  
Sameed Ahmed M Khatana ◽  
Paul N Fiorilli ◽  
Peter W Groeneveld ◽  
Jay S Giri

Objectives: Patients have few objective predictors of quality in their choice of physician. We studied whether physician education variables and board certification status were associated with 30 day mortality rates after percutaneous coronary interventions (PCI) in New York State. Methods: Using the New York State PCI registry we obtained 30 day risk adjusted mortality rates after PCI procedures for all interventional cardiologists practicing between 2010-2012. Educational and certification variables were obtained using publicly available sources. Mortality rates were adjusted using a hierarchical Poisson shrinkage estimator. Hierarchical regression modeling was used to assess associations between mortality rates and education and certification markers (graduation from American vs. foreign medical school, years since medical school graduation, board certification in interventional cardiology and maintenance of certification for board certified physicians in 2016) with and without adjustment for caseload. Excluding correlated covariates, a regression model including caseload, board certification and US graduates was also constructed. Results: A total of 346 interventional cardiologists performed an average of 427.41 ± 402.52 cases with 3.90 ± 3.51 deaths. The average shrinkage estimator adjusted mortality rate was 1.00 ± 0.16. Only interventional cardiology board certification (75.8% of providers) was associated with lower mortality rate in univariate analysis (β = -0.06; p = 0.03). No other variables had a significant association with the outcomes. After adjusting for caseload, the association with board certification became non-significant. In the multivariate regression model including the above noted covariates, the association between caseload and the outcome remained significant (β = -0.001; p <.01). Conclusion: Risk-adjusted mortality rate after PCI is not associated with any education or certification markers, including board certification in interventional cardiology or maintenance of certification, after adjustment for caseload. Caseload was the only predictor of mortality rate in multivariate modeling.


2004 ◽  
Vol 133 (1) ◽  
pp. 121-125 ◽  
Author(s):  
C. WU ◽  
H.-G. CHANG ◽  
L.-A. McNUTT ◽  
P. F. SMITH

The New York State hospital discharge database and the multiple cause-of-death file were used to estimate the mortality rate of hepatitis C in New York State excluding New York City in 1997. The mortality rate with hepatitis C was severely underestimated when each data source was used alone. Applying the capture–recapture method using the hospital discharge database and the multiple cause-of-death file appears to be an efficient method to estimate the mortality rate with hepatitis C.


1988 ◽  
Vol 4 (2) ◽  
pp. 121-135
Author(s):  
Margaret Farnworth ◽  
M. Joan McDermott ◽  
Sherwood E. Zimmerman

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. 270-270
Author(s):  
John Clark Henegan

270 Background: The racial disparity in outcomes for prostate cancer, gastric cancer, and multiple myeloma is demonstrated by these malignancies having the highest age-adjusted mortality rate ratio for black Americans versus white Americans. A variety of factors have been identified as contributing to this disparity, leading to our hypothesis that there would not be concordance, in respect to the mean, when the county-level age-adjusted black: white mortality rate ratio for a malignancy was compared to the other two malignancies. Methods: Publically available information from cancerrates.gov was used to obtain county-level data in regards to race-specific age-adjusted mortality rates for prostate cancer, gastric cancer, and multiple myeloma. Counties with potentially unstable age-adjusted mortality rates were excluded. A malignancy’s age-adjusted mortality rate for blacks was divided by the complementary rate for whites to determine the black: white mortality rate ratio. Across a county, malignancies were compared for concordance in mortality rate ratios relative to the mean ratio for that malignancy. After a preliminary inspection noted that all New Jersey counties had a markedly lower black: white mortality ratio for gastric cancer than other counties in the data set, the New Jersey counties were excluded from analysis and odds ratios for concordance were calculated. Results: All counties (n = 68) had a black: white age-adjusted mortality ratio of > 1 for each malignancy. In the analyzed counties (n = 52), there was a statistically significant concordance in black: white mortality rate ratios for prostate cancer and gastric cancer (OR = 3.26, p = 0.046). The black: white mortality rate ratios for neither prostate cancer (OR = 1.17, p = 0.78) nor gastric cancer (OR = 1.17, p = 0.78) demonstrated a statistically significant concordance with multiple myeloma. Conclusions: The concordance in the black: white mortality rate ratios for prostate cancer and gastric cancer in this dataset indicate that these two malignancies may share common clinical, environmental, or genetic factors in African-Americans. Future research is needed into what common factors may contribute to disparities in these two malignancies.


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