Search

Background: Mechanisms underlying racial and ethnic disparities in robot-assisted radical prostatectomy (RARP) vs open radical prostatectomy (ORP) are unclear. We sought to test 2 physician-level hypotheses: 1) Segregated Treatment and 2) Differential Treatment., Methods: This observational study used the New York State Cancer Registry linked to discharge records and included patients undergoing radical prostatectomy for localized prostate cancer from October 1, 2008 to December 31, 2018. For hypothesis 1, we examined the association between patient race and ethnicity and treating surgeon RARP use (high-use surgeons, low-use surgeons, and surgeons at non-RARP facilities). For hypothesis 2, we determined the association between patient race and ethnicity and receipt of RARP when matching on treating surgeon, age, year of procedure, and Gleason group. We explored the role of insurance in both analyses., Results: This study included 18 926 patients (8.0% Hispanic, 16.9% non-Hispanic Black, 75.1% non-Hispanic White), with a mean age of 60.4 ± 7.1 years. Compared with non-Hispanic White patients, Hispanic and non-Hispanic Black patients had higher odds of being treated by low-RARP-use surgeons (odds ratio [OR] = 2.16, 95% confidence interval [CI] = 1.20 to 3.88; OR = 1.76, 95% CI = 1.06 to 2.94, respectively) and by surgeons at non-RARP facilities (OR = 4.19, 95% CI = 2.18 to 8.07; OR = 4.60, 95% CI = 2.58 to 8.23, respectively). In the matched cohorts, Hispanic and non-Hispanic Black patients were less likely to receive RARP than non-Hispanic White patients (OR = 0.78, 95% CI = 0.62 to 0.98; OR = 0.75, 95% CI = 0.57 to 1.00, respectively). These associations were partially attenuated after accounting for insurance., Conclusions: Racial and ethnic disparities in RARP use are related to patients being treated by different surgeons and treated differently by the same surgeons. Identifying and addressing multilevel barriers to equitable surgical treatment is needed to reduce disparities among prostate cancer patients., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Social Security numbers (SSNs) collected by cancer surveillance registries in the United States are used for patient matching, deduplication, follow-up, and linkage studies. However, due to various reasons, a small proportion of patient records have missing or inaccurate SSNs. Recently, New York State Cancer Registry (NYSCR) data have been linked to LexisNexis data to obtain patient demographic information, including SSNs. The current study evaluated the feasibility of using LexisNexis to improve SSN information in the NYSCR., Materials and Methods: Patients diagnosed during the years 2005-2016, aged 21 or older, in the NYSCR were linked to LexisNexis data. For the matched patients, LexisNexis returned demographic information, including SSNs as available. Percentages of patients without LexisNexis matches or without LexisNexis SSNs were examined by demographic characteristics. We used multivariate logistic regression analyses to further evaluate how patient demographic characteristics affected the likelihood of no LexisNexis matches or of no SSNs returned. For patients with SSNs returned, LexisNexis SSNs were compared with registry SSNs. If patients had prior missing registry SSNs or if LexisNexis SSNs were inconsistent with registry SSNs, we used Match*Pro to review and verify match status. Registry SSNs were updated for those confirmed to be true matches. Improvement of SSNs was assessed based on percentage reduction of missingness., Results: Of 1,396,078 patient records submitted for LexisNexis linkage, 1.6% were not matched. Among those matched, 1.5% did not have SSNs returned. Multivariate logistic regression analyses indicated that patients who were female, Black, Asian Pacific Islander (API), Hispanic, born outside the United States, deceased, or living in poorer census tracts were more likely to not have LexisNexis matches, or to not have SSNs returned. Among 47,271 patients with missing registry SSNs (3.4%), 26,895 had SSNs returned from LexisNexis, and 24,919 were confirmed to be true matches. After registry SSNs updates, the percentage of SSN missingness was reduced to 1.7%, with a larger absolute reduction observed among those who were younger than 60 years, API, or alive. For 33,057 patients with inconsistent SSNs, 11,474 were due to incorrect consolidations of SSNs in the registry, and those SSNs were subsequently fixed., Conclusions: LexisNexis is a valuable resource for improving the quality of SSN information in registries. Our results showed that the overall percentage of patients with missing SSNs was reduced from 3.4% to 1.7% after LexisNexis link-age, and SSNs that were initially incorrectly consolidated for some patients were also identified and subsequently fixed. However, the magnitude of SSN improvement varied by patient demographic characteristics. Data quality improvements often require resources, and this evaluation can assist registries with decisions related to similar efforts., (© 2023 National Cancer Registrars Association.)

Extreme temperature events are linked to increased emergency department visits, hospitalizations, and mortality for individuals with behavioral health disorders (BHD). This study aims to characterize risk factors for concurrent temperature-related illness among BHD hospitalizations in New York State. Using data from the NYS Statewide and Planning Research and Cooperative System between 2005-2019, multivariate log binomial regression models were used in a population of BHD hospitalizations to estimate risk ratios (RR) for a concurrent heat-related (HRI) or cold-related illness (CRI). Dementia (RR 1.65; 95% CI:1.49, 1.83) and schizophrenia (RR 1.38; 95% CI:1.19, 1.60) were associated with an increased risk for HRI among BHD hospitalizations, while alcohol dependence (RR 2.10; 95% CI:1.99, 2.22), dementia (RR 1.52; 95% CI:1.44, 1.60), schizophrenia (RR 1.41; 95% CI:1.31, 1.52), and non-dependent drug/alcohol use (RR 1.20; 95% CI:1.15, 1.26) were associated with an increased risk of CRI among BHD hospitalizations. Risk factors for concurrent HRI among BHD hospitalizations include increasing age, male gender, non-Hispanic Black race, and medium hospital size. Risk factors for concurrent CRI among BHD hospitalizations include increasing age, male gender, non-Hispanic Black race, insurance payor, the presence of respiratory disease, and rural hospital location. This study adds to the literature by identifying dementia, schizophrenia, substance-use disorders, including alcohol dependence and non-dependent substance-use, and other sociodemographic factors as risk factors for a concurrent CRI in BHD hospitalizations.

On July 18, 2022, the New York State Department of Health (NYSDOH) notified CDC of detection of poliovirus type 2 in stool specimens from an unvaccinated immunocompetent young adult from Rockland County, New York, who was experiencing acute flaccid weakness. The patient initially experienced fever, neck stiffness, gastrointestinal symptoms, and limb weakness. The patient was hospitalized with possible acute flaccid myelitis (AFM). Vaccine-derived poliovirus type 2 (VDPV2) was detected in stool specimens obtained on days 11 and 12 after initial symptom onset. To date, related Sabin-like type 2 polioviruses have been detected in wastewater* in the patient's county of residence and in neighboring Orange County up to 25 days before (from samples originally collected for SARS-CoV-2 wastewater monitoring) and 41 days after the patient's symptom onset. The last U.S. case of polio caused by wild poliovirus occurred in 1979, and the World Health Organization Region of the Americas was declared polio-free in 1994. This report describes the second identification of community transmission of poliovirus in the United States since 1979; the previous instance, in 2005, was a type 1 VDPV (1). The occurrence of this case, combined with the identification of poliovirus in wastewater in neighboring Orange County, underscores the importance of maintaining high vaccination coverage to prevent paralytic polio in persons of all ages., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest.

Background: Environmental exposures such as traffic may contribute to asthma morbidity including recurrent emergency department (ED) visits. However, these associations are often confounded by socioeconomic status and health care access., Objective: This study aims to assess the association between traffic density and recurrence of asthma ED visits in the primarily low income Medicaid population in New York State (NYS) between 2005 and 2015., Methods: The primary outcome of interest was a recurrent asthma ED visit within 1-year of index visit. Traffic densities (weighted for truck traffic) were spatially linked based on home addresses. Bivariate and multivariate logistic regression analyses were conducted to identify factors predicting recurrent asthma ED visits., Results: In a multivariate model, Medicaid recipients living within 300-m of a high traffic density area were at a statistically significant risk of a recurrent asthma ED visit compared to those in a low traffic density area (OR = 1.31; 95% CI:1.24,1.38). Additionally, we evaluated effect measure modification for risk of recurrent asthma visits associated with traffic exposure by socio-demographic factors. The highest risk was found for those exposed to high traffic and being male (OR = 1.87; 95% CI:1.46,2.39), receiving cash assistance (OR = 2.11; 95% CI:1.65,2.72), receiving supplemental security income (OR = 2.21; 95% CI:1.66,2.96) and being in the 18.44 age group (OR = 1.59;95% CI 1.48,1.70) was associated with the highest risk of recurrent asthma ED visit. Black non-Hispanics (OR = 2.35; 95% CI:1.70,3.24), Hispanics (OR = 2.13; 95% CI:1.49,3.04) and those with race listed as "Other" (OR = 1.89 95% CI:1.13,3.16) in high traffic areas had higher risk of recurrent asthma ED visits as compared to White non-Hispanics in low traffic areas., Conclusion: We observed significant persistent disparities in asthma morbidity related to traffic exposure and race/ethnicity in a low-income population. Our findings suggest that even within a primarily low-income study population, socioeconomic differences persist. These differences in susceptibility in the extremely low-income group may not be apparent in health studies that use Medicaid enrollment as a proxy for low SES., (© 2022. The Author(s).)

Background: Air pollution health studies have been increasingly using prediction models for exposure assessment even in areas without monitoring stations. To date, most studies have assumed that a single exposure model is correct, but estimated effects may be sensitive to the choice of exposure model., Methods: We obtained county-level daily cardiovascular (CVD) admissions from the New York (NY) Statewide Planning and Resources Cooperative System (SPARCS) and four sets of fine particulate matter (PM 2.5 ) spatio-temporal predictions (2002-2012). We employed overdispersed Poisson models to investigate the relationship between daily PM 2.5 and CVD, adjusting for potential confounders, separately for each state-wide PM 2.5 dataset., Results: For all PM 2.5 datasets, we observed positive associations between PM 2.5 and CVD. Across the modeled exposure estimates, effect estimates ranged from 0.23% (95%CI: -0.06, 0.53%) to 0.88% (95%CI: 0.68, 1.08%) per 10 µg/m 3 increase in daily PM 2.5 . We observed the highest estimates using monitored concentrations 0.96% (95%CI: 0.62, 1.30%) for the subset of counties where these data were available., Conclusions: Effect estimates varied by a factor of almost four across methods to model exposures, likely due to varying degrees of exposure measurement error. Nonetheless, we observed a consistently harmful association between PM 2.5 and CVD admissions, regardless of model choice., (© 2021. The Author(s).)

Background: Individuals with congenital heart defects (CHDs) are recommended to receive all inpatient cardiac and noncardiac care at facilities that can offer specialized care. We describe geographic accessibility to such centers in New York State and determine several factors associated with receiving care there., Methods: We used inpatient hospitalization data from the Statewide Planning and Research Cooperative System (SPARCS) in New York State 2008-2013. In the absence of specific adult CHD care center designations during our study period, we identified pediatric/adult and adult-only cardiac surgery centers through the Cardiac Surgery Reporting System to estimate age-based specialized care. We calculated one-way drive and public transit time (in minutes) from residential address to centers using R gmapsdistance package and the Google Maps Distance Application Programming Interface (API). We calculated prevalence ratios using modified Poisson regression with model-based standard errors, fit with generalized estimating equations clustered at the hospital level and subclustered at the individual level., Results: Individuals with CHDs were more likely to seek care at pediatric/adult or adult-only cardiac surgery centers if they had severe CHDs, private health insurance, higher severity of illness at encounter, a surgical procedure, cardiac encounter, and shorter drive time. These findings can be used to increase care receipt (especially for noncardiac care) at pediatric/adult or adult-only cardiac surgery centers, identify areas with limited access, and reduce disparities in access to specialized care among this high-risk population., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Women with congenital heart defects (CHDs) experiencing pregnancies require specialized delivery care and extensive monitoring that may not be available at all birthing hospitals. In this study, we examined proximity to, and delivery at, a hospital with an appropriate level of perinatal care for pregnant women with CHDs and evaluated predictors of high travel distance to appropriate care. Appropriate care was defined as Level 3 perinatal hospitals and Regional Perinatal Centers (RPCs)., Methods: Inpatient delivery records for women with CHD in New York State (NYS) between 2008 and 2013 were obtained. Driving time and transit time were calculated between the pregnant woman's residence and the actual delivery hospital as well as the closest Level 3 or RPC hospital using Geographic Information Systems (GIS). Linear and logistic regression models evaluated predictors of high distance to, and utilization of, appropriate delivery care respectively., Results: From 2008 to 2013, there were 909 deliveries in a NYS hospital by women with CHDs. Approximately 75% of women delivered at a Level 3 or RPC hospital. Younger women, those who reside in rural and smaller urban areas, and those who are non-Hispanic White had a greater drive time to an appropriate care facility. After adjustment for geographic differences, racial/ethnic minorities and poor women were less likely to deliver at an appropriate delivery care center., Conclusions: Although most women with CHDs in NYS receive appropriate delivery care, there are some geographic and socio-demographic differences that require attention to ensure equitable access.

Background: Regional National Weather Service (NWS) heat advisory criteria in New York State (NYS) were based on frequency of heat events estimated by sparse monitoring data. These may not accurately reflect temperatures at which specific health risks occur in large geographic regions. The objectives of the study were to use spatially resolved temperature data to characterize health risks related to summertime heat exposure and estimate the temperatures at which excessive risk of heat-related adverse health occurs in NYS. We also evaluated the need to adjust current heat advisory threshold and messaging based on threshold temperatures of multiple health outcomes., Methods: We assessed the effect of multi-day lag exposure for maximum near-surface air temperature (T max) and maximum Heat Index derived from the gridded National Land Data Assimilation System (NLDAS) reanalysis dataset on emergency department (ED) visits/ hospitalizations for heat stress, dehydration, acute kidney failure (AKF) and cardiovascular diseases (CVD) using a case-crossover analysis during summers of 2008-2012. We assessed effect modification using interaction terms and stratified analysis. Thresholds were estimated using piecewise spline regression., Results: We observed an increased risk of heat stress (Risk ratio (RR) = 1.366, 95% confidence interval (CI): 1.347, 1.386) and dehydration (RR = 1.024, 95% CI: 1.021, 1.028) for every 1 °C increase in T max on the day of exposure. The highest risk for AKF (RR = 1.017, 95% CI: 1.014, 1.021) and CVD (RR = 1.001, 95% CI: 1.000, 1.002) were at lag 1 and 4 respectively. The increased risk of heat-health effects persists up to 6 days. Rural areas of NYS are at as high a risk of heat-health effects as urban areas. Heat-health risks start increasing at temperatures much lower than the current NWS criteria., Conclusion: Reanalysis data provide refined exposure-response functions for health research, in areas with sparse monitor observations. Based on this research, rural areas in NYS had similar risk for health effects of heat. Heat advisories in New York City (NYC) had been reviewed and lowered previously. As such, the current NWS heat advisory threshold was lowered for the upstate region of New York and surrounding areas. Enhanced outreach materials were also developed and disseminated to local health departments and the public.

Objective: A time-series study was used to assess the effect of temperature variation during summer on respiratory disease in New York State., Methods: Daily respiratory admissions were linked with various meteorological indicators including daily and weekly temperature variation from June-August, 1991-2004. Two-stage Bayesian hierarchical models were used to first compute percent excess risks at the region level while controlling for air pollutants and time-varying variables using Poisson generalized additive models, and then to pool statewide estimates together after controlling for regional confounders., Results: This study found that the daily temperature range between maximum and minimum temperature was associated with a 0·27-0·38% increased risk of admission. Minimum temperature (TMIN) above the previous 6-day average was associated with a 0·93% higher risk of respiratory morbidity. Multiday temperature ranges within 5 and 7 days were associated with 0·49 and 0·73% increases in admissions, respectively., Conclusions: We concluded that daily and multiday temperature variation may increase respiratory hospitalizations with a larger risk associated with TMIN.