Annual report, standard analysis files and an online query system from the national data registry on the end-stage renal disease (ESRD) population in the U.S., including treatments and outcomes. The Annual Data Report is divided into two parts. The Atlas section displays data using graphs and charts. Specific chapters address trends in ESRD patient populations, quality of ESRD care, kidney transplantation outcomes, costs of ESRD care, Healthy People 2010 objectives, chronic kidney disease, pediatric ESRD, and cardiovascular disease special studies. The Reference Tables are devoted entirely to the ESRD population. The RenDER (Renal Data Extraction and Referencing) online data query system allows users to build data tables and maps for the ESRD population. National, state, and county level data are available. USRDS staff collaborates with members of Centers for Medicare & Medicaid Services (CMS), the United Network for Organ Sharing (UNOS), and the ESRD networks, sharing datasets and actively working to improve the accuracy of ESRD patient information.

NCHS has linked data from various surveys with End Stage Renal Disease (ESRD) data obtained from the United States Renal Data System (USRDS). Linkage of the data from NCHS survey participants with the USRDS ESRD data provides the opportunity to study changes in health status and health care utilization among patients diagnosed with ESRD.

This dataset tracks the updates made on the dataset "NCHS Survey Data Linked to United States Renal Data System (USRDS) End-Stage Renal Disease Files" as a repository for previous versions of the data and metadata.

The USRDS is the largest and most comprehensive national ESRD surveillance system in the US (Collins et al., 2015). The USRDS contains data on all ESRD cases in the US through the Medical Evidence Report CMS-2728 which is mandated for all new patients diagnosed with ESRD (Foley and Collins, 2013). Detailed information about the USRDS can be found on their website (http://www.usrds.org). The EQI was constructed for 2000-2005 for all US counties and is composed of five domains (air, water, built, land, and sociodemographic), each composed of variables to represent the environmental quality of that domain. Domain-specific EQIs were developed using principal components analysis (PCA) to reduce these variables within each domain while the overall EQI was constructed from a second PCA from these individual domains (L. C. Messer et al., 2014). To account for differences in environment across rural and urban counties, the overall and domain-specific EQIs were stratified by rural urban continuum codes (RUCCs) (U.S. Department of Agriculture, 2015). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data stored as csv files. This dataset is associated with the following publication: Kosnik, M., D. Reif, D. Lobdell, T. Astell-Burt, X. Feng, J. Hader, and J. Hoppin. Associations between access to healthcare, environmental quality, and end-stage renal disease survival time: Proportional-hazards models of over 1,000,000 people over 14 years. PLoS ONE. Public Library of Science, San Francisco, CA, USA, 14(3): e0214094, (2019).

Background and objectivePrevious reports indicated that patients on thrice-weekly hemodialysis (HD) had higher mortality rates after the 3-day interdialytic interval. However, day-of-the-week patterns of emergency department (ED) visits and hospitalizations remain under-investigated.MethodsWe conducted a retrospective cohort study of HD patients on thrice-weekly dialysis, using 2013 data from the United States Renal Data System (USRDS). We estimated crude incidence rates of ED visits and hospitalizations by day of the week and dialysis schedule (Monday, Wednesday, Friday or Tuesday, Thursday, Saturday). Using Poisson regression, we estimated case-mix adjusted rate ratios of all-cause ED visits and hospitalizations, and adjusted rates of cause-specific ED visits and hospitalizations.ResultsWe identified 241,093 eligible HD patients in 2013, who had 514,773 ED visits and 301,674 hospitalizations that year. Three distinct but related patterns of outcome events were observed. Crude and adjusted incidence rates of all-cause, cardiovascular, and infection-related ED visits and hospitalizations, but not vascular-access-related events, were higher on all three HD treatment days (“dialysis-day effect”). Rates for ED visits and hospitalizations were lower on weekends than weekdays, rising appreciably from Sunday to Monday for both dialysis schedules (“post-weekend effect”); and rates were highest after the long 3-day interval between dialysis sessions for both dialysis schedules (“interdialytic-gap effect”). In contrast, rates of hospitalizations not preceded by an ED visit were nearly the same Monday through Friday and lower on weekends for both dialysis schedules.ConclusionsHigher rates of ED visits and hospitalizations on the days of HD sessions and early in the week are a public-health concern that should stimulate research to explain these patterns and reduce the excessive morbidity and associated costs among patients on thrice-weekly HD, while improving quality of care and patient experience with dialysis.

Number and rate (per year) of all-cause total ED visits, ED visits followed by hospital admission, ED visits not followed by hospital admission, total hospital admissions, and hospital admission not preceded by an ED visit, among in-center HD patients, by dialysis schedule and day of the week.

Summary of demographic characteristics [percentage or means (standard deviation)] of in-center HD patients by dialysis schedule, in 2013.