National health statistics reports最新文献

Background-Administrative data from medical claims are often used for injury surveillance. Effective October 1, 2015, hospitals covered by the Health Insurance Portability and Accountability Act were required to use the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) to report medical information in administrative data. In 2017, the National Center for Health Statistics (NCHS) and the National Center for Injury Prevention and Control (NCIPC) published a proposed ICD-10-CM surveillance case definition for injuryrelated emergency department (ED) visits. At the time, ICD-10-CM coded data were not available for testing. When data became available, NCHS and NCIPC collaborated with the Council of State and Territorial Epidemiologists and epidemiologists from state and local health departments to test and update the proposed definition. This report summarizes the results and presents the 2021 revised ICD-10-CM surveillance case definition.

Objective-This report presents prevalence estimates of prescription opioid use among U.S. adults with chronic pain.

Objective-This report examines differences in survey reports of disability between two sets of disability questions, the Short Set on Functioning (WG-SS) developed by the Washington Group on Disability Statistics (WG) and a set of disability questions developed for the American Community Survey (ACS).

Objective-This report presents trends in mean weight, recumbent length, height, waist circumference, and body mass index (BMI) among children and adolescents in the United States from 1999 through 2018.

Background-The National Cancer Institute (NCI) Joinpoint regression software is a widely used software program for evaluating trends. In addition to producing model estimates for trend models, this software can search for changes in slope along the trend line. One component of the software, which tests whether line segment slopes are zero, is different from the usual t-test of zero slope that is used in linear models. This report will demonstrate this Joinpoint software procedure through replication using the SAS Institute's statistical software (that is, SAS) and discuss the implications of the different assumptions used by Joinpoint and a typical SAS model for the test of zero slope. Methods-First, Joinpoint's procedure for testing a zero slope is compared with a typical test of zero slope using SAS, and the assumptions behind both approaches are evaluated. Second, the test from the Joinpoint software is replicated in SAS using its PROC REG procedure and additional SAS programming. Trend analyses of rates of drug overdose deaths involving fentanyl from the general population and among females are used as examples. Results-In the evaluation of the trend of drug overdose deaths for the total population, Joinpoint produces a similar result to the linear model test in SAS. For the female subgroup, however, Joinpoint and SAS produce differing results for the test of zero slope. The replication of the Joinpoint test of zero slope using SAS demonstrates that Joinpoint's procedure is based on fewer degrees of freedom, which results in a larger standard error estimate. Conclusion-The Joinpoint approach accounts for the fact that the joinpoints are estimated and thus leads to a more conservative hypothesis test, particularly when the number of points in a trend analysis is small.