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1.
Natl Health Stat Report ; (116): 1-11, 2018 08.
Article in English | MEDLINE | ID: mdl-30248014

ABSTRACT

This report demonstrates the use of the National Hospital Care Survey (NHCS) for the study of pneumonia inpatient hospitalizations and emergency department (ED) visits. The analysis is based on unweighted data of inpatient and ED encounters from the 2014 NHCS and is intended to illustrate the capabilities of the survey, including the ability to link inpatient hospitalizations or ED visits across settings and with other data sources, once hospital participation allows for nationally representative estimates.


Subject(s)
Emergency Service, Hospital , Health Care Surveys , Hospitalization , Pneumonia , Adolescent , Adult , Aged , Critical Care , Emergency Service, Hospital/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , Patient Discharge , Pneumonia/diagnosis , Pneumonia/mortality , United States/epidemiology , Young Adult
2.
Inquiry ; 40(4): 401-15, 2003.
Article in English | MEDLINE | ID: mdl-15055838

ABSTRACT

Until recently, sample design information needed to correctly estimate standard errors from the National Ambulatory Medical Care Survey (NAMCS) and the National Hospital Ambulatory Medical Care Survey (NHAMCS) public use files was not released for confidentiality reasons. In 2002, masked sample design variables were released for the first time with the 1995-2000 NAMCS and NHAMCS public use files. This paper shows how to use masked design variables to compute standard errors in three software applications. It also discusses when masking overstates or understates "in-house" standard errors, and how masking affects the significance levels of point estimates and logistic regression parameters.


Subject(s)
Ambulatory Care/statistics & numerical data , Bias , Emergency Service, Hospital/statistics & numerical data , Health Care Surveys/methods , Health Care Surveys/statistics & numerical data , Office Visits/statistics & numerical data , Outpatient Clinics, Hospital/statistics & numerical data , Adolescent , Adult , Aged , Child , Child, Preschool , Cluster Analysis , Data Collection/methods , Database Management Systems , Female , Humans , Infant , Infant, Newborn , Logistic Models , Male , Middle Aged , Models, Statistical , National Center for Health Statistics, U.S. , Probability , United States
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