Sampling Procedures for the Collection of Electronic Health Record Data From Federally Qualified Health Centers, 2021-2022 National Ambulatory Medical Care Survey.

As part of modernization efforts, in 2021 the National Ambulatory Medical Care Survey (NAMCS) began collecting electronic health records (EHRs) for ambulatory care visits in its Health Center (HC) Component. As a result, the National Center for Health Statistics (NCHS)needed to adjust the approaches used in the sampling design for the HC Component. This report provides details on these changes to the 2021-2022 NAMCS.

National Center for Health Statistics Data Presentation Standards for Proportions.

The National Center for Health Statistics (NCHS) disseminates information on a broad range of health topics through diverse publications. These publications must rely on clear and transparent presentation standards that can be broadly and efficiently applied. Standards are particularly important for large, cross-cutting reports where estimates cannot be individually evaluated and indicators of precision cannot be included alongside the estimates.

Nonresponse Bias in Estimates From the 2012 National Ambulatory Medical Care Survey.

Background: The National Ambulatory Medical Care Survey (NAMCS) is an annual, nationally representative sample survey of physicians and of visits to physicians. Two major changes were made to the 2012 NAMCS to support reliable state estimates. The sampling design changed from an area sample to a fivefold-larger list sample of physicians stratified by the nine U.

A Note on the Effect of Data Clustering on the Multiple-Imputation Variance Estimator: A Theoretical Addendum to , .

Multiple imputation is a popular approach to handling missing data. Although it was originally motivated by survey nonresponse problems, it has been readily applied to other data settings. However, its general behavior still remains unclear when applied to survey data with complex sample designs, including clustering.

Determining Sufficient Number of Imputations Using Variance of Imputation Variances: Data from 2012 NAMCS Physician Workflow Mail Survey.

How many imputations are sufficient in multiple imputations? The answer given by different researchers varies from as few as 2 - 3 to as many as hundreds. Perhaps no single number of imputations would fit all situations. In this study, , the minimally sufficient number of imputations, was determined based on the relationship between , the number of imputations, and , the standard error of imputation variances using the 2012 National Ambulatory Medical Care Survey (NAMCS) Physician Workflow mail survey.

Negative Binomials Regression Model in Analysis of Wait Time at Hospital Emergency Department.

Wait time is the differences between the time a patient arrives in the emergency department (ED) and the time an ED provider examines that patient. This study focuses on the development of a negative binomial model to examine factors associated with ED wait time using the National Hospital Ambulatory Medical Care Survey (NHAMCS). Conducted by National Center for Health Statistics (NCHS), NHAMCS has been gathering, analyzing, and disseminating information annually about visits made for medical care to hospital outpatient department and EDs since 1992.

Lessons from the 2006 Louisiana health and population survey.

The 2005 hurricane season caused extensive damage and induced a mass migration of approximately 1.1 million people from southern Louisiana in the United States. Current and accurate estimates of population size and demographics and an assessment of the critical needs for public services were required to guide recovery efforts.

Hospital preparedness for emergency response: United States, 2008.

Objective: This report is a summary of hospital preparedness for responding to public health emergencies, including mass casualties and epidemics of naturally occurring diseases such as influenza.

Methods: Data are from an emergency response preparedness supplement to the 2008 National Hospital Ambulatory Medical Care Survey, which uses a national probability sample of nonfederal general and short-stay hospitals in the United States. Sample data were weighted to produce national estimates.

Redesign and operation of the National Home And Hospice Care Survey, 2007.

Objectives: This methods report provides an overview of the redesigned National Home and Hospice Care Survey (NHHCS) conducted in 2007. NHHCS is a national probability sample survey that collects data on U.S.

Linked surveys of health services utilization.

The linked population/establishment survey (LS) of health services utilization is a two-phase sample survey that links the sample designs of the population sample survey (PS) and the health-care provider establishment sample survey (ES) of health services utilization. In Phase I, household respondents in the PS identify their health-care providers during a specified calendar period. In Phase II, health-care providers identified in Phase I report the variables of interest for all or a sample of their transactions with all households during the same calendar period.

Effects of form length and item format on response patterns and estimates of physician office and hospital outpatient department visits. National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey, 2001.

Objectives: This report describes effects due to form length and/or item formats on respondent cooperation and survey estimates.

Methods: Two formats were used for the Patient Record form for the 2001 NAMCS and OPD component of the NHAMCS: a short form with 70 subitems and a long form with 140 subitems. The short form also contained many write-in items and fit on a one-sided page.

Guide to using masked design variables to estimate standard errors in public use files of the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey.

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.

Combining estimates from complementary surveys: a case study using prevalence estimates from national health surveys of households and nursing homes.

Objectives: When a single survey does not cover a domain of interest, estimates from two or more complementary surveys can be combined to extend coverage. The purposes of this article are to discuss and demonstrate the benefits of combining estimates from complementary surveys and to provide a catalog of the analytic issues involved.

Methods: The authors present a case study in which data from the National Health Interview Survey and the National Nursing Home Survey were combined to obtain prevalence estimates for several chronic health conditions for the years 1985, 1995, and 1997.