The Utility of Synthetic and Regression Estimation

Techniques for Local Health Planning

Datos Bibliográficos

ID9104814
AutoresEllen J Mackenzie (0000-0002-5480-8502, Johns Hopkins University, autor de correspondencia), Sam Shapiro (Health Services Research & Development, autor de correspondencia), Richard Yaffe (Centers for Medicare and Medicaid Services)
Año1985
Volumen23
Número1
Páginas1-13
Fecha de publicación1985-01-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaMedical Care (JOURNAL)
Identificadores de la revistaISSN: 0025-7079 • E-ISSN: 1537-1948
EditorialOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/00005650-198501000-00001
PMID3968919
OpenAlexW2035931360
IdiomaEN
Citas recibidas3

Health planning agencies have long had a need for local area data on issues such as health status, utilization, and preventive care. Synthetic estimation and regression techniques have been advanced for use in adjusting national or regional data from the NCHS Health Interview Survey (HIS) to the local area based on demographic and other pertinent variables. To evaluate the accuracy and utility of these techniques for local health planning, estimates of certain key HIS variables were obtained from a telephone survey of 2,500 randomly selected households located in the Central Maryland Health Systems Agency (CMHSA). This paper presents results of the comparison between these telephone estimates and the corresponding estimates derived from the national HIS. The techniques are evaluated on the basis of data generally available to local planning agencies

Agency (philosophy) · Econometrics · Estimation · Regression · Regression analysis · Statistics · Survey data collection · Computer Science · Engineering · Food Security and Health in Diverse Populations · Health disparities and outcomes · Healthcare Policy and Management · Mathematics