The Utility of Synthetic and Regression Estimation

Techniques for Local Health Planning

Dados Bibliográficos

ID9104814
AutoresEllen J Mackenzie (0000-0002-5480-8502, Johns Hopkins University, autor correspondente), Sam Shapiro (Health Services Research & Development, autor correspondente), Richard Yaffe (Centers for Medicare and Medicaid Services)
Ano1985
Volume23
Fascículo1
Páginas1-13
Data de publicação1985-01-01
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoMedical Care (JOURNAL)
Identificadores do periódicoISSN: 0025-7079 • E-ISSN: 1537-1948
EditoraOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/00005650-198501000-00001
PMID3968919
OpenAlexW2035931360
IdiomaEN
Citações recebidas3

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