State-level estimation of diabetes and prediabetes prevalence: Combining national and local survey data and clinical data.
Stat Med
; 37(27): 3975-3990, 2018 11 30.
Article
em En
| MEDLINE
| ID: mdl-29931829
ABSTRACT
Many statisticians and policy researchers are interested in using data generated through the normal delivery of health care services, rather than carefully designed and implemented population-representative surveys, to estimate disease prevalence. These larger databases allow for the estimation of smaller geographies, for example, states, at potentially lower expense. However, these health care records frequently do not cover all of the population of interest and may not collect some covariates that are important for accurate estimation. In a recent paper, the authors have described how to adjust for the incomplete coverage of administrative claims data and electronic health records at the state or local level. This article illustrates how to adjust and combine multiple data sets, namely, national surveys, state-level surveys, claims data, and electronic health record data, to improve estimates of diabetes and prediabetes prevalence, along with the estimates of the method's accuracy. We demonstrate and validate the method using data from three jurisdictions (Alabama, California, and New York City). This method can be applied more generally to other areas and other data sources.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Estado Pré-Diabético
/
Estatística como Assunto
/
Diabetes Mellitus
Tipo de estudo:
Prevalence_studies
/
Risk_factors_studies
Limite:
Humans
País/Região como assunto:
America do norte
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article