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Autism Secondary Data Analysis Research (Autism SDAR)

Sector: Government • Location: United States of America

Source: Grants.gov

Project
Closed

The purpose of the SDAR program is to support research that analyzes existing national data sets and/or administrative records to answer questions that can improve the health and well-being of MCH populations, including children and teenagers with autism spectrum disorders and other developmental disabilities (ASD/DD). The SDAR program helps researchers use existing data sets to identify new issue

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The project “Autism Secondary Data Analysis Research (Autism SDAR)” is an infrastructure initiative in the Government sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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Description

Description

The purpose of the SDAR program is to support research that analyzes existing national data sets and/or administrative records to answer questions that can improve the health and well-being of MCH populations, including children and teenagers with autism spectrum disorders and other developmental disabilities (ASD/DD). The SDAR program helps researchers use existing data sets to identify new issues, study new research questions, test hypotheses, and determine pathways for intervention. Existing and new public health challenges affecting MCH populations, including children with special health care needs (MCH SDAR) and children and adolescents with ASD/DD (Autism SDAR), require timely, evidence-based responses from programs, policy, and practice. Without sufficient evidence or data, it is hard to develop interventions addressing both existing and new issues. SDAR research projects should help address any of the following HRSA’s Strategic Plan Objectives: • 1.4 Incorporate health equity concepts and measures into programs and policies; • 2.3 Improve the quality, safety, and effectiveness of health services for underserved populations and those in need; and • 2.4 Enhance maternal and child health efforts and reduce disparities in morbidity, mortality, and health outcomes.

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Source reliability

High

Data quality score

100%

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