ArticlePharmacoEconomics2016
National Database for Autism Research (NDAR): Big Data Opportunities for Health Services Research and Health Technology Assessment.
Article in PharmacoEconomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed, 2 syntheses or guidelines pooled it, 89 citations in OpenAlex.
- A Systematic Review of Techniques and Sources of Big Data in the Healthcare Sector.Journal of medical systems · 2017Pooled it
- A systematic review and meta-analysis of comprehensive interventions for pre-school children with autism spectrum disorder (ASD).PloS one · 2017Pooled it
- AI and neuroimaging in autism spectrum disorder: advances in diagnosis, methodological challenges and future directions.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Review
- Costs of autism spectrum disorders and access to services in Spain.BMC health services research · 2026Observational
- Adaptive Behavior Change in Autism: Outcomes from a Comprehensive, Interdisciplinary Clinical Care Cohort.Journal of personalized medicine · 2026Article
- Lifespan Tree of Brain Anatomy: Diagnostic Values for Motor and Cognitive Neurodegenerative Diseases.Human brain mapping · 2025Article
- Applications of artificial intelligence and the challenges in health technology assessment: a scoping review and framework with a focus on economic dimensions.Health economics review · 2025Review
- A foundation model for enhancing magnetic resonance images and downstream segmentation, registration and diagnostic tasks.Nature biomedical engineering · 2025Article
- Cross-modal privacy-preserving synthesis and mixture-of-experts ensemble for robust ASD prediction.Frontiers in neuroinformatics · 2025Article
- A computational cognitive neuroscience approach for characterizing individual differences in autism: Introduction to Special Issue.Personality neuroscience · 2025Article
- The Challenges Ahead: Concepts, Analytics, and Ethics of Value-Based Care in Applied Behavior Analysis.Behavior analysis in practice · 2024Review
- Brain structure ages-A new biomarker for multi-disease classification.Human brain mapping · 2024Article
- Self-supervised learning with application for infant cerebellum segmentation and analysis.Nature communications · 2023Article
- Volumetric Analysis of Amygdala and Hippocampal Subfields for Infants with Autism.Journal of autism and developmental disorders · 2023Article
- Review
- A 4D infant brain volumetric atlas based on the UNC/UMN baby connectome project (BCP) cohort.NeuroImage · 2022Article
- Joint attention in infants at high familial risk for autism spectrum disorder and the association with thalamic and hippocampal macrostructure.Cerebral cortex communications · 2022Article
- Big Data Technology Oriented to Wetland Resource Ecosystem Value Evaluation.Computational intelligence and neuroscience · 2022Article
- Machine learning for autism spectrum disorder diagnosis using structural magnetic resonance imaging: Promising but challenging.Frontiers in neuroinformatics · 2022Review
- EYE-C: Eye-Contact Robust Detection and Analysis during Unconstrained Child-Therapist Interactions in the Clinical Setting of Autism Spectrum Disorders.Brain sciences · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
The National Database for Autism Research (NDAR) is a US National Institutes of Health (NIH)-funded research data repository created by integrating heterogeneous datasets through data sharing agreements between autism researchers and the NIH. To date, NDAR is considered the largest neuroscience and genomic data repository for autism research. In addition to biomedical data, NDAR contains a large collection of clinical and behavioral assessments and health outcomes from novel interventions. Importantly, NDAR has a global unique patient identifier that can be linked to aggregated individual-level data for hypothesis generation and testing, and for replicating research findings. As such, NDAR promotes collaboration and maximizes public investment in the original data collection. As screening and diagnostic technologies as well as interventions for children with autism are expensive, health services research (HSR) and health technology assessment (HTA) are needed to generate more evidence to facilitate implementation when warranted. This article describes NDAR and explains its value to health services researchers and decision scientists interested in autism and other mental health conditions. We provide a description of the scope and structure of NDAR and illustrate how data are likely to grow over time and become available for HSR and HTA.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.