# Access to Preventive Dental Care for Children in the United States

> **NIH NIH R01** · GEORGIA INSTITUTE OF TECHNOLOGY · 2021 · $364,212

## Abstract

PROJECT SUMMARY
Oral health was cited as the greatest unmet health need in the United States, greatly affecting
the nation's poor children. Access to preventive dental care in all its dimensions, affordability,
accessibility, availability, acceptability and accommodation, is a precursor of utilization of
preventive care services, which have been shown to be effective in averting caries and severe
oral health outcomes. Identifying and advancing interventions to address access to preventive
dental care for children requires rigorous modeling to reliably estimate access, to make
inferences under uncertainty of factors impacting dental care delivery and to quantify how
interventions might change the access to care given limited resources.
 The proposed objective is to support informed and reliable policy making and interventions for
access to dental care for children at the national level. This proposal will establish a rigorous
framework for studying access to preventive dental care for children. This framework not only
will contribute towards addressing the primary limitations in the existing research for spatial
access to dental care for children but also it will provide inferences on interventions to improve
access. The proposed framework takes a system approach in modeling access, accounting for
constraints in the system including mobility, user choice, willingness to travel, Medicaid
participation and acceptance ratios of dental services providers, Medicaid reimbursement
policies, congestion and capacity constraints. The access estimates are complemented by
statistical inference, employed to identify communities with greatest unmet dental care need.
The proposed modeling is further employed to evaluate potential interventions, and analyze the
impact that optimal policy changes and network interventions would have on spatial access and
outcomes of the overall system, specific population subgroups, and areas of greatest shortage.
Because the models are computationally expensive, particularly, when applied to large
geographic areas and in the context of statistical inference, we also propose a distributed
computing approach to solve the underlying mathematical access model; the distributed
computational approach is particularly important in the inference on interventions.
 The proposed research will build on multiple datasets already acquired by the research
team. The primary source of data consists of the Medicaid Analytical eXtract (MAX) claims data
for the U.S. acquired from the Centers for Medicare and Medicaid Services (CMS). We will
implement the proposed modeling approach to 45 states in the U.S.—states were excluded
because of data availability and/or quality limitations.

## Key facts

- **NIH application ID:** 10149985
- **Project number:** 5R01DE028283-04
- **Recipient organization:** GEORGIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Nicoleta Serban
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $364,212
- **Award type:** 5
- **Project period:** 2018-09-07 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10149985

## Citation

> US National Institutes of Health, RePORTER application 10149985, Access to Preventive Dental Care for Children in the United States (5R01DE028283-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10149985. Licensed CC0.

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