Dental safety net capacity: An innovative use of existing data to measure dentists' clinical engagement in state Medicaid programs

Hannah Maxey, Connor Whelan Norwood, Sierra X. Vaughn, Yumin Wang, Stacie Marsh, John Williams

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: The demand for dentists available for state Medicaid populations has long outpaced the supply of such providers. To help understand the workforce dynamics, this study sought to develop a novel approach to measuring dentists' relative contribution to the dental safety net and, using this new measurement, identify demographic and practice characteristics predictive of dentists' willingness to participate in Indiana's Medicaid program. Methods: We examined Medicaid claims data for 1,023 Indiana dentists. We fit generalized ordered logistic regression models to measure dentists' level of clinical engagement with Medicaid. Using a partial proportional odds specification model, we estimated proportional adjusted odds ratios for covariates and separate estimates for each contrast of nonproportional covariates. Results: Though 75% of Medicaid-enrolled dentists were active providers, only 27% of them had 800 or more claims during fiscal year 2015. As has been shown in previous studies, our findings from the proportional odds model reinforced certain demographic and practice characteristics to be predictive of dentists' participation in state Medicaid programs. Conclusions: In addition to confirming predictive factors for Medicaid enrollment, this study validated the clinical engagement measure as a reliable method to assess the level of Medicaid participation. Prior studies have been limited by self-reported data and variations in Medicaid claims reporting. Practical implications: Our findings have implications for state Medicaid policymakers by enabling access to data regarding dental providers' level of participation in Medicaid in addition to identifying factors predictive of such participation. This information will inform Medicaid program plans and provider recruitment efforts.

Original languageEnglish (US)
JournalJournal of Public Health Dentistry
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Medicaid
Dentists
Tooth
Safety
Logistic Models
Demography
Odds Ratio

Keywords

  • Access to care
  • Dental
  • Dental care
  • Health policy
  • Insurance
  • Medicaid
  • Medicaid participation
  • Public policy

ASJC Scopus subject areas

  • Dentistry(all)
  • Public Health, Environmental and Occupational Health

Cite this

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title = "Dental safety net capacity: An innovative use of existing data to measure dentists' clinical engagement in state Medicaid programs",
abstract = "Background: The demand for dentists available for state Medicaid populations has long outpaced the supply of such providers. To help understand the workforce dynamics, this study sought to develop a novel approach to measuring dentists' relative contribution to the dental safety net and, using this new measurement, identify demographic and practice characteristics predictive of dentists' willingness to participate in Indiana's Medicaid program. Methods: We examined Medicaid claims data for 1,023 Indiana dentists. We fit generalized ordered logistic regression models to measure dentists' level of clinical engagement with Medicaid. Using a partial proportional odds specification model, we estimated proportional adjusted odds ratios for covariates and separate estimates for each contrast of nonproportional covariates. Results: Though 75{\%} of Medicaid-enrolled dentists were active providers, only 27{\%} of them had 800 or more claims during fiscal year 2015. As has been shown in previous studies, our findings from the proportional odds model reinforced certain demographic and practice characteristics to be predictive of dentists' participation in state Medicaid programs. Conclusions: In addition to confirming predictive factors for Medicaid enrollment, this study validated the clinical engagement measure as a reliable method to assess the level of Medicaid participation. Prior studies have been limited by self-reported data and variations in Medicaid claims reporting. Practical implications: Our findings have implications for state Medicaid policymakers by enabling access to data regarding dental providers' level of participation in Medicaid in addition to identifying factors predictive of such participation. This information will inform Medicaid program plans and provider recruitment efforts.",
keywords = "Access to care, Dental, Dental care, Health policy, Insurance, Medicaid, Medicaid participation, Public policy",
author = "Hannah Maxey and Norwood, {Connor Whelan} and Vaughn, {Sierra X.} and Yumin Wang and Stacie Marsh and John Williams",
year = "2018",
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doi = "10.1111/jphd.12272",
language = "English (US)",
journal = "Journal of Public Health Dentistry",
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T2 - An innovative use of existing data to measure dentists' clinical engagement in state Medicaid programs

AU - Maxey, Hannah

AU - Norwood, Connor Whelan

AU - Vaughn, Sierra X.

AU - Wang, Yumin

AU - Marsh, Stacie

AU - Williams, John

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Background: The demand for dentists available for state Medicaid populations has long outpaced the supply of such providers. To help understand the workforce dynamics, this study sought to develop a novel approach to measuring dentists' relative contribution to the dental safety net and, using this new measurement, identify demographic and practice characteristics predictive of dentists' willingness to participate in Indiana's Medicaid program. Methods: We examined Medicaid claims data for 1,023 Indiana dentists. We fit generalized ordered logistic regression models to measure dentists' level of clinical engagement with Medicaid. Using a partial proportional odds specification model, we estimated proportional adjusted odds ratios for covariates and separate estimates for each contrast of nonproportional covariates. Results: Though 75% of Medicaid-enrolled dentists were active providers, only 27% of them had 800 or more claims during fiscal year 2015. As has been shown in previous studies, our findings from the proportional odds model reinforced certain demographic and practice characteristics to be predictive of dentists' participation in state Medicaid programs. Conclusions: In addition to confirming predictive factors for Medicaid enrollment, this study validated the clinical engagement measure as a reliable method to assess the level of Medicaid participation. Prior studies have been limited by self-reported data and variations in Medicaid claims reporting. Practical implications: Our findings have implications for state Medicaid policymakers by enabling access to data regarding dental providers' level of participation in Medicaid in addition to identifying factors predictive of such participation. This information will inform Medicaid program plans and provider recruitment efforts.

AB - Background: The demand for dentists available for state Medicaid populations has long outpaced the supply of such providers. To help understand the workforce dynamics, this study sought to develop a novel approach to measuring dentists' relative contribution to the dental safety net and, using this new measurement, identify demographic and practice characteristics predictive of dentists' willingness to participate in Indiana's Medicaid program. Methods: We examined Medicaid claims data for 1,023 Indiana dentists. We fit generalized ordered logistic regression models to measure dentists' level of clinical engagement with Medicaid. Using a partial proportional odds specification model, we estimated proportional adjusted odds ratios for covariates and separate estimates for each contrast of nonproportional covariates. Results: Though 75% of Medicaid-enrolled dentists were active providers, only 27% of them had 800 or more claims during fiscal year 2015. As has been shown in previous studies, our findings from the proportional odds model reinforced certain demographic and practice characteristics to be predictive of dentists' participation in state Medicaid programs. Conclusions: In addition to confirming predictive factors for Medicaid enrollment, this study validated the clinical engagement measure as a reliable method to assess the level of Medicaid participation. Prior studies have been limited by self-reported data and variations in Medicaid claims reporting. Practical implications: Our findings have implications for state Medicaid policymakers by enabling access to data regarding dental providers' level of participation in Medicaid in addition to identifying factors predictive of such participation. This information will inform Medicaid program plans and provider recruitment efforts.

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