Hannah L Maxey1, Connor W Norwood1, Sierra X Vaughn1, Yumin Wang1,2, Stacie Marsh1, John Williams3. 1. Department of Family Medicine, Bowen Center for Health Workforce Research & Policy, Indiana University School of Medicine, Indianapolis, IN, USA. 2. Department of Biostatistics, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA. 3. Office of the Dean, Indiana University School of Dentistry, Indianapolis, IN, USA.
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.
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.
Authors: Caroline K Geiger; Ashley M Kranz; Andrew W Dick; Erin Duffy; Mark Sorbero; Bradley D Stein Journal: J Rural Health Date: 2018-12-07 Impact factor: 4.333
Authors: Evan V Goldstein; Andrew W Dick; Rachel Ross; Bradley D Stein; Ashley M Kranz Journal: J Public Health Dent Date: 2021-01-06 Impact factor: 2.258