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Estimation of oral disease burden from claims and self‐reported data
Author(s) -
Okunseri Christopher,
FrantsveHawley Julie,
ThakkarSamtani Madhuli,
Okunev IIya,
Heaton Lisa J.,
Tranby Eric P.
Publication year - 2022
Publication title -
journal of public health dentistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.64
H-Index - 63
eISSN - 1752-7325
pISSN - 0022-4006
DOI - 10.1111/jphd.12550
Subject(s) - medicaid , medical expenditure panel survey , medicine , population , family medicine , dental insurance , oral health , gerontology , environmental health , health care , health insurance , economics , economic growth
Objective To compare the use of Medicaid and commercial claims data with self‐reported survey data in estimating the prevalence of oral disease burden. Methods We analyzed 2018 Medicaid claims from the IBM Watson Medicaid Marketscan database, commercial claims from the IBM Dental Database, and Medical Expenditure Panel Survey (MEPS) data. The estimate of oral disease burden was based on standard metrics using periodontal and caries‐related Current Dental Terminology (CDT) procedure codes. A direct comparison between the data sets was also done. Results Unweighted Medicaid and commercial enrollees were 11.6 and 10.5 million, respectively. The weighted proportion from MEPS for Medicaid and commercial plans ranged from 80 to 208 million people. Estimates of caries‐related treatments were calculated from IBM Watson and MEPS data for Medicaid enrollees (13% vs. 12%, respectively) and commercial claims (25% vs. 17%, respectively). Prevalence of periodontal related treatments for those with a dental visit was estimated for IBM Watson and MEPS enrollees for Medicaid (0.7% vs. 0.5%, respectively) and commercial claims (7% vs. 1.6%, respectively). Dental disease estimates were higher in individuals with at least one dental visit across cohorts. Prevalence of disease for those with a dental visit based on specific procedures were higher in commercial plans than in Medicaid. Conclusions Claims data has the potential to serve as a proxy measure for the estimate of dental disease burden in a population.