Open AccessDeveloping and Testing Electronic Health Record-Derived Caries Indices
Author(s) -
Joel M. White,
Elizabeth Mertz,
Joanna Mullins,
Joshua Even,
T. W. Guy,
Elena Blaga,
Aubri Kottek,
Shria Kumar,
Suhasini Bangar,
Ram Vaderhobli,
Ryan Brandon,
William Santo,
Larry Jenson,
Stuart A. Gansky
Publication year - 2019
Publication title -
caries research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.355
H-Index - 100
eISSN - 1421-976X
pISSN - 0008-6568
DOI - 10.1159/000499700
Subject(s) - concordance , medicine , verdict , electronic health record , dentistry , population , statistics , test (biology) , mathematics , health care , environmental health , political science , law , biology , economic growth , paleontology , economics
Caries indices, the basis of epidemiologic caries measures, are not easily obtained in clinical settings. This study’s objective was to design, test, and validate an automated program (Valid Electronic Health Record Dental Caries Indices Calculator Tool [VERDICT]) to calculate caries indices from an electronic health record (EHR). Synthetic use case scenarios and actual patient cases of primary, mixed, and permanent dentition, including decayed, missing, and filled teeth (DMFT/dmft) and tooth surfaces (DMFS/dmfs) were entered into the EHR. VERDICT measures were compared to a previously validated clinical electronic data capture (EDC) system and statistical program to calculate caries indices. Four university clinician-researchers abstracted EHR caries exam data for 45 synthetic use cases into the EDC and post-processed with SAS software creating a gold standard to compare the VERDICT-derived caries indices. Then, 2 senior researchers abstracted EHR caries exam data and calculated caries indices for 24 patients, allowing further comparisons to VERDICT indices. Agreement statistics were computed among abstractors, and discrepancies were resolved by consensus. Agreement statistics between the 2 final-phase abstractors and the VERDICT measures showed extremely high concordance: Lin’s concordance coefficients (LCCs) >0.99 for dmfs, dmft, DS, ds, DT, dt, ms, mt, FS, fs, FT, and ft; LCCs >0.95 for DMFS and DMFT; and LCCs of 0.92–0.93 for MS and MT. Caries indices, essential to developing primary health outcome measures for research, can be reliably derived from an EHR using VERDICT. Using these indices will enable population oral health management approaches and inform quality improvement efforts.