Literature DB >> 31167186

Developing and Testing Electronic Health Record-Derived Caries Indices.

Joel M White1,2, Elizabeth A Mertz3,4,5, Joanna M Mullins6, Joshua B Even6, Trey Guy6, Elena Blaga6, Aubri M Kottek4,5, Shwetha V Kumar7, Suhasini Bangar7, Ram Vaderhobli3, Ryan Brandon6, William Santo3,4, Larry Jenson3, Stuart A Gansky3,4,5,8.   

Abstract

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.
© 2019 S. Karger AG, Basel.

Entities:  

Keywords:  Caries detection/diagnosis/prevention; Dental informatics/bioinformatics; Electronic dental records; Epidemiology; Outcomes research

Mesh:

Year:  2019        PMID: 31167186      PMCID: PMC6864222          DOI: 10.1159/000499700

Source DB:  PubMed          Journal:  Caries Res        ISSN: 0008-6568            Impact factor:   4.056


  27 in total

Review 1.  Changes in dental caries 1953-2003.

Authors:  T M Marthaler
Journal:  Caries Res       Date:  2004 May-Jun       Impact factor: 4.056

2.  A qualitative investigation of the content of dental paper-based and computer-based patient record formats.

Authors:  Titus Schleyer; Heiko Spallek; Pedro Hernández
Journal:  J Am Med Inform Assoc       Date:  2007-04-25       Impact factor: 4.497

3.  Comparison of paper-based and electronic data collection process in clinical trials: costs simulation study.

Authors:  Ivan Pavlović; Tomaz Kern; Damijan Miklavcic
Journal:  Contemp Clin Trials       Date:  2009-04-02       Impact factor: 2.226

4.  Using your electronic medical record for research: a primer for avoiding pitfalls.

Authors:  Amanda L Terry; Vijaya Chevendra; Amardeep Thind; Moira Stewart; J Neil Marshall; Sonny Cejic
Journal:  Fam Pract       Date:  2009-10-14       Impact factor: 2.267

5.  Lessons learned during the conduct of clinical studies in the dental PBRN.

Authors:  Gregg H Gilbert; Joshua S Richman; Valeria V Gordan; D Brad Rindal; Jeffrey L Fellows; Paul L Benjamin; Martha Wallace-Dawson; O Dale Williams
Journal:  J Dent Educ       Date:  2011-04       Impact factor: 2.264

6.  Clinician attitudes, skills, motivations and experience following the implementation of clinical decision support tools in a large dental practice.

Authors:  Elizabeth Mertz; Cynthia Wides; Joel White
Journal:  J Evid Based Dent Pract       Date:  2016-10-20       Impact factor: 5.267

7.  Validation of the Use of Electronic Health Records for Classification of ADHD Status.

Authors:  Siobhan M Gruschow; Benjamin E Yerys; Thomas J Power; Dennis R Durbin; Allison E Curry
Journal:  J Atten Disord       Date:  2016-10-01       Impact factor: 3.256

8.  Examination criteria and calibration procedures for prevention trials of the Early Childhood Caries Collaborating Centers.

Authors:  John J Warren; Karin Weber-Gasparoni; Norman Tinanoff; Terence S Batliner; Bonnie Jue; William Santo; Raul I Garcia; Stuart A Gansky
Journal:  J Public Health Dent       Date:  2015-05-22       Impact factor: 1.821

9.  Validation of electronic health record phenotyping of bipolar disorder cases and controls.

Authors:  Victor M Castro; Jessica Minnier; Shawn N Murphy; Isaac Kohane; Susanne E Churchill; Vivian Gainer; Tianxi Cai; Alison G Hoffnagle; Yael Dai; Stefanie Block; Sydney R Weill; Mireya Nadal-Vicens; Alisha R Pollastri; J Niels Rosenquist; Sergey Goryachev; Dost Ongur; Pamela Sklar; Roy H Perlis; Jordan W Smoller
Journal:  Am J Psychiatry       Date:  2014-12-12       Impact factor: 18.112

10.  Inequalities of caries experience in Nevada youth expressed by DMFT index vs. Significant Caries Index (SiC) over time.

Authors:  Marcia Ditmyer; Georgia Dounis; Connie Mobley; Eli Schwarz
Journal:  BMC Oral Health       Date:  2011-04-05       Impact factor: 2.757

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  1 in total

1.  Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records.

Authors:  Suhasini Bangar; Ana Neumann; Joel M White; Alfa Yansane; Todd R Johnson; Gregory W Olson; Shwetha V Kumar; Krishna K Kookal; Aram Kim; Enihomo Obadan-Udoh; Elizabeth Mertz; Kristen Simmons; Joanna Mullins; Ryan Brandon; Muhammad F Walji; Elsbeth Kalenderian
Journal:  Appl Clin Inform       Date:  2022-01-19       Impact factor: 2.342

  1 in total

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