Developing Automated Computer Algorithms to Phenotype Periodontal Disease Diagnoses in Electronic Dental Records.
Journal
Methods of information in medicine
ISSN: 2511-705X
Titre abrégé: Methods Inf Med
Pays: Germany
ID NLM: 0210453
Informations de publication
Date de publication:
12 2022
12 2022
Historique:
pubmed:
23
11
2022
medline:
28
12
2022
entrez:
22
11
2022
Statut:
ppublish
Résumé
Our objective was to phenotype periodontal disease (PD) diagnoses from three different sections (diagnosis codes, clinical notes, and periodontal charting) of the electronic dental records (EDR) by developing two automated computer algorithms. We conducted a retrospective study using EDR data of patients ( The completeness of PD diagnosis from the EDR was as follows: periodontal diagnosis codes 36% ( We successfully developed, tested, and deployed two automated algorithms on big EDR datasets to improve the completeness of PD diagnoses. After phenotyping, EDR provided 100% completeness of PD diagnoses of 27,138 unique patients for research purposes. This approach is recommended for use in other large databases for the evaluation of their EDR data quality and for phenotyping PD diagnoses and other relevant variables.
Identifiants
pubmed: 36413995
doi: 10.1055/s-0042-1757880
pmc: PMC9788909
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e125-e133Informations de copyright
The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
Déclaration de conflit d'intérêts
None declared.
Références
J Am Med Inform Assoc. 2013 Dec;20(e2):e341-8
pubmed: 24190931
Oper Dent. 2021 May 01;46(3):263-270
pubmed: 34411254
Appl Clin Inform. 2017 Aug 02;8(3):794-809
pubmed: 28765864
J Am Dent Assoc. 2018 Jul;149(7):576-588.e6
pubmed: 29957185
J Biomed Inform. 2015 Dec;58 Suppl:S128-S132
pubmed: 26318122
J Periodontol. 2015 May;86(5):611-22
pubmed: 25688694
Sci Rep. 2019 Jun 11;9(1):8495
pubmed: 31186466
Stud Health Technol Inform. 2015;216:1081
pubmed: 26262380
Technol Health Care. 2021;29(6):1099-1108
pubmed: 33896855
J Dent. 2013 Dec;41(12):1148-63
pubmed: 23603087
Stud Health Technol Inform. 2017;245:313-317
pubmed: 29295106
J Periodontol. 2018 Jun;89 Suppl 1:S159-S172
pubmed: 29926952
EGEMS (Wash DC). 2017 Sep 04;5(1):14
pubmed: 29881734
J Am Med Inform Assoc. 2013 Jan 1;20(1):144-51
pubmed: 22733976
J Am Med Inform Assoc. 2019 Apr 1;26(4):364-379
pubmed: 30726935
Appl Clin Inform. 2020 Mar;11(2):305-314
pubmed: 32349142
J Biomed Inform. 2021 Apr;116:103712
pubmed: 33609761
BMC Oral Health. 2021 May 29;21(1):282
pubmed: 34051781
AMIA Annu Symp Proc. 2018 Dec 05;2018:1442-1450
pubmed: 30815189
J Intern Med. 2013 Dec;274(6):547-60
pubmed: 23952476
Methods Inf Med. 2018 Nov;57(5-06):253-260
pubmed: 30875704
BMC Med Inform Decis Mak. 2018 Dec 7;18(Suppl 5):118
pubmed: 30526596
J Clin Periodontol. 2017 Dec;44(12):1182-1191
pubmed: 28733997
Dent Clin North Am. 2005 Jul;49(3):517-32, v-vi
pubmed: 15978239
JMIR Med Inform. 2020 Dec 21;8(12):e23082
pubmed: 33346740
J Clin Periodontol. 2018 Jun;45 Suppl 20:S44-S67
pubmed: 29926492
Med Care Res Rev. 2010 Oct;67(5):503-27
pubmed: 20150441
BMC Med Inform Decis Mak. 2021 Jul 30;21(Suppl 2):90
pubmed: 34330244