Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study.
Adolescents
Algorithms
Children
Diabetes mellitus
Electronic health records
Epidemiology
Infants
Surveillance
Young adults
Journal
BMC medical research methodology
ISSN: 1471-2288
Titre abrégé: BMC Med Res Methodol
Pays: England
ID NLM: 100968545
Informations de publication
Date de publication:
10 10 2021
10 10 2021
Historique:
received:
13
04
2021
accepted:
07
09
2021
entrez:
11
10
2021
pubmed:
12
10
2021
medline:
3
11
2021
Statut:
epublish
Résumé
Disease surveillance of diabetes among youth has relied mainly upon manual chart review. However, increasingly available structured electronic health record (EHR) data have been shown to yield accurate determinations of diabetes status and type. Validated algorithms to determine date of diabetes diagnosis are lacking. The objective of this work is to validate two EHR-based algorithms to determine date of diagnosis of diabetes. A rule-based ICD-10 algorithm identified youth with diabetes from structured EHR data over the period of 2009 through 2017 within three children's hospitals that participate in the SEARCH for Diabetes in Youth Study: Cincinnati Children's Hospital, Cincinnati, OH, Seattle Children's Hospital, Seattle, WA, and Children's Hospital Colorado, Denver, CO. Previous research and a multidisciplinary team informed the creation of two algorithms based upon structured EHR data to determine date of diagnosis among diabetes cases. An ICD-code algorithm was defined by the year of occurrence of a second ICD-9 or ICD-10 diabetes code. A multiple-criteria algorithm consisted of the year of first occurrence of any of the following: diabetes-related ICD code, elevated glucose, elevated HbA1c, or diabetes medication. We assessed algorithm performance by percent agreement with a gold standard date of diagnosis determined by chart review. Among 3777 cases, both algorithms demonstrated high agreement with true diagnosis year and differed in classification (p = 0.006): 86.5% agreement for the ICD code algorithm and 85.9% agreement for the multiple-criteria algorithm. Agreement was high for both type 1 and type 2 cases for the ICD code algorithm. Performance improved over time. Year of occurrence of the second ICD diabetes-related code in the EHR yields an accurate diagnosis date within these pediatric hospital systems. This may lead to increased efficiency and sustainability of surveillance methods for incidence of diabetes among youth.
Sections du résumé
BACKGROUND
Disease surveillance of diabetes among youth has relied mainly upon manual chart review. However, increasingly available structured electronic health record (EHR) data have been shown to yield accurate determinations of diabetes status and type. Validated algorithms to determine date of diabetes diagnosis are lacking. The objective of this work is to validate two EHR-based algorithms to determine date of diagnosis of diabetes.
METHODS
A rule-based ICD-10 algorithm identified youth with diabetes from structured EHR data over the period of 2009 through 2017 within three children's hospitals that participate in the SEARCH for Diabetes in Youth Study: Cincinnati Children's Hospital, Cincinnati, OH, Seattle Children's Hospital, Seattle, WA, and Children's Hospital Colorado, Denver, CO. Previous research and a multidisciplinary team informed the creation of two algorithms based upon structured EHR data to determine date of diagnosis among diabetes cases. An ICD-code algorithm was defined by the year of occurrence of a second ICD-9 or ICD-10 diabetes code. A multiple-criteria algorithm consisted of the year of first occurrence of any of the following: diabetes-related ICD code, elevated glucose, elevated HbA1c, or diabetes medication. We assessed algorithm performance by percent agreement with a gold standard date of diagnosis determined by chart review.
RESULTS
Among 3777 cases, both algorithms demonstrated high agreement with true diagnosis year and differed in classification (p = 0.006): 86.5% agreement for the ICD code algorithm and 85.9% agreement for the multiple-criteria algorithm. Agreement was high for both type 1 and type 2 cases for the ICD code algorithm. Performance improved over time.
CONCLUSIONS
Year of occurrence of the second ICD diabetes-related code in the EHR yields an accurate diagnosis date within these pediatric hospital systems. This may lead to increased efficiency and sustainability of surveillance methods for incidence of diabetes among youth.
Identifiants
pubmed: 34629073
doi: 10.1186/s12874-021-01394-8
pii: 10.1186/s12874-021-01394-8
pmc: PMC8502379
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
210Subventions
Organisme : NIDDK NIH HHS
ID : R01 DK127208
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006131
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006138
Pays : United States
Organisme : NCCDPHP CDC HHS
ID : U18 DP006139
Pays : United States
Informations de copyright
© 2021. The Author(s).
Références
JAMA. 2007 Jun 27;297(24):2716-24
pubmed: 17595272
Am J Epidemiol. 2015 Jan 1;181(1):32-9
pubmed: 25515167
Pediatr Diabetes. 2014 Dec;15(8):573-84
pubmed: 24913103
N Engl J Med. 2017 Apr 13;376(15):1419-1429
pubmed: 28402773
Am J Epidemiol. 2014 Mar 15;179(6):749-58
pubmed: 24488511
BMC Med Inform Decis Mak. 2013 Aug 01;13:81
pubmed: 23915139
BMC Med Inform Decis Mak. 2020 Jan 8;20(1):6
pubmed: 31914992
JAMA. 2014 May 7;311(17):1778-86
pubmed: 24794371
Diabetes Care. 2014 Feb;37(2):402-8
pubmed: 24041677
Diabetes Care. 2014 Feb;37(2):565-8
pubmed: 24271190
Diabetes Care. 2016 Sep;39(9):1527-34
pubmed: 27519447
Mayo Clin Proc Innov Qual Outcomes. 2017 Apr 28;1(1):100-110
pubmed: 30225406
Am J Epidemiol. 2014 Jan 1;179(1):27-38
pubmed: 24100956
BMJ Open Diabetes Res Care. 2019 Feb 16;7(1):e000547
pubmed: 30899525
Am J Prev Med. 2012 Jun;42(6 Suppl 2):S154-62
pubmed: 22704432
Diabetes Care. 2020 Oct;43(10):2418-2425
pubmed: 32737140
Diabetes. 2014 Nov;63(11):3938-45
pubmed: 24898146