A Risk Stratification Approach to Allocating Diabetes Education and Support Services.
Diabetes self-management education and support
Population health management
Predictive modeling
Type 2 diabetes
Journal
Diabetes technology & therapeutics
ISSN: 1557-8593
Titre abrégé: Diabetes Technol Ther
Pays: United States
ID NLM: 100889084
Informations de publication
Date de publication:
01 2022
01 2022
Historique:
pubmed:
16
9
2021
medline:
1
4
2022
entrez:
15
9
2021
Statut:
ppublish
Résumé
The objective of this study was to describe a predictive modeling approach to risk stratify people with type 2 diabetes for diabetes self-management education and support (DSMES) services. With data from a large health system, a predictive model including age, glycated hemoglobin (HbA1c), and insulin use among other factors, was developed to assess risk of future high HbA1c. The model was retrospectively applied to a cohort of people who received DSMES over a 2-year period to assess the impact of DSMES on glycemia by risk strata. Of 6934 eligible people, 4014 (58%) were in the composite low-risk group and 2604 (38%) were in the composite high-risk group. Mean HbA1c change after DSMES was -0.38% in the low-risk group and -0.84% in the high-risk group. This analysis demonstrates the potential application of predictive modeling as one approach to target DSMES resources to people who will benefit most.
Identifiants
pubmed: 34524006
doi: 10.1089/dia.2021.0253
pmc: PMC8783623
doi:
Substances chimiques
Glycated Hemoglobin A
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
75-78Subventions
Organisme : NIDDK NIH HHS
ID : T32 DK007052
Pays : United States
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