The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR): Unique 1.4 M patient Electronic Health Record cohort.
Big data
Chronic disease
Diabetes mellitus
Electronic health records
Epidemiologic methods
Epidemiologic research design
Public health informatics
Public health practice
Journal
Healthcare (Amsterdam, Netherlands)
ISSN: 2213-0772
Titre abrégé: Healthc (Amst)
Pays: Netherlands
ID NLM: 101622189
Informations de publication
Date de publication:
Dec 2020
Dec 2020
Historique:
received:
02
12
2019
revised:
17
06
2020
accepted:
27
07
2020
pubmed:
5
10
2020
medline:
30
6
2021
entrez:
4
10
2020
Statut:
ppublish
Résumé
The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) study uses a novel Electronic Health Record (EHR) data approach as a tool to assess the epidemiology of known and new risk factors for type 2 diabetes mellitus (T2DM) and study how prevention interventions affect progression to and onset of T2DM. We created an electronic cohort of 1.4 million patients having had at least 4 encounters with a healthcare organization for at least 24-months; were aged ≥18 years in 2010; and had no diabetes (i.e., T1DM or T2DM) at cohort entry or in the 12 months following entry. EHR data came from patients at nine healthcare organizations across the U.S. between January 1, 2010-December 31, 2016. Approximately 5.9% of the LEADR cohort (82,922 patients) developed T2DM, providing opportunities to explore longitudinal clinical care, medication use, risk factor trajectories, and diagnoses for these patients, compared with patients similarly matched prior to disease onset. LEADR represents one of the largest EHR databases to have repurposed EHR data to examine patients' T2DM risk. This paper is first in a series demonstrating this novel approach to studying T2DM. Chronic conditions that often take years to develop can be studied efficiently using EHR data in a retrospective design. While much is already known about T2DM risk, this EHR's cohort's 160 M data points for 1.4 M people over six years, provides opportunities to investigate new unique risk factors and evaluate research hypotheses where results could modify public health practice for preventing T2DM.
Sections du résumé
BACKGROUND
BACKGROUND
The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) study uses a novel Electronic Health Record (EHR) data approach as a tool to assess the epidemiology of known and new risk factors for type 2 diabetes mellitus (T2DM) and study how prevention interventions affect progression to and onset of T2DM. We created an electronic cohort of 1.4 million patients having had at least 4 encounters with a healthcare organization for at least 24-months; were aged ≥18 years in 2010; and had no diabetes (i.e., T1DM or T2DM) at cohort entry or in the 12 months following entry. EHR data came from patients at nine healthcare organizations across the U.S. between January 1, 2010-December 31, 2016.
RESULTS
RESULTS
Approximately 5.9% of the LEADR cohort (82,922 patients) developed T2DM, providing opportunities to explore longitudinal clinical care, medication use, risk factor trajectories, and diagnoses for these patients, compared with patients similarly matched prior to disease onset.
CONCLUSIONS
CONCLUSIONS
LEADR represents one of the largest EHR databases to have repurposed EHR data to examine patients' T2DM risk. This paper is first in a series demonstrating this novel approach to studying T2DM.
IMPLICATIONS
CONCLUSIONS
Chronic conditions that often take years to develop can be studied efficiently using EHR data in a retrospective design.
LEVEL OF EVIDENCE
METHODS
While much is already known about T2DM risk, this EHR's cohort's 160 M data points for 1.4 M people over six years, provides opportunities to investigate new unique risk factors and evaluate research hypotheses where results could modify public health practice for preventing T2DM.
Identifiants
pubmed: 33011645
pii: S2213-0764(20)30057-9
doi: 10.1016/j.hjdsi.2020.100458
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
100458Informations de copyright
Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.