Using item response theory with health system data to identify latent groups of patients with multiple health conditions.
A critical step toward tailoring effective interventions for heterogeneous and medically complex patients is to identify clinically meaningful subgroups on the basis of their comorbid conditions. We applied Item Response Theory (IRT), a potentially useful tool to identify clinically meaningful subgr...
Main Authors: | Katherine M Prenovost, Stephan D Fihn, Matthew L Maciejewski, Karin Nelson, Sandeep Vijan, Ann-Marie Rosland |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2018-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC6261016?pdf=render |
Similar Items
-
Item response theory : an introduction to latent trait models to test and item
by: Talib, Rohaya, et al.
Published: (2018) -
Latent Variable Modelling and Item Response Theory Analyses in Marketing Research
by: Brzezińska Justyna
Published: (2016-12-01) -
Characteristics of younger women Veterans with service connected disabilities
by: Charles Maynard, et al.
Published: (2019-03-01) -
Identifying latent groupings in market data: a latent class approach
by: Khalid, Haniza
Published: (2014) -
Integrating social and behavioral determinants of health into patient care and population health at Veterans Health Administration: a conceptual framework and an assessment of available individual and population level data sources and evidence-based measurements
by: Elham Hatef, et al.
Published: (2019-07-01)