TY - JOUR
T1 - Group-based trajectory analysis identifies varying diabetes-related cost trajectories among type 2 diabetes patients in Texas
T2 - an empirical study using commercial insurance
AU - Han, Gang
AU - Spencer, Matthew Scott
AU - Ahn, Sang Nam
AU - Smith, Matthew Lee
AU - Zhong, Lixian
AU - Andreyeva, Elena
AU - Carpenter, Keri
AU - Towne, Samuel D.
AU - Preston, Veronica Averhart
AU - Ory, Marcia G.
N1 - Funding Information:
We thank Blue Cross and Blue Shield of Texas for their support. We also thank Drs. Carrie Byington and Nancy Dickey for their leadership and support at the Texas A&M Health Science Center for this joint effort.
Funding Information:
This research was supported by a grant from Blue Cross and Blue Shield of Texas to establish the Texas A&M University Health Science Center Rural Health Moonshot Initiative. All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations.
Publisher Copyright:
© 2023, BioMed Central Ltd., part of Springer Nature.
PY - 2023/10/18
Y1 - 2023/10/18
N2 - Background: The trend of Type 2 diabetes-related costs over 4 years could be classified into different groups. Patient demographics, clinical factors (e.g., A1C, short- and long-term complications), and rurality could be associated with different trends of cost. Study objectives are to: (1) understand the trajectories of cost in different groups; (2) investigate the relationship between cost and key factors in each cost trajectory group; and (3) assess significant factors associated with different cost trajectories. Methods: Commercial claims data in Texas from 2016 to 2019 were provided by a large commercial insurer and were analyzed using group-based trajectory analysis, longitudinal analysis of cost, and logistic regression analyses of different trends of cost. Results: Five groups of distinct trends of Type 2 diabetes-related cost were identified. Close to 20% of patients had an increasing cost trend over the 4 years. High A1C values, diabetes complications, and other comorbidities were significantly associated with higher Type 2 diabetes costs and higher chances of increasing trend over time. Rurality was significantly associated with higher chances of increasing trend over time. Conclusions: Group-based trajectory analysis revealed distinct patient groups with increased cost and stable cost at low, medium, and high levels in the 4-year period. The significant associations found between the trend of cost and A1C, complications, and rurality have important policy and program implications for potentially improving health outcomes and constraining healthcare costs.
AB - Background: The trend of Type 2 diabetes-related costs over 4 years could be classified into different groups. Patient demographics, clinical factors (e.g., A1C, short- and long-term complications), and rurality could be associated with different trends of cost. Study objectives are to: (1) understand the trajectories of cost in different groups; (2) investigate the relationship between cost and key factors in each cost trajectory group; and (3) assess significant factors associated with different cost trajectories. Methods: Commercial claims data in Texas from 2016 to 2019 were provided by a large commercial insurer and were analyzed using group-based trajectory analysis, longitudinal analysis of cost, and logistic regression analyses of different trends of cost. Results: Five groups of distinct trends of Type 2 diabetes-related cost were identified. Close to 20% of patients had an increasing cost trend over the 4 years. High A1C values, diabetes complications, and other comorbidities were significantly associated with higher Type 2 diabetes costs and higher chances of increasing trend over time. Rurality was significantly associated with higher chances of increasing trend over time. Conclusions: Group-based trajectory analysis revealed distinct patient groups with increased cost and stable cost at low, medium, and high levels in the 4-year period. The significant associations found between the trend of cost and A1C, complications, and rurality have important policy and program implications for potentially improving health outcomes and constraining healthcare costs.
KW - Diabetes self-management education and support
KW - Group-based trajectory analysis
KW - Multivariable logistic regression models
KW - Type 2 Diabetes related cost
KW - Texas/epidemiology
KW - Diabetes Complications
KW - Humans
KW - Insurance
KW - Glycated Hemoglobin
KW - Diabetes Mellitus, Type 2
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U2 - 10.1186/s12913-023-10118-1
DO - 10.1186/s12913-023-10118-1
M3 - Article
C2 - 37853393
AN - SCOPUS:85174453238
SN - 1472-6963
VL - 23
SP - 1116
JO - BMC Health Services Research
JF - BMC Health Services Research
IS - 1
M1 - 1116
ER -