Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review.
BACKGROUND
Population segmentation permits the division of a heterogeneous population into relatively homogenous subgroups. This scoping review aims to summarize the clinical applications of data driven and expert driven population segmentation among Type 2 diabetes mellitus (T2DM) patients.


METHODS
The literature search was conducted in Medline®, Embase®, Scopus® and PsycInfo®. Articles which utilized expert-based or data-driven population segmentation methodologies for evaluation of outcomes among T2DM patients were included. Population segmentation variables were grouped into five domains (socio-demographic, diabetes related, non-diabetes medical related, psychiatric / psychological and health system related variables). A framework for PopulAtion Segmentation Study design for T2DM patients (PASS-T2DM) was proposed.


RESULTS
Of 155,124 articles screened, 148 articles were included. Expert driven population segmentation approach was most commonly used, of which judgemental splitting was the main strategy employed (n = 111, 75.0%). Cluster based analyses (n = 37, 25.0%) was the main data driven population segmentation strategies utilized. Socio-demographic (n = 66, 44.6%), diabetes related (n = 54, 36.5%) and non-diabetes medical related (n = 18, 12.2%) were the most used domains. Specifically, patients' race, age, Hba1c related parameters and depression / anxiety related variables were most frequently used. Health grouping/profiling (n = 71, 48%), assessment of diabetes related complications (n = 57, 38.5%) and non-diabetes metabolic derangements (n = 42, 28.4%) were the most frequent population segmentation objectives of the studies.


CONCLUSIONS
Population segmentation has a wide range of clinical applications for evaluating clinical outcomes among T2DM patients. More studies are required to identify the optimal set of population segmentation framework for T2DM patients.
['Seng|Jun Jie Benjamin|JJB|0000-0002-3039-3816', 'Monteiro|Amelia Yuting|AY|0000-0001-8764-9627', 'Kwan|Yu Heng|YH|0000-0001-7802-9696', 'Zainudin|Sueziani Binte|SB|0000-0003-1686-0358', 'Tan|Chuen Seng|CS|0000-0002-6513-2309', 'Thumboo|Julian|J|0000-0001-6712-5535', 'Low|Lian Leng|LL|0000-0003-4228-2862']
D003924:Diabetes Mellitus, Type 2 D006801:Humans
Population segmentation Scoping review Cluster analysis Data analysis Diabetes mellitus, type 2 Latent class analysis Outcome assessment, health care Patient outcome assessment