Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review
Abstract 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...
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| Format: | Article |
| Language: | English |
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BMC
2021-03-01
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| Series: | BMC Medical Research Methodology |
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| Online Access: | https://doi.org/10.1186/s12874-021-01209-w |
| _version_ | 1819180970381672448 |
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| author | Jun Jie Benjamin Seng Amelia Yuting Monteiro Yu Heng Kwan Sueziani Binte Zainudin Chuen Seng Tan Julian Thumboo Lian Leng Low |
| author_facet | Jun Jie Benjamin Seng Amelia Yuting Monteiro Yu Heng Kwan Sueziani Binte Zainudin Chuen Seng Tan Julian Thumboo Lian Leng Low |
| author_sort | Jun Jie Benjamin Seng |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-22T22:22:48Z |
| format | Article |
| id | doaj.art-86451a9ed5444e4aa474d330cd44424b |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-12-22T22:22:48Z |
| publishDate | 2021-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-86451a9ed5444e4aa474d330cd44424b2022-12-21T18:10:38ZengBMCBMC Medical Research Methodology1471-22882021-03-0121111910.1186/s12874-021-01209-wPopulation segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping reviewJun Jie Benjamin Seng0Amelia Yuting Monteiro1Yu Heng Kwan2Sueziani Binte Zainudin3Chuen Seng Tan4Julian Thumboo5Lian Leng Low6Duke-NUS Medical SchoolDuke-NUS Medical SchoolSingHealth Regional Health System PULSES Centre, Singapore Health ServicesDepartment of General Medicine (Endocrinology), Sengkang General HospitalSaw Swee Hock School of Public Health, National University of Singapore and National University Health SystemSingHealth Regional Health System PULSES Centre, Singapore Health ServicesSingHealth Regional Health System PULSES Centre, Singapore Health ServicesAbstract 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.https://doi.org/10.1186/s12874-021-01209-wDiabetes mellitus, type 2Cluster analysisLatent class analysisPopulation segmentationData analysisPatient outcome assessment |
| spellingShingle | Jun Jie Benjamin Seng Amelia Yuting Monteiro Yu Heng Kwan Sueziani Binte Zainudin Chuen Seng Tan Julian Thumboo Lian Leng Low Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review BMC Medical Research Methodology Diabetes mellitus, type 2 Cluster analysis Latent class analysis Population segmentation Data analysis Patient outcome assessment |
| title | Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review |
| title_full | Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review |
| title_fullStr | Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review |
| title_full_unstemmed | Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review |
| title_short | Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review |
| title_sort | population segmentation of type 2 diabetes mellitus patients and its clinical applications a scoping review |
| topic | Diabetes mellitus, type 2 Cluster analysis Latent class analysis Population segmentation Data analysis Patient outcome assessment |
| url | https://doi.org/10.1186/s12874-021-01209-w |
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