Dataset Information

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.

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.

SUBMITTER: Seng JJB

PROVIDER: S-EPMC7953703 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review.

Seng Jun Jie Benjamin JJB Monteiro Amelia Yuting AY Kwan Yu Heng YH Zainudin Sueziani Binte SB Tan Chuen Seng CS Thumboo Julian J Low Lian Leng LL

BMC medical research methodology 20210311 1

<h4>Background</h4>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.<h4>Methods</h4>The literature search was conducted in Medline®, Embase®, Scopus® and PsycInfo®. Articles which utilized expert-based or data-driven population segmentation methodologies for evaluatio ...[more]

PMID: 33706717

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Project description:BACKGROUND:The prevalence of type-2 diabetes mellitus (T2DM) has been increasing globally. Without proper management, T2DM can develop into serious complications and even death. Diet modification is one of the most effective tools in managing T2DM at the early stage, but it requires knowledge and compliance from the patients. Thus, meal replacement (MR) has gained its popularity as a tool for diet modification to improve glycemic control and also reducing weight in T2DM patients. There are several existing meal replacement studies but not much is known on the general scope and effect of these existing MRs. Hence, this review is aimed to provide an overview of the existing evidences regarding the application of meal replacement on T2DM patients and identify the gaps or limitations in the studies. METHODOLOGY:The scoping review will be carried out in six stages: (1) identifying the research question, (2) identifying relevant studies through electronic databases (i.e., PubMed, Scopus, Cochrane Reviews, Google Scholar, EBSCOHOST, Science Direct) and also gray literature, and (3) selection of studies to be included based on inclusion criteria. Search and initial screening of studies to be included will be conducted by two independent reviewers. Discrepancies will then be solved through discussion with other reviewers; (4) charting and categorizing extracted data in a pretested data extraction form; (5) collating, summarizing, and reporting the results; and lastly, (6) conducting consultation with stakeholders and experts in diabetes. DISCUSSION:This scoping review protocol is aimed to provide a framework enabling us to map and summarize the findings from existing studies involving meal replacement. It will help researchers to identify the research gap and provide recommendations for future meal replacement studies. The results from this scoping review will be useful to various stakeholders in healthcare. It is also part of a research project in which the information obtained will be utilized in a clinical trial of a developed meal replacement plan. Dissemination of knowledge will also be done through presentations at related scientific conferences.

Project description:BackgroundAccording to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited.ObjectiveThe objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM.MethodsA scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA1c).ResultsIn total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of -0.54% (95% CI -0.8 to -0.28) for T2DM and -0.63% (95% CI -0.93 to -0.32) for T1DM.ConclusionsDM-specific mHealth apps improved the glycemic control by significantly reducing HbA1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail.

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Dataset Information

Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review.

Background

Methods

Results

Conclusions

Publications

Population segmentation of type 2 diabetes mellitus patients and its clinical applications - a scoping review.

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