Dataset Information

Computer simulation models of pre-diabetes populations: a systematic review protocol.

ABSTRACT:

Introduction

Diabetes is a major public health problem and prediabetes (intermediate hyperglycaemia) is associated with a high risk of developing diabetes. With evidence supporting the use of preventive interventions for prediabetes populations and the discovery of novel biomarkers stratifying the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. In diabetes and prediabetes, it is relevant to inform cost-effectiveness analysis using decision models due to their ability to forecast long-term health outcomes and costs beyond the time frame of clinical trials. To support good implementation and reimbursement decisions of interventions in these populations, models should be clinically credible, based on best available evidence, reproducible and validated against clinical data. Our aim is to identify recent studies on computer simulation models and model-based economic evaluations of populations of individuals with prediabetes, qualify them and discuss the knowledge gaps, challenges and opportunities that need to be addressed for future evaluations.

Methods and analysis

A systematic review will be conducted in MEDLINE, Embase, EconLit and National Health Service Economic Evaluation Database. We will extract peer-reviewed studies published between 2000 and 2016 that describe computer simulation models of the natural history of individuals with prediabetes and/or decision models to evaluate the impact of interventions, risk stratification and/or screening on these populations. Two reviewers will independently assess each study for inclusion. Data will be extracted using a predefined pro forma developed using best practice. Study quality will be assessed using a modelling checklist. A narrative synthesis of all studies will be presented, focussing on model structure, quality of models and input data, and validation status.

Ethics and dissemination

This systematic review is exempt from ethics approval because the work is carried out on published documents. The findings of the review will be disseminated in a related peer-reviewed journal and presented at conferences.

Reviewregistration number

CRD42016047228.

SUBMITTER: Leal J

PROVIDER: S-EPMC5640045 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Publications

Computer simulation models of pre-diabetes populations: a systematic review protocol.

Leal Jose J Khurshid Waqar W Pagano Eva E Feenstra Talitha T

BMJ open 20171005 10

<h4>Introduction</h4>Diabetes is a major public health problem and prediabetes (intermediate hyperglycaemia) is associated with a high risk of developing diabetes. With evidence supporting the use of preventive interventions for prediabetes populations and the discovery of novel biomarkers stratifying the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. In diabetes and prediabetes, it is relevant to inform cost-effectiveness analysis using decision ...[more]

PMID: 28982807

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Project description:BackgroundType 2 diabetes mellitus (T2DM), a highly prevalent chronic disease, puts a large burden on individual health and health care systems. Computer simulation models, used to evaluate the clinical and economic effectiveness of various interventions to handle T2DM, have become a well-established tool in diabetes research. Despite the broad consensus about the general importance of validation, especially external validation, as a crucial instrument of assessing and controlling for the quality of these models, there are no systematic reviews comparing such validation of diabetes models. As a result, the main objectives of this systematic review are to identify and appraise the different approaches used for the external validation of existing models covering the development and progression of T2DM.MethodsWe will perform adapted searches by applying respective search strategies to identify suitable studies from 14 electronic databases. Retrieved study records will be included or excluded based on predefined eligibility criteria as defined in this protocol. Among others, a publication filter will exclude studies published before 1995. We will run abstract and full text screenings and then extract data from all selected studies by filling in a predefined data extraction spreadsheet. We will undertake a descriptive, narrative synthesis of findings to address the study objectives. We will pay special attention to aspects of quality of these models in regard to the external validation based upon ISPOR and ADA recommendations as well as Mount Hood Challenge reports. All critical stages within the screening, data extraction and synthesis processes will be conducted by at least two authors. This protocol adheres to PRISMA and PRISMA-P standards.DiscussionThe proposed systematic review will provide a broad overview of the current practice in the external validation of models with respect to T2DM incidence and progression in humans built on simulation techniques.Systematic review registrationPROSPERO CRD42017069983 .

Project description:BackgroundTobacco control models are mathematical models predicting tobacco-related outcomes in defined populations. The policy simulation model is considered as a subcategory of tobacco control models simulating the potential outcomes of tobacco control policy options. However, we could not identify any existing tool specifically designed to assess the quality of tobacco control models.ObjectiveThe aims of this systematic methodology review are to: (1) identify best modeling practices, (2) highlight common pitfalls, and (3) develop recommendations to assess the quality of tobacco control policy simulation models. Crucially, these recommendations can empower model users to assess the quality of current and future modeling studies, potentially leading to better tobacco policy decision-making for the public. This protocol describes the planned systematic review stages, paper inclusion and exclusion criteria, data extraction, and analysis.MethodsTwo reviewers searched five databases (Embase, EconLit, PsycINFO, PubMed, and CINAHL Plus) to identify eligible studies published between July 2013 and August 2019. We included papers projecting tobacco-related outcomes with a focus on tobacco control policies in any population and setting. Eligible papers were independently screened by two reviewers. The data extraction form was designed and piloted to extract model structure, data sources, transparency, validation, and other qualities. We will use a narrative synthesis to present the results by summarizing model trends, analyzing model approaches, and reporting data input and result quality. We will propose recommendations to assess the quality of tobacco control policy simulation models using the findings from this review and related literature.ResultsData collection is in progress. Results are expected to be completed and submitted for publication by April 2021.ConclusionsThis systematic methodological review will summarize the best practices and pitfalls existing among tobacco control policy simulation models and present a recommendation list of a high-quality tobacco control simulation model. A more standardized and quality-assured tobacco control policy simulation model will benefit modelers, policymakers, and the public on both model building and decision making.Trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42020178146; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020178146.International registered report identifier (irrid)DERR1-10.2196/26854.

Project description:AimsWith evidence supporting the use of preventive interventions for prediabetes populations and the use of novel biomarkers to stratify the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. Our aim is to summarize and assess the quality and validity of decision models and model-based economic evaluations of populations with prediabetes, to evaluate their potential use for the assessment of novel prevention strategies and to discuss the knowledge gaps, challenges and opportunities.Materials and methodsWe searched Medline, Embase, EconLit and NHS EED between 2000 and 2018 for studies reporting computer simulation models of the natural history of individuals with prediabetes and/or we used decision models to evaluate the impact of treatment strategies on these populations. Data were extracted following PRISMA guidelines and assessed using modelling checklists. Two reviewers independently assessed 50% of the titles and abstracts to determine whether a full text review was needed. Of these, 10% was assessed by each reviewer to cross-reference the decision to proceed to full review. Using a standardized form and double extraction, each of four reviewers extracted 50% of the identified studies.ResultsA total of 29 published decision models that simulate prediabetes populations were identified. Studies showed large variations in the definition of prediabetes and model structure. The inclusion of complications in prediabetes (n = 8) and type 2 diabetes (n = 17) health states also varied. A minority of studies simulated annual changes in risk factors (glycaemia, HbA1c, blood pressure, BMI, lipids) as individuals progressed in the models (n = 7) and accounted for heterogeneity among individuals with prediabetes (n = 7).ConclusionsCurrent prediabetes decision models have considerable limitations in terms of their quality and validity and do not allow evaluation of stratified strategies using novel biomarkers, highlighting a clear need for more comprehensive prediabetes decision models.

Project description:Computer-based simulation (CBS) is an interactive pedagogical training method that has seen increased interest, especially in recent years. There is some evidence that CBS in pharmacy education is not as widely adopted compared to other healthcare disciplines. Pharmacy education literature to date has not specifically discussed the potential barriers which may cause this uptake challenge. In this systematic narrative review, we attempted to explore and discuss potential barriers that may impact the integration of CBS in pharmacy practice education and provide our suggestions to overcome them. We searched five major databases and used the AACODS checklist for grey literature assessment. We identified 42 studies and four grey literature reports, published between 1 January 2000 and 31 August 2022, which met the inclusion criteria. Then, the specific approach of Braun and Clarke for thematic analysis was followed. The majority of the included articles were from Europe, North America, and Australasia. Although none of the included articles had a specific focus on barriers to implementation, thematic analysis was used to extract and discuss several potential barriers, such as resistance to change, cost, time, usability of software, meeting accreditation standards, motivating and engaging students, faculty experience, and curriculum constraints. Ad- dressing academic, process, and cultural barriers can be considered the first step in providing guidance for future implementation research for CBS in pharmacy education. The analysis suggests that to effectively overcome any possible barriers to implementing CBS, different stakeholders must engage in careful planning, collaboration, and investment in resources and training. The review indicates that additional research is required to offer evidence-based approach and strategies to prevent overwhelming or disengaging users from either learning or teaching process. It also guides further research into exploring potential barriers in different institutional cultures and regions.

Dataset Information

Computer simulation models of pre-diabetes populations: a systematic review protocol.

Introduction

Methods and analysis

Ethics and dissemination

Reviewregistration number

Publications

Computer simulation models of pre-diabetes populations: a systematic review protocol.

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