Application of Discrete-Event Simulation in Health Technology Assessment: A Cost-Effectiveness Analysis of Alzheimer’s Disease Treatment Using Real-World Evidence in Thailand

Kongpakwattana, Khachen; Chaiyakunapruk, Nathorn

doi:10.1016/j.jval.2020.01.010

Cited by 8 publications

(12 citation statements)

References 26 publications

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“…Eight studies (35%) were conducted in Europe [ 31 , 37 , 42 , 45 , 47 , 49 – 51 ], eight (35%) were conducted in the US [ 32 – 34 , 36 , 39 – 41 , 48 ], and two (9%) were conducted in Canada [ 44 , 46 ]. Additionally, single studies (4% each) were conducted in Australia [ 52 ], Brazil [ 30 ], South Korea [ 43 ], Taiwan [ 38 ], and Thailand [ 35 ].…”

Section: Resultsmentioning

confidence: 99%

“…In most of the included studies, analyses were performed using TreeAge [ 30 , 31 , 35 , 40 , 43 , 48 , 49 ] and Microsoft Excel [ 34 , 36 , 47 , 50 , 51 ] each with six studies (52%, in total). For a CBA conducted through decision tree modelling, a combination of Stata Standard Edition (SE) version v16 and TreeAge Pro 2019 software was used in the study [ 46 ].…”

Section: Resultsmentioning

confidence: 99%

“…The time horizon of analysis ranged from 3 months ( n = 1, 4%) [ 42 ] for a diagnostic option, to lifetime as the most common approach, with 13 studies (57%) [Table 3 ]. Four studies applied time horizons of 10 and 24 years [ 30 , 35 , 38 , 48 ], which can be considered equivalent to a lifetime horizon, given that dementia is typically diagnosed in older adults with a shorter life expectancy. The time horizon in four other studies varied between 1 year and 5 years [ 37 , 45 , 46 , 51 ] and one study did not detail the time horizon employed [ 47 ].…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Model-Based Economic Evaluations of Interventions for Dementia: An Updated Systematic Review and Quality Assessment

Darab,

Engel,

Henzler

et al. 2024

Appl Health Econ Health Policy

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Background There has been an increase in model-based economic evaluations of interventions for dementia. The most recent systematic review of economic evaluations for dementia highlighted weaknesses in studies, including lack of justification for model assumptions and data inputs. Objective This study aimed to update the last published systematic review of model-based economic evaluations of interventions for dementia, including Alzheimer’s disease, with a focus on any methodological improvements and quality assessment of the studies. Methods Systematic searches in eight databases, including PubMed, Cochrane, Embase, CINAHL, PsycINFO, EconLit, international HTA database, and the Tufts Cost-Effectiveness Analysis Registry were undertaken from February 2018 until August 2022. The quality of the included studies was assessed using the Philips checklist and the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklist. The findings were summarized through narrative analysis. Results This review included 23 studies, comprising cost-utility analyses (87%), cost-benefit analyses (9%) and cost-effectiveness analyses (4%). The studies covered various interventions, including pharmacological ( n = 10, 43%), non-pharmacological ( n = 4, 17%), prevention ( n = 4, 17%), diagnostic ( n = 4, 17%) and integrated ( n = 1, 4%) [diagnostics-pharmacologic] strategies. Markov transition models were commonly employed (65%), followed by decision trees (13%) and discrete-event simulation (9%). Several interventions from all categories were reported as being cost effective. The quality of reporting was suboptimal for the Methods and Results sections in almost all studies, although the majority of studies adequately addressed the decision problem, scope, and model-type selection in their economic evaluations. Regarding the quality of methodology, only a minority of studies addressed competing theories or clearly explained the rationale for model structure. Furthermore, few studies systematically identified key parameters or assessed data quality, and uncertainty was mostly addressed partially. Conclusions This review informs future research and resource allocation by providing insights into model-based economic evaluations for dementia interventions and highlighting areas for improvement. Supplementary Information The online version contains supplementary material available at 10.1007/s40258-024-00878-0.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Model-Based Economic Evaluations of Interventions for Dementia: An Updated Systematic Review and Quality Assessment

Darab,

Engel,

Henzler

et al. 2024

Appl Health Econ Health Policy

View full text Add to dashboard Cite

show abstract

“…AD-ACE model applications (22, 34, 41) showed higher lecanemab treatment value with higher discontinuation rates, with maintained reduced amyloid level after stopping treatment and with lower dosing frequency while assuming no treatment effect waning, and lower lecanemab treatment value with shorter maximum treatment duration. Kongpakwattana et al (42) showed a higher cost-effectiveness ratio with earlier stopping donepezil at severe dementia. Ross et al (15) showed a higher cost-effectiveness ratio with later discontinuation at severe instead of moderate dementia.…”

Section: Discussionmentioning

confidence: 99%

New IPECAD open-source model framework for the health technology assessment of early Alzheimer’s disease treatment: development and use cases

Handels,

Herring,

Grimm

et al. 2024

Preprint

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Objectives: Market access and reimbursement decisions for new Alzheimer's disease (AD) treatments are informed by economic evaluations. An open-source model with intuitive structure for model cross-validation can support the transparency and credibility of such evaluations. We describe the new IPECAD open-source model framework (version 2) for the health-economic evaluation of early AD treatment and use it for cross-validation and addressing uncertainty. Methods: A cohort state transition model using a categorized composite domain (cognition and function) was developed by replicating an existing reference model and testing it for internal validity. Then, features of existing "ICER" and "AD-ACE" models assessing lecanemab treatment were implemented for model cross-validation. Additional uncertainty scenarios were performed on choice of efficacy outcome from trial, natural disease progression, treatment effect waning and stopping rules, and other methodological choices. The model is available open-source as R code, spreadsheet and web-based version via https://github.com/ronhandels/IPECAD. Results: In the IPECAD model incremental life years, QALY gains and cost savings were 21-31% smaller compared to the ICER model and 36-56% smaller compared to the AD-ACE model. IPECAD model results were particularly sensitive to assumptions on treatment effect waning and stopping rules and choice of efficacy outcome from trial. Conclusions: We demonstrated the ability of a new IPECAD opens-source model framework for researchers and decision-makers to cross-validate other (HTA submission) models and perform additional uncertainty analyses, setting an example for open science in AD decision modeling and supporting important reimbursement decisions.

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“…Applications of simulation in healthcare vary in scope, including material flow planning in hospitals [24], COVID-19 RT-PCR testing processes [25], patient scheduling [26], patient registration processing [27], using virtual reality [28], and assessing health technology [29]. On the other hand, lean, SS, and LSS interventions (LSS) have also been implemented with different approaches and goals, e.g., redesigning a supply chain for an operating room [30], improving the discharge process [31], redesigning the scheduling process for elective surgery [32], enhancing the patient flow in emergency department (ED) [33], or improving controlled drug processes [34].…”

Section: Introductionmentioning

confidence: 99%

Lean, Six Sigma, and Simulation: Evidence from Healthcare Interventions

et al. 2022

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In the Industry 4.0 era, healthcare services have experienced more dual interventions that integrate lean and six sigma with simulation modeling. This systematic review, which focuses on evidence-based practice and complies with the PRISMA guidelines, aims to evaluate the effects of these dual interventions on healthcare services and provide insights into which paradigms and tools produce the best results. Our review identified 4018 studies, of which 39 studies met the inclusion criteria and were selected. The predominantly positive results reported in 73 outcomes were mostly related to patient flow: length of stay, waiting time, and turnaround time. In contrast, there is little reported evidence of the impact on patient health and satisfaction, staff wellbeing, resource use, and savings. Discrete event simulation stands out in 74% of the interventions as the main simulation paradigm. Meanwhile, 66% of the interventions utilized lean, followed by lean-six sigma with 28%. Our findings confirm that dual interventions focus mainly on utilization and access to healthcare services, particularly on either patient flow problems or problems concerning the allocation of resources; however, most interventions lack evidence of implementation. Therefore, this study promotes further research and encourages practical applications including the use of Industry 4.0 technologies.

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Application of Discrete-Event Simulation in Health Technology Assessment: A Cost-Effectiveness Analysis of Alzheimer’s Disease Treatment Using Real-World Evidence in Thailand

Cited by 8 publications

References 26 publications

Model-Based Economic Evaluations of Interventions for Dementia: An Updated Systematic Review and Quality Assessment

Model-Based Economic Evaluations of Interventions for Dementia: An Updated Systematic Review and Quality Assessment

New IPECAD open-source model framework for the health technology assessment of early Alzheimer’s disease treatment: development and use cases

Lean, Six Sigma, and Simulation: Evidence from Healthcare Interventions

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