Core Discrete Event Simulation Model for the Evaluation of Health Care Technologies in Major Depressive Disorder

Vataire, Anne-Lise; Aballéa, Samuel; Antoñanzas, Fernando; Roijen, Leona Hakkaart-van; Lam, Raymond W.; McCrone, Paul; Persson, Ulf; Toumi, Mondher

doi:10.1016/j.jval.2013.11.012

Cited by 13 publications

(43 citation statements)

References 22 publications

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“…There are also other reasons for DES being chosen in preference to other alternatives, such as less limitations on the number of events and health states to be represented [61, 62], higher flexibility, less computing intensity [63], and event-based conceptualization attribute [55]. Taken together, DES models are increasingly considered as a more practical and flexible modeling technique in case of complex and dynamic contexts in health care.…”

Section: Discussionmentioning

confidence: 99%

Application of discrete event simulation in health care: a systematic review

Zhang

2018

BMC Health Serv Res

181

132

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BackgroundThe objective was to explore the current advances and extent of DES (Discrete Event Simulation) applied to assisting with health decision making, as well as to categorize the wide spectrum of health-related topics where DES was applied.MethodsA systematic review was conducted of the literature published over the last two decades. Original research articles were included and reviewed if they concentrated on the topic of DES technique applied to health care management with model frameworks explicitly demonstrated. No restriction regarding the settings of DES application was applied.ResultsA total of 211 papers met the predefined inclusion criteria. The number of publications included increased significantly especially after 2010.101 papers (48%) stated explicitly disease areas targeted, the most frequently modeled of which are related to circulatory system, nervous system and Neoplasm. The DES applications were distributed unevenly into 4 major classes: health and care systems operation (HCSO) (65%), disease progression modeling (DPM) (28%), screening modeling (SM) (5%) and health behavior modeling (HBM) (2%). More than 68% of HCSO by DES were focused on specific problems in individual units. However, more attempts at modeling highly integrated health service systems as well as some new trends were identified.ConclusionsDES technique has been an effective tool to approach a wide variety of health care issues. Among all DES applications in health care, health system operations research occupied the most considerable proportion and increased most significantly. Health Economic Evaluation (HEE) was the second most common topic for DES in health care, but with stable rather than increasing numbers of publications.

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Section: Discussionmentioning

confidence: 99%

Application of discrete event simulation in health care: a systematic review

Zhang

2018

BMC Health Serv Res

181

132

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“…There are some published DES models relevant to depression, but none has included another condition. [211][212][213][214][215] The characteristics of depression alone, and particularly the characteristics of depression alongside another condition, make DES the ideal modelling approach to address the stated research question.…”

Section: Modelling Approachmentioning

confidence: 99%

“…Consequently Ali Afzali et al 218 proposed to use a DES model with a lifetime horizon, which is in keeping with a growing body of model developers using discrete event models for cost-effectiveness modelling in depression. [212][213][214][215] Key attributes that were identified as being attractive for using a DES model for depression and CHD were the ability to:…”

Section: Quantifying the Impact Of Multimorbidity In A Model-based Comentioning

confidence: 99%

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Better guidelines for better care: accounting for multimorbidity in clinical guidelines – structured examination of exemplar guidelines and health economic modelling

Guthrie

Thompson

Dumbreck

et al. 2017

Health Serv Deliv Res

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Health Services and Delivery ResearchISSN 2050-4349 (Print) ISSN 2050-4357 (Online) This journal is a member of and subscribes to the principles of the Committee on Publication Ethics (COPE) (www.publicationethics.org/).Editorial contact: journals.library@nihr.ac.ukThe full HS&DR archive is freely available to view online at www.journalslibrary.nihr.ac.uk/hsdr. Print-on-demand copies can be purchased from the report pages of the NIHR Journals Library website: www.journalslibrary.nihr.ac.uk Criteria for inclusion in the Health Services and Delivery Research journalReports are published in Health Services and Delivery Research (HS&DR) if (1) they have resulted from work for the HS&DR programme or programmes which preceded the HS&DR programme, and (2) they are of a sufficiently high scientific quality as assessed by the reviewers and editors. HS&DR programmeThe Health Services and Delivery Research (HS&DR) programme, part of the National Institute for Health Research (NIHR), was established to fund a broad range of research. It combines the strengths and contributions of two previous NIHR research programmes: the Health Services Research (HSR) programme and the Service Delivery and Organisation (SDO) programme, which were merged in January 2012.The HS&DR programme aims to produce rigorous and relevant evidence on the quality, access and organisation of health services including costs and outcomes, as well as research on implementation. The programme will enhance the strategic focus on research that matters to the NHS and is keen to support ambitious evaluative research to improve health services.For more information about the HS&DR programme please visit the website: http://www.nets.nihr.ac.uk/programmes/hsdr This reportThe research reported in this issue of the journal was funded by the HS&DR programme or one of its preceding programmes as project number 11/2003/27. The contractual start date was in October 2012. The final report began editorial review in July 2015 and was accepted for publication in November 2015. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HS&DR editors and production house have tried to ensure the accuracy of the authors' report and would like to thank the reviewers for their constructive comments on the final report document. However, they do not accept liability for damages or losses arising from material published in this report.This report presents independent research funded by the National Institute for Health Research (NIHR). The views and opinions expressed by authors in this publication are those of the authors and do not necessarily reflect those of the NHS, the NIHR, NETSCC, the HS&DR programme or the Department of Health. If there are verbatim quotations included in this publication the views and opinions expressed by the interviewees are those of the interviewees and do not necessarily reflect those of the authors, those of the NHS, the NIHR, NETSCC, the HS&DR programme or the Department of Hea...

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“…The majority of the 53 economic evaluations were carried out in the Netherlands (28%) [ 29 , 30 , 38 , 41 – 43 , 49 , 51 , 54 , 57 , 67 , 71 – 73 , 76 ] and the United Kingdom (26%) [ 28 , 33 , 35 , 36 , 44 , 46 , 47 , 50 , 52 , 60 – 62 , 75 , 78 ]. Five studies derive from Spain [ 27 , 39 , 63 , 64 , 66 ] and four respectively from the United States [ 45 , 48 , 68 , 69 ] and Germany [ 31 , 32 , 37 , 40 ].…”

Section: Resultsmentioning

confidence: 99%

Considering the societal perspective in economic evaluations: a systematic review in the case of depression

et al. 2020

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Background Depressive disorders are associated with a high burden of disease. However, due to the burden posed by the disease on not only the sufferers, but also on their relatives, there is an ongoing debate about which costs to include and, hence, which perspective should be applied. Therefore, the aim of this paper was to examine whether the change between healthcare payer and societal perspective leads to different conclusions of cost-utility analyses in the case of depression. Methods A systematic literature search was conducted to identify economic evaluations of interventions in depression, launched on Medline and the Cost-Effectiveness Registry of the Tufts University using a ten-year time horizon (2008–2018). In a two-stepped screening process, cost-utility studies were selected by means of specified inclusion and exclusion criteria. Subsequently, relevant findings was extracted and, if not fully stated, calculated by the authors of this work. Results Overall, 53 articles with 92 complete economic evaluations, reporting costs from healthcare payer/provider and societal perspective, were identified. More precisely, 22 estimations (24%) changed their results regarding the cost-effectiveness quadrant when the societal perspective was included. Furthermore, 5% of the ICURs resulted in cost-effectiveness regarding the chosen threshold (2% of them became dominant) when societal costs were included. However, another four estimations (4%) showed the opposite result: these interventions were no longer cost-effective after the inclusion of societal costs. Conclusions Summarising the disparities in results and applied methods, the results show that societal costs might alter the conclusions in cost-utility analyses. Hence, the relevance of the perspectives chosen should be taken into account when carrying out an economic evaluation. This systematic review demonstrates that the results of economic evaluations can be affected by different methods available for estimating non-healthcare costs.

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Core Discrete Event Simulation Model for the Evaluation of Health Care Technologies in Major Depressive Disorder

Abstract: The discrete event simulation model can provide a more comprehensive evaluation of different therapeutic options in MDD, compared with existing Markov models, and can be used to compare a wide range of health care technologies in various groups of patients with MDD.

Cited by 13 publications

References 22 publications

Application of discrete event simulation in health care: a systematic review

Application of discrete event simulation in health care: a systematic review

Better guidelines for better care: accounting for multimorbidity in clinical guidelines – structured examination of exemplar guidelines and health economic modelling

Considering the societal perspective in economic evaluations: a systematic review in the case of depression

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