Publications (Modelling Methods)

Role of visual analytics in supporting mental healthcare systems research and policy: A systematic scoping review

By Admin in RESOURCES FOR MODELLERS, RESOURCES FOR PLANNERS, PUBLICATIONS (MODELLING METHODS)

May 10, 2019

Peer reviewed: Yes Authors: Chung, Younjin and Bagheri, Nasser and Salinas-Perez, Jose Alberto and Smurthwaite, Kayla and Walsh, Erin and Furst, MaryAnne and Rosenberg, Sebastian and Salvador-Carulla, Luis Publication: International Journal of Information Management. Year: 2020 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.04.012 Method: Scoping review. Message: Visual analytics is needed for mental healthcare systems research and policy. BibTeX: @article{ChungYRole2020U, title={Role of visual analytics in supporting mental healthcare systems research and policy: A systematic scoping review}, author={Chung, Younjin and Bagheri, Nasser and Salinas-Perez, Jose Alberto and Smurthwaite, Kayla and Walsh, Erin and Furst, MaryAnne and Rosenberg, Sebastian and Salvador-Carulla, Luis}, journal={International Journal of Information Management}, volume={50}, pages={}, year={2020}, publisher={Elsevier BV}}

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A decision support system for assessing management interventions in a mental health ecosystem: The case of Bizkaia (Basque Country, Spain)

By Admin in RESOURCES FOR MODELLERS, PUBLICATIONS (MODELLING METHODS)

February 14, 2019

Peer reviewed: Yes Authors: García-Alonso, Carlos R. and Almeda, Nerea and Salinas-Pérez, José A. and Gutiérrez-Colosía, Mencía R. and Uriarte-Uriarte, José J. and Salvador-Carulla, Luis Publication: PLOS ONE. Year: 2019 DOI: https://doi.org/10.1371/journal.pone.0212179 Method: A Monte-Carlo simulation combined with a fuzzy inference engine was used to examine the Relative Technical Efficiency (RTE) of three proposed intervention scenarios. Message: Decision makers can use information from this approach to design new interventions and policies.

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Causal modelling for supporting planning and management of mental health services and systems: a systematic review

By Admin in Publications (Modelling Methods), Resources for Modellers, Resources for Planners

January 25, 2019

Peer reviewed: Yes. Authors: Almeda, Nerea and García-Alonso, Carlos R and Salinas-Pérez, José A and Gutiérrez-Colosía, Mencía R and Salvador-Carulla, Luis. Publication: International Journal of Environmental Research and Public Health. Year: 2019 DOI: https://doi.org/10.3390/ijerph16030332 Method: A systematic review the use of causal modelling (a tool for decision-making based on identifying critical variables and their causal relationships) in mental health services and systems. Message: The papers included in the review showed very different objectives and subjects of study.

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Regional planning for meaningful person-centred care in mental health: context is the signal not the noise

By Admin in Publications (Modelling Methods), Resources for Modellers, Resources for Planners

December 1, 2017

Peer reviewed: Yes. Authors: Rock, D and Cross, SP Publication: Epidemiology and Psychiatric Sciences Year: 2020 DOI: doi:10.1017/S2045796020000153 Method: Editorial. Message: To ensure planned and provided care is most appropriate to more than merely the ‘average’ person requires a combination of (1) relevant, local and sophisticated data planning, collection and analysis systems, (2) more detailed person-centred service planning and delivery and (3) system accountability through co-design and transparent public reporting of health system performance in a manner that is understandable, relevant, and locally applicable.

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Simulation modelling in mental health: A systematic review

By Admin in Publications (Modelling Methods), Resources for Modellers, Resources for Planners

December 1, 2017

Peer reviewed: Yes Authors: Long, Katrina M and Meadows, Graham N Publication: Journal of Simulation Year: 2018 DOI: https://doi.org/10.1057/s41273-017-0062-0 Method: A systematic review the use of simulation modelling in mental healthcare. Message: There were widespread and innovative applications of simulation in the areas of medical decision making and epidemiology, with health system planning and optimisation relatively underrepresented. Markov modelling was the preferred method across area and illness. However, the literature is currently undermined by a lack of coherence and evidence of implementation, and there is an ongoing issue of accessing unpublished models from healthcare and government organisations.

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A modelling tool for policy analysis to support the design of efficient and effective policy responses for complex public health problems

By Admin in RESOURCES FOR MODELLERS, RESOURCES FOR PLANNERS, PUBLICATIONS (MENTAL HEALTH POLICY), PUBLICATIONS (MODELLING METHODS)

March 2, 2015

Peer reviewed: Yes Authors: Atkinson, Jo-An and Page, Andrew and Wells, Robert and Milat, Andrew and Wilson, Andrew Publication: Implementation Science. Year: 2015 DOI: https://doi.org/10.1186/s13012-015-0221-5 Method: Commentary. Message: There is a strong case for inclusion of systems modelling in the analytic tool kit for identifying targeted investments likely to deliver efficient, effective & equitable impacts. BibTeX: @article{AtkinsonJA2015S, title={A modelling tool for policy analysis to support the design of efficient and effective policy responses for complex public health problems}, author={Atkinson, Jo-An and Page, Andrew and Wells, Robert and Milat, Andrew and Wilson, Andrew}, journal={Implementation Science}, volume={10}, pages={26}, year={2015}, publisher={Springer Science and Business Media LLC}}

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Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

By Admin in Publications (Modelling Methods), Resources for Modellers

September 30, 2010

Peer reviewed: Yes Authors: Gibert, Karina and García-Alonso, Carlos and Salvador-Carulla, Luis Publication: Health research policy and systems Year: 2010 DOI: https://doi.org/10.1186/1478-4505-8-28 Method: Descriptive introduction of a new hybrid methodology Expert-based Cooperative Analysis (EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge to improve decision support in healthcare systems. EbCA was compared to classical procedures using qualitative explicit prior knowledge in two case examples: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR).

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