Simulation Modelling for Mental Health Services

About Simulation Modelling for Mental Health Services

Background

Mental health services managers must take into account multiple factors when making decisions about the most effective way to deliver care to clients. Currently, however, evidence to support decision-makers in choosing from a range of proposed mental health service configurations is commonly lacking. The increasing availability of epidemiological and service use data for mental illness and advanced modelling technology has made feasible the exploration of possible changes in the service system in a constructed simulation before resources are committed to the changes.

While simulation methods are widely used in epidemiology in policy research related to cardiovascular disease, public health preparedness and epidemic modelling, to date the application of simulation modelling in mental health care has been very limited. The work has been restricted to models depicting operational processes within individual components of mental health care systems, such as institutions or clinical services.

The focus of this research is the development of modelling tools aiming to assist mental health services managers and policymakers in their work. The models aim to be tailored to desired scenarios from managers and policy makers and allow scenarios regarding the delivery of mental health services to be simulated, enabling predictions to be made about the cost and quality of care of these services and allowing policy alternatives to be explored safely and inexpensively.

A critical aspect of the work is the examination of the impact of the project on health services management involved.  Reviewers in the ARC funding process requested we put more emphasis on this aspect of the project and we followed through on that. Especially important here has been the work of Katrina Long as a PhD student working with the project. As her systematic review has established, implementation and impact assessments of models in mental health care are very limited in number and typically in scope. This work will advance knowledge and understanding of how various modelling techniques may interact in their application with the real world of mental health care management.

Project team and partnerships

This work has received funding from Monash University, Monash Health, and the Australian Research Council. Partnerships through time have involved Deakin University and the University of Calgary; more recently including collaborations with staff from the University of Western Sydney, the Australian Prevention Partnership Centre, and The Sax Institute also based in Sydney.

Mental Health Services:Prof. Graham Meadows (Project Leader), Mr Peter Gibbs
Health Economics:Prof. Brett Inder
Modelling Technologies:Prof. Scott Patten, Dr Lee Gordon-Brown, Dr Mehmet Ozmen, Dr Ante Prodan, Dr Jo-An Atkinson
Information Technology:Dr Joarder Kamruzzaman, Dr Gour Karmakar
Social Work:      A/Prof. Fiona McDermott
Organisational Psychology:Dr Simon Albrecht, Ms Katrina Long
Project Management:Dr Joanne Brooker
Industry Engagement: Dr John Morrison

Funding support to the research program

  • 2010-11. Monash Faculty of Medicine, Nursing and Health Sciences, strategic grant. $48,125.
  • ARC linkage 2011-2014. ARC contribution $184,000 with further support from Partners.

Presentation summarising work to date on one of the models

This link will take you to a powerpoint presentation concentrating on the model relating to Mindfulness Based Cognitive Therapy.

References

  1. Long, K. M., McDermott, F., & Meadows, G. N. (2018). Being pragmatic about healthcare complexity: our experiences applying complexity theory and pragmatism to health services research. BMC Medicine, 16(1), 94. doi:10.1186/s12916-018-1087-6
  2. Long, K. M., & Meadows, G. N. (2018). Simulation modelling in mental health: A systematic review. Journal of Simulation, 12(1), 76-85. doi:10.1057/s41273-017-0062-0
  3. Long K, Meadows GN,Simulation modelling for psychiatric service planning: a mixed methods protocol. JMIR Research Protocols. 2018; accepted - reprint available on-line. DOI: 10.2196/11119
  4. Patten SB, Gordon-Brown L, Meadows G.  Simulation studies of age-specific lifetime major depression prevalence.  BMC Psychiatry. 2010;10(85).
  5. Patten S,  Meadows G. Linking Epidemiologic Evidence to Practice: Mindfulness Based Cognitive Therapy as a Case in Point. Psychiatric Services.  2009;60:1540-1542.
  6. Meadows G, Gielewski H, Falconer B, Kelly H, Joubert L, Clarke M.  The pattern of care model: A tool for planning community mental health  services. Psychiatric Services. 1997;48(2):218 - 223.