Using system dynamics to help develop and implement policies and programmes in health care in England

Royston, Geoff; Dost, Ayesha; Townshend, Jeremy; Turner, Howard

doi:10.1002/(sici)1099-1727(199923)15:3<293::aid-sdr169>3.0.co;2-1

Cited by 115 publications

(45 citation statements)

References 17 publications

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“…For example, screening for disease, developing emergency health and managing waiting times for treatment. At the other end of the spectrum is the application of System Dynamics in more complex and wider ranging issues in health care, such as assessing public health risks, or planning the healthcare workforce [14]. This paper describes a System Dynamics model for the supply of doctors in Sri Lanka, which fits well with the above described scope and applications of System Dynamics.…”

Section: Discussionmentioning

confidence: 99%

How many doctors should we train for Sri Lanka? System dynamics modelling for training needs

Silva

2017

Ceylon Med. J.

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Section: Discussionmentioning

confidence: 99%

How many doctors should we train for Sri Lanka? System dynamics modelling for training needs

Silva

2017

Ceylon Med. J.

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“…8,16,17 Once systems thinking and SD models are validated, and there is confidence in their structure and behavior, they can be put to the task of generating plausible, sustainable solutions by using the model for policy testing, scenario analyses, or intervention optimization. [18][19][20][21][22] SD modeling has been used to examine health care quality improvement; 11,[23][24][25][26][27][28] community-based systems of care; [29][30][31][32] epidemiology and disease surveillance; [33][34][35][36][37] global health care management; [38][39][40] behavioral health interventions in tobacco; 37,[41][42][43][44][45] substance abuse; [46][47][48][49] and mental health; 9,50 as well as in managing chronic illness. 32,51,52 SD modeling to examine HIV epidemiology, prevention, and treatment has also been conducted.…”

Section: Introductionmentioning

confidence: 92%

Simulating Patterns of Patient Engagement, Treatment Adherence, and Viral Suppression: A System Dynamics Approach to Evaluating HIV Care Management

Lounsbury

Schwartz

Palma

et al. 2015

AIDS Patient Care and STDs

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System dynamics (SD) modeling belongs to the rapidly evolving, interdisciplinary field of system science research. This field adds value to more traditional health research by contributing to the design and testing of complex integrated models of change, to examine health system performance and patient outcomes. Using selected milestones in HIV care management to frame our simulation research, we created a SD model to examine three patient subgroups of women of color (WOC) represented in our multi-site cohort, classified by their health care seeking status at baseline. Asked to reflect on their circumstance 6 months prior to enrollment in the MSE cohort, 53% noted they were receiving some care (In Care, n = 341), 31% that they had been seeking care (Seeking Care, n = 201), and 16% that they were undecided about seeking care (i.e., answered that they may or may not look for care) for treatment of their HIV (May or May Not Seek Care, n = 103). Our SD model compared simulated patterns of patient retention over 24 months in relation to: (1) access to antiretroviral therapy (ART), (2) adherence to ART, and (3) viral suppression. Assessed patterns yielded insights about system capacities and constraints in the context of the SPNS initiative under evaluation.

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“…The most common state transition model is an S-I-R model (Kermack and McKendrick, 1927, is the classic reference; Anderson and May, 1991, provide coverage of additional applications, while Su et al, 1992, Royston et al, 1999, Bagni et al, 2002, Homer and Hirsch, 2006, and Udo et al, 2006, provide various epidemiological applications in a system dynamics context). Animals or herds in an S-I-R model can be either susceptible to disease (S), infected with FMD (I), or "removed" (R) from the system through either death, recovery from disease, or vaccination.…”

Section: S-i-r Models Of Fmd Spreadmentioning

confidence: 99%

An interregional system dynamics model of animal disease control: applications to foot‐and‐mouth disease in the Southern Cone of South America

Rich

2008

System Dynamics Review

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Foot-and-mouth disease (FMD) is costly for meat producers, given its ability to rapidly spread over space, with control efforts in one region crucially depending on the control efforts undertaken in other regions. This paper presents a model of FMD control that applies system dynamics to the spatial spread of disease among South American countries with traditionally different control regimes and assesses the impact of alternative control strategies. Model results demonstrate that preventative vaccination led to shorter outbreaks (by over 2 weeks) than other strategies, though the resources required to implement this may be difficult to mobilize. The model also shows that a combination of region-specific policies often controls disease better than uniform region-wide approaches, suggesting the need for improved multinational coordination of disease control.

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Using system dynamics to help develop and implement policies and programmes in health care in England

Cited by 115 publications

References 17 publications

How many doctors should we train for Sri Lanka? System dynamics modelling for training needs

How many doctors should we train for Sri Lanka? System dynamics modelling for training needs

Simulating Patterns of Patient Engagement, Treatment Adherence, and Viral Suppression: A System Dynamics Approach to Evaluating HIV Care Management

An interregional system dynamics model of animal disease control: applications to foot‐and‐mouth disease in the Southern Cone of South America

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