System dynamics applications to European health care issues

Dangerfield, Brian

doi:10.1057/palgrave.jors.2600729

Cited by 92 publications

(41 citation statements)

References 24 publications

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“…feedback). Typical examples of feedback include infectious disease outcomes, where higher levels of infection produce higher risks of further infection but also reduce the number of people in the susceptible pool, and health care service constraints, where the system performs differently when it is full or over-capacity [23][24][25]. Factors affecting rates of change may include behavioural influences.…”

Section: Aggregate Models With Interaction Allowedmentioning

confidence: 99%

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A taxonomy of model structures for economic evaluation of health technologies

2006

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Models for the economic evaluation of health technologies provide valuable information to decision makers. The choice of model structure is rarely discussed in published studies and can affect the results produced. Many papers describe good modelling practice, but few describe how to choose from the many types of available models. This paper develops a new taxonomy of model structures. The horizontal axis of the taxonomy describes assumptions about the role of expected values, randomness, the heterogeneity of entities, and the degree of non-Markovian structure. Commonly used aggregate models, including decision trees and Markov models require large population numbers, homogeneous sub-groups and linear interactions. Individual models are more flexible, but may require replications with different random numbers to estimate expected values. The vertical axis of the taxonomy describes potential interactions between the individual actors, as well as how the interactions occur through time. Models using interactions, such as system dynamics, some Markov models, and discrete event simulation are fairly uncommon in the health economics but are necessary for modelling infectious diseases and systems with constrained resources. The paper provides guidance for choosing a model, based on key requirements, including output requirements, the population size, and system complexity.

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Section: Aggregate Models With Interaction Allowedmentioning

confidence: 99%

“…There have been applications concerned with community care, short-term psychiatric care, HIV/ AIDS [24], smallpox preparedness [27][28][29], CJD [30] and others.…”

Section: Aggregate Models With Interaction Allowedmentioning

confidence: 99%

A taxonomy of model structures for economic evaluation of health technologies

2006

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“…Today, SD methodology is used beyond the industrial setting and has been applied in many different fields of study including health care. 13 SD combines both qualitative and quantitative aspects and aims to enhance understanding of complex systems, to gain insights into system behaviour. The qualitative aspect entails the construction of ''causal maps'' or ''influence diagrams'' in which the system structure and the interrelations between the components of a system are explored.…”

Section: Brief Introduction To System Dynamicsmentioning

confidence: 99%

Reviewing emergency care systems I: insights from system dynamics modelling

Lattimer

2004

Emergency Medicine Journal

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Objectives: To describe the components of an emergency and urgent care system within one health authority and to investigate ways in which patient flows and system capacity could be improved. Methods: Using a qualitative system dynamics (SD) approach, data from interviews were used to build a conceptual map of the system illustrating patient pathways from entry to discharge. The map was used to construct a quantitative SD model populated with demographic and activity data to simulate patterns of demand, activity, contingencies, and system bottlenecks. Using simulation experiments, a range of scenarios were tested to determine their likely effectiveness in meeting future objectives and targets. Results: Emergency hospital admissions grew at a faster annual rate than the national average for 1998-2001. Without intervention, and assuming this trend continued, acute hospitals were likely to have difficulty sustaining levels of elective work, in reaching elective admission targets and in achieving bed occupancy targets. General practice admissions exerted the greatest influence on occupancy rates. Prevention of emergency admissions for older people (3%-6% each year) reduced bed occupancy in both hospitals by 1% per annum over five years. Prevention of emergency admissions for patients with chronic respiratory disease affected occupancy less noticeably, but because of the seasonal pattern of admissions, had an effect on peak winter occupancy. Conclusions: Modelling showed the potential consequences of continued growth in demand for emergency care, but also considerable scope to intervene to ameliorate the worst case scenarios, in particular by increasing the care management options available in the community.

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“…This paper presents a qualitative analysis carried out within a larger programme of work using Operations Research (OR) methods, specifically system dynamics (SD) modelling (Dangerfield, ; Rosenhead & Mingers, ), to explore the organisation of services for admission and admission avoidance. SD modelling is a well‐established approach to describing complex systems and may, in its quantitative phase, be used for predictive simulation modelling of different service organisation scenarios.…”

Section: Methodsmentioning

confidence: 99%

Professional perspectives on systemic barriers to admission avoidance: learning from a system dynamics study of older people's admission pathways

Walsh

Lattimer

Wintrup

et al. 2014

Int J Older People Nursing

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Background. There is debate worldwide about the best way to manage increased healthcare demand within ageing populations, particularly rising rates of unplanned and avoidable hospital admissions. Objectives. To understand health and social care professionals' perspectives on barriers to admission avoidance throughout the admissions journey, in particular: the causes of avoidable admissions in older people; drivers of admission and barriers to use of admission avoidance strategies; and improvements to reduce unnecessary admissions. Design. A qualitative framework analysis of interview data from a System dynamics (SD) modelling study. Methods. Semi-structured interviews were conducted with twenty health and social care professionals with experience of older people's admissions. The interviews were used to build understanding of factors facilitating or hindering admission avoidance across the admissions system. Data were analysed using framework analysis. Results. Three overarching themes emerged: understanding the needs of the patient group; understanding the whole system; and systemwide access to expertise in care of older people. There were diverse views on the underlying reasons for avoidable admissions and recognition of the need for whole-system approaches to service redesign. Conclusions. Participants recommended system redesign that recognises the specific needs of older people, but there was no consensus on underlying patient needs or © 2014 John Wiley & Sons Ltd 1 specific service developments. Access to expertise in management of older and frailer patients was seen as a barrier to admission avoidance throughout the system. Implications for practice. Providing access to expertise and leadership in care of frail older people across the admissions system presents a challenge for service managers and nurse educators but is seen as a prerequisite for effective admission avoidance. System redesign to meet the needs of frail older people requires agreement on causes of avoidable admission and underlying patient needs.Key words: admission avoidance, frailty, framework analysis, hospital admissions, older people, system dynamics modelling What does this research add to existing knowledge in gerontology?• Professionals' assumptions about patient needs and service development were not shared across professional groups and services.• Although professionals acknowledged the need for whole-system service redesign, this study revealed that professionals had only a partial understanding of the whole admissions system.• Lack of expertise in care of older people was seen as a systemwide limitation on development and delivery of admission avoidance services.What are the implications of this new knowledge for nursing care with older people?• The nursing profession must consider how expertise and leadership in care of older people can be developed across the healthcare system.• Nurses with expertise in care of older people to disseminate and develop effective interventions which acknowledge the specific needs of frail older ...

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System dynamics applications to European health care issues

Cited by 92 publications

References 24 publications

A taxonomy of model structures for economic evaluation of health technologies

A taxonomy of model structures for economic evaluation of health technologies

Reviewing emergency care systems I: insights from system dynamics modelling

Professional perspectives on systemic barriers to admission avoidance: learning from a system dynamics study of older people's admission pathways

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