Abstract
We describe a decision support toolkit that was developed with the aim of assisting those responsible with the management and treatment of Parkinson’s disease (PD) in the UK. Having created a baseline model and established its face validity, the toolkit captures the complexity of PD services at a sufficient level and operates within a user-friendly environment; that is, an interface was built to allow users to specify their own local PD service and input their own estimates or data of service demands and capacities. The main strength of this decision support tool is the adoption of a team approach to studying the system, involving six PD specialist nurses across the country, ensuring that variety of views and suggestions are taken as well as systems modelling and simulations. The tool enables key decision-makers to estimate the likely impact of changes, such as increased use of community services on activity, cost, staffing levels, skill-mix and utilisation of resources. Such previously unobtainable quantitative information can be used to support business cases for changes in the increased use of community services and its impact on clinical outcomes (disease progression), nurse visits and costing.
Highlights
Parkinson’s disease (PD) is the second most common chronic neurodegenerative condition in older people especially beyond the age of sixty (De Rijk, et al 1997)
The importance of the research can be appreciated in the current context of increasing demand on health service provision at the time when we are moving to the new reality of tighter public finances
This might mean providers and purchasers of services (i.e. National Health Service (NHS) Trusts and Clinical Commissioning Groups, respectively) may need to re-design services with increased use of community services as opposed to treating patients within a hospital setting, because this is the way care has been organised over a number of years
Summary
Parkinson’s disease (PD) is the second most common chronic neurodegenerative condition in older people especially beyond the age of sixty (De Rijk, et al 1997). The tool should respond to the concerns of these end users and enable them to achieve a better understanding of the system structure and operations and how these influence key performance metrics, such as activity results (e.g. the number of patients treated per year), resource utilisation levels (e.g. neurologist, nurses, and beds) and clinical and cost outcomes (e.g. disease progression) In this context, the tool should accommodate the playing-out of a range of policies and scenarios relevant to decision makers and allow testing of the possible impact of these scenarios on the care system performance indicators. 2.1 Discrete-event simulation in healthcare DES has been commonly used in health management especially since the 1990 due to the increased complexity of health care systems, the shift to more evidence based decision making in the health sector, and the significant improvements in DES software capabilities and ease of use These applications have been first reviewed by England and Roberts (1978), who surveyed 92 models covering areas such as laboratory studies and emergency services. The model was used to evaluate 13 care options recommended by the English Bowel Cancer Advisory Committee as possible areas of service improvement and their impact on incremental life years gained, quality adjusted life years, and the cost per life year gained
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