A scoping review of clusters of multiple long-term conditions in people with intellectual disabilities and factors impacting on outcomes for this patient group.

People with intellectual disabilities (ID) are vulnerable to multiple long-term conditions (MLTC). However, in the UK, there are no individual strategies tailored for them. This study synthesised evidence on prevalence of MLTC in people with ID alongside risk factors, outcomes and preventative strategies. The scoping review used the tool Abstrackr to search retrieved articles from three bibliographic databases. Of 933 articles initially screened and further identified, 20 papers met our inclusion criteria. Our findings revealed significant data on prevalence of MLTC in people with ID across the studies, but very limited data on clusters or patterns of co-occurrence in this population. The majority of papers explored risk factors and strategies for prevention of MLTC, but far fewer compared outcomes by MLTC. The identified gaps in the literature indicate the need for further research to identify clusters of MLTC and tailored prevention strategies to reduce poor outcomes in this population.

Development of modelling method selection tool for health services management: from problem structuring methods to modelling and simulation methods.

BACKGROUND: There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. AIM: The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. METHODS: This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). RESULTS: The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. CONCLUSIONS: A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.