Aim: To use quantitative and qualitative research methods to investigate:

• Whether and how care services for people with rare diseases are coordinated in the UK, and
• How patients and their families affected by rare diseases and health care professionals who treat rare diseases would like them to be coordinated

Questions:

1. What does “coordinated care” mean? What are the specific components which characterise “coordinated care“? In what ways and why may coordinated care for people with rare diseases be similar or different to coordinated care for people with other conditions?
2. Is care for people with rare diseases in the UK coordinated, and if so, how?
3. What are the preferences of patients, families and professionals in relation to how care for rare diseases is coordinated?
4. What are the different ways in which care for people with rare diseases might be coordinated?
5. How much do these options cost?

Funder: National Institute for Health Research Health Services and Delivery Research Programme (project number 16/116/82).
PI: Prof Steve Morris
Health Economist: Emma Hudson
Further information: https://geneticalliance.org.uk/our-work/healthcare-and-delivery/coordinated-care-of-rare-diseases-concord/

Background:

Child maltreatment (CM), and domestic violence and abuse (DVA) are highly prevalent violations of human rights, associated with a spectrum of adverse short- and long-term impacts on the health, wellbeing and life opportunities of affected individuals.

Both CM and DVA share multiple common family and environmental risk factors, leading to co-occurrence of CM and DVA in approximately 30% to 60% of households. To date, economic impact studies have considered CM or DVA individually but have not accounted for the impact of co-occurrence on outcomes and subsequent costs to society.

Aims:

• Develop a multi-sectoral incidence-based cost model to quantify the combined lifetime UK societal costs associated with CM and DVA in families.
• Develop an economic model accounting for the interaction between CM, DVA, to estimate the lifetime societal cost, and to evaluate the cost-effectiveness of relevant interventions.
• Develop a web-based resource for the use of local and national decision-makers to explore the impact of adopting alternative policies under user-defined scenarios and assumptions.

Methods:

• Scoping review of relevant economic impact studies focused on CM and/or DVA
• Systematic review of the current literature to identify all short- and long-term outcomes arising from exposure to CM and DVA in the UK, and to derive the best available estimates for the risks, resource use, health-related quality of life (HRQoL) and costs associated with these outcomes.
• De novo analyses of relevant electronic patient record databases and longitudinal cohort study data to extend the evidence base for costs associated with CM and DVA.
• Using the evidence from objectives 1, 2 and 3, develop an incidence-based cost model to quantify the combined lifetime costs of CM and DVA in families from a societal perspective.
• Identification of interventions and policies suitable for inclusion in a full economic model.
• Develop a full economic model with a lifetime (up to 85 years of age) time horizon, to evaluate the cost-effectiveness of interventions identified in objective 4.

PI: Prof Steve Morris
Health Economist: Dr Kevin Herbert

Our researchers are in specifically involved in the economic analysis component of DEPICT.

Background of economic analysis:
PICRT models Transport teams across the country are set-up in different ways and each approach has associated costs and benefits. in order to identify the costs and benefits and make comparisons between models so that it may be possible to find ways of improving efficiency.

Aim of economic analysis:
To perform cost effectiveness analyses of Paediatric Intensive Care Retrieval Teams (PICRT) provision for critically ill children, comparing different models currently in use.

Questions:

• What are the costs and outcomes at 30 days following PICU admission?
• What are the costs, outcomes and benefits at one year following PICU admission?
• What are the lifetime costs and benefits in the longer-term?

A UK NHS and personal social services (PSS) perspective will be adopted for the short- and medium-run analyses, though PSS cost are expected to be negligible in the short-run; in the long-run analysis, an NHS/PSS perspective will be adopted in the base case and a societal perspective will be adopted in the sensitivity analysis. Costs are considered in terms of cost of transport, cost of NHS resource, cost to families and primary care cost. Outcomes are considered in terms of mortality and benefits are considered in terms of Quality Adjusted Life Years (QALYs)

Methods of economic analysis:
Analyses of the mortality data will use the same method as the primary outcome analysis for the DEPICT study (https://depict-study.org.uk). QALYs will be analysed using a similar approach using linear models. Cost data are likely to be skewed and so to analyse these data (at 30 days, one year and lifetime) we will use a generalised linear model with gamma family and log link, but will consider using other functional forms, such as Normal, Gaussian, inverse Gaussian and negative binomial distributions, selecting the model that gives the best fit of the data in terms of residual plots and the Akaike Information Criterion.

Current guidance on conduct of economic evaluations using observational data to assess the main assumptions for addressing selection bias in the statistical models implemented will be used. A regression analyses will estimate lives saved, differences in costs, and QALYs gained between different PICRT models. We will consider other approaches to the basic regression approach e.g., propensity score matching.

Cost-effectiveness will be measured using incremental net monetary benefits (NMBs) calculated at different values of the willingness to pay to avoid one death e.g., £100,00-£200,000 per death averted or gain one QALY. e.g., £15,000-£30,000 £ per QALYs gained. There will be considerable uncertainty in our estimates, especially in the medium- and long-run analyses. We will investigate this extensively using deterministic and probabilistic sensitivity analysis, including accounting for the uncertainty in the predicted values from the analysis of the different, linked datasets. Parametric and non-parametric bootstrap methods will be employed to evaluate uncertainty around differences in the lives saved, QALYs gained, costs and NMB, and we will construct cost-effectiveness acceptability curves.

Funder: National Institute for Health Research Health Services and Delivery Research Programme (project number 16/116/82)
PI: Dr Padmanabhan Ramnarayan (Great Ormond Street Hospital)
Lead Health Economist: Prof Steve Morris
Health Economist: Emma Hudson
Further information: https://depict-study.org.uk

Background
The WRAP trial showed that behavioural weight loss programmes could be effective in the short-term to decrease people weight and, by doing so, mitigate the risk factors for some diseases, such as diabetes and cancers.

Aims
WRAP-UP is an extension study of WRAP, which aims to shed light on the long-term effects of the weight loss programmes investigated in WRAP and, thus, assess their cost-effectiveness.

Methods
Individuals with a body mass index of 28 kg/m2 or higher were randomised to either a weight-management programme or standard care, namely brief advice and self-help materials. The 5-year data on resource consumption, patients’ weight loss and their quality of life collected during WRAP-UP will be used to perform a cost-effectiveness analysis. The results of the within-trial cost-effectiveness analysis will be presented by incremental cost-effectiveness ratios, which will describe the incremental cost for 1 kg of weight loss alongside the incremental cost to obtain one additional QALY. A simulation study will extrapolate the within-trial results to assess whether the life-time effects of WRAP-UP programmes could represent good value for money for the NHS.

Funder: National Institute for Health Research Programme Grants for Applied Research (NIHR RP-PG-0216-20010).
PI: Dr Amy Ahern
Health Economist: Dr Francesco Fusco