Our latest research, all in one place. Browse our collection of journal articles, reports and conference proceedings to see how we’re contributing to HEOR research. Remember to:
INTRODUCTION: There is an ever-increasing demand for social care in the UK, with expenditure predicted to double to £56 billion by 2038/39. Many councils are under budget restrictions putting pressure on the number of services provided and their quality. Telecare complements social care and involves the implementation of technology to keep individuals more independent.
METHODS: This study utilised a retrospective time-series analysis of data provided by Lancashire County Council between the period January-2013 to March-2018. A generalised linear mixed model (GLMM) was used to control for potential confounders. Two groups were identified: those using telecare (telecare group, n = 699) and those who did not (control group, n = 839).
RESULTS: The fixed effects data showed that telecare group start £75 per week lower in cost and as time progressed this reduced further by 9p per service user per week. In contrast, control group costs rose 5p per week per user. This effect was independent of age but was affected by measure of dependency. Analysis was then utilised to make predictions based on weighted averages. The scenario showed a total difference of £4,949 per service user over the whole year. A second scenario pro-rata'd costs for the full year showed a difference of £6,214, where telecare would avoid costs of £17 million per year.
DISCUSSION: This analysis demonstrates that there is evident potential for the use of telecare to reduce social care resource use and costs. This study also highlights the use of a GLMM as a novel method of analysing observed data by controlling confounders.
Matthew Taylor and Karina Watts outline methods of evaluating the cost-effectiveness of different treatments for acid reflux, focusing on antacids and proton-pump inhibitors.
OBJECTIVES: The aim of this study was to develop a comprehensive economic evaluation of the integrated cognitive assessment (ICA) tool compared with standard cognitive tests when used for dementia screening in primary care and for initial patient triage in memory clinics.
METHODS: ICA was compared with standard of care comprising a mixture of cognitive assessment tools over a lifetime horizon and employing the UK health and social care perspective. The model combined a decision tree to capture the initial outcomes of the cognitive testing with a Markov structure that estimated long-term outcomes of people with dementia. Quality of life outcomes were quantified using quality-adjusted life years (QALYs), and the economic benefits were assessed using net monetary benefit (NMB). Both costs and QALYs were discounted at 3.5% per annum and cost-effectiveness was assessed using a threshold of £20,000 per QALY gained.
RESULTS: ICA dominated standard cognitive assessment tools in both the primary care and memory clinic settings. Introduction of the ICA tool was estimated to result in a lifetime cost saving of approximately £123 and £226 per person in primary care and memory clinics, respectively. QALY gains associated with early diagnosis were modest (0.0016 in primary care and 0.0027 in memory clinic). The net monetary benefit (NMB) of ICA introduction was estimated at £154 in primary care and £281 in the memory clinic settings.
CONCLUSION: Introduction of ICA as a tool to screen primary care patients for dementia and perform initial triage in memory clinics could be cost saving to the UK public health and social care payer.
Green space matters for mental health but is under constant pressure in an increasingly urbanising world. Often there is little space available in cities for green areas, so it is vital to optimise the design and usage of these available green spaces. To achieve this, experts in planning, design and nature conservation need to know which types and characteristics of green spaces are most beneficial for residents' mental health.
A scoping review of studies that compare different green space types and characteristics on mental health was conducted. A total of 215 (experimental, observational and qualitative) papers were included in the scoping review.
This review highlights a high level of heterogeneity in study design, geographical locations, mental health outcomes and green space measures. Few of the included studies were specifically designed to enable direct comparisons between green space types and characteristics (e.g. between parks and forests). The included studies have predominantly experimental research designs looking at the effects of short-term exposure to green space on short-term mental health outcomes (e.g. affect and physiological stress). More studies enabled only indirect comparisons, either within the same study or between different studies.
Analysis of the direction of the mental health outcomes (positive, neutral, negative) from exposure to various types and characteristics of green space found positive (i.e. beneficial) effects across all green space types. However, green space characteristics did appear to render more diverse effects on mental health, which is especially the case for vegetation characteristics (e.g. higher vegetation density can be negative for mental health).
The scoping review reveals gaps in the present evidence base, with a specific need for more studies directly comparing green space types and characteristics within the same study. Proposed future research directions include the use of longitudinal research designs focusing on green space characteristics, considering actual exposure and systematically addressing heterogeneity in factors influencing the relation between green spaces and mental health (e.g. type of interaction, user experience).
Living reviews are an increasingly popular research paradigm. The purpose of a 'living' approach is to allow rapid collation, appraisal and synthesis of evolving evidence on an important research topic, enabling timely influence on patient care and public health policy. However, living reviews are time- and resource-intensive. The accumulation of new evidence and the possibility of developments within the review's research topic can introduce unique challenges into the living review workflow. To investigate the potential of software tools to support living systematic or rapid reviews, we present a narrative review informed by an examination of tools contained on the Systematic Review Toolbox website. We identified 11 tools with relevant functionalities and discuss the important features of these tools with respect to different steps of the living review workflow. Four tools (NestedKnowledge, SWIFT-ActiveScreener, DistillerSR, EPPI-Reviewer) covered multiple, successive steps of the review process, and the remaining tools addressed specific components of the workflow, including scoping and protocol formulation, reference retrieval, automated data extraction, write-up and dissemination of data. We identify several ways in which living reviews can be made more efficient and practical. Most of these focus on general workflow management, or automation through artificial intelligence and machine-learning, in the screening process. More sophisticated uses of automation mostly target living rapid reviews to increase the speed of production or evidence maps to broaden the scope of the map. We use a case study to highlight some of the barriers and challenges to incorporating tools into the living review workflow and processes. These include increased workload, the need for organisation, ensuring timely dissemination and challenges related to the development of bespoke automation tools to facilitate the review process. We describe how current end-user tools address these challenges, and which knowledge gaps remain that could be addressed by future tool development. Dedicated web presences for automatic dissemination of in-progress evidence updates, rather than solely relying on peer-reviewed journal publications, help to make the effort of a living evidence synthesis worthwhile. Despite offering basic living review functionalities, existing end-user tools could be further developed to be interoperable with other tools to support multiple workflow steps seamlessly, to address broader automatic evidence retrieval from a larger variety of sources, and to improve dissemination of evidence between review updates.
OBJECTIVE: Exploratory analysis to conceptualize and evaluate the potential cost-effectiveness and economic drivers of using a novel tissue valve compared with mechanical heart valves for surgical aortic valve replacement (SAVR) in people aged 55-64 and 65+ with aortic stenosis (AS) from a National Health Service (NHS) UK perspective.
METHODS: A decision-analytic model was developed using a partitioned survival model. Parameter inputs were obtained from published literature. Deterministic and probabilistic sensitivity analyses (DSA and PSA) were conducted to explore the uncertainty around the parameters.
RESULTS: The novel tissue valve was potentially associated with higher quality-adjusted life years (QALYs) of 0.01 per person. Potential cost savings were greatest for those aged 55-64 (£408) versus those aged 65+(£53). DSA indicated the results to be most dependent on relative differences in general mortality, procedure costs, and reoperation rates. PSA estimated around 75% of the iterations to be cost-effective at £20,000 per QALY for those aged 55-64, and 57% for those aged 65+.
CONCLUSIONS: The exploratory analysis suggests that the novel tissue valve could be a cost-effective intervention for people over the age of 55 with AS who are suitable for SAVR in the UK.
Understanding the drivers of health and economic cost for the treatment of mental health conditions is critical to meet the accelerating demands for care. We conducted an economic evaluation of real-world healthcare-systems data from 27,540 patients receiving care for a mood or an anxiety disorder within the UK National Healthcare Service. Using Markov models built on discrete health states to compare the cost-effectiveness of different interventions, we show that the principal drivers of healthcare cost relate to waiting times and treatment effectiveness. We find that internet-delivered cognitive behavioral therapy has a 'dominant' incremental cost-effectiveness ratio relative to standard care, offering similar clinical effectiveness but with shorter treatment times. In most healthcare systems, the clinical effectiveness of mental healthcare remains unquantified, and long treatment times are common. The potential for these findings to inform mental healthcare policy is substantial, particularly around immediacy of access and the importance of outcomes-focused quality management.
