Unravelling elements of value of healthcare and assessing their importance using evidence from two discrete-choice experiments in England

Background Health systems are moving towards value-based care, implementing new care models that allegedly aim beyond patient outcomes. Therefore, a policy and academic debate is underway regarding the definition of value in healthcare, the inclusion of costs in value metrics, and the importance of each value element. This study aimed to define healthcare value elements and assess their relative importance (RI) to the public in England. Method Using data from 26 semi-structured interviews and a literature review, and applying decision-theory axioms, we selected a comprehensive and applicable set of value-based elements. Their RI was determined using two discrete choice experiments (DCEs) based on Bayesian D-efficient DCE designs, with one DCE incorporating healthcare costs expressed as income tax rise. Respondent preferences were analysed using mixed logit models. Results Six value elements were identified: additional life-years, health-related quality of life, patient experience, target population size, equity, and cost. The DCE surveys were completed by 402 participants. All utility coefficients had the expected signs and were statistically significant (p < 0.05). Additional life-years (25.3%; 95% confidence interval [CI] 22.5–28.6%) and patient experience (25.2%; 95% CI 21.6–28.9%) received the highest RI, followed by target population size (22.4%; 95% CI 19.1–25.6%) and quality of life (17.6%; 95% CI 15.0–20.3%). Equity had the lowest RI (9.6%; 95% CI 6.4–12.1%), decreasing by 8.8 percentage points with cost inclusion. A similar reduction was observed in the RI of quality of life when cost was included. Conclusion The public prioritizes value elements not captured by conventional metrics, such as quality-adjusted life-years. Although cost inclusion did not alter the preference ranking, its inclusion in the value metric warrants careful consideration

Commissioning [integrated] care in England: an analysis of the current decision context

Background: The emergence of Integrated Care Systems (ICSs) across England poses an additional challenge and responsibility for local commissioners to accelerate the implementation of integrated care programmes and improve the overall efficiency across the system. To do this, ICS healthcare commissioners could learn from the experience of the former local commissioning structures and identify areas of improvement in the commissioning process. This study describes the investment decision process in integrated care amid the transition toward ICSs, highlights challenges, and provides recommendations to inform ICSs in their healthcare commissioning role. Methods: Twenty-six semi-structured interviews were conducted with local commissioners and other relevant stakeholders in South East England in 2021. Interviews were supplemented with literature. Results: England’s local healthcare commissioning has made the transition towards a new organisational architecture, with some integrated care programmes running, and a dual top-down and bottom-up prioritisation process in place. The commissioning and consequent development of integrated care programmes have been hindered by various barriers, including difficulties in accessing and using information, operational challenges, and resource constraints. Investment decisions have mainly been driven by national directives and budget considerations, with a mixture of subjective and objective approaches. A systematic and data-driven framework could replace this ad-hoc prioritisation of integrated care and contribute to a more rational and transparent commissioning process. Conclusion: The emerging ICSs seem to open an opportunity for local commissioners to strengthen the commissioning process of integrated care with evidence-based priority-setting approaches similar to the well-established health technology assessment framework at the national level

Supporting the local decision-making process in England in the context of integrated care

Over the last decade, England has emphasised the implementation of new care models and restructured the local commissioning architecture aiming to strengthen its integration agenda. Although this overhaul has increased the need for evidence-based decisions, research suggests that local commissioners may not have enough evidence to make well-informed investment decisions. Evaluating these models systematically and empirically can be challenging, and traditional economic evaluation methods may not be suitable. This thesis develops a relevant, practical and theoretically sound decision-support framework, based on multi-criteria decision analysis (MCDA) for evaluating and monitoring new models of care at local level in England. The framework’s structure was informed by semi-structured interviews with local stakeholders and a systematic literature review on the application of MCDA in healthcare. Public preferences were integrated through a discrete choice experiment (DCE) with the general public. The framework's feasibility was tested on two early intervention in psychosis (EIP) services using electronic health record data. The interviews highlighted the importance of rational and transparent local commissioning processes. Through the interviews and literature review, a comprehensive set of value-based elements was identified that can be objectively applied to assess new models of care. Results of the DCE suggest that the public assigns high importance to elements of value that are not captured in conventional value metrics. The EIP evaluation demonstrated the framework's feasibility in mental health, a key priority area for NHS England. The DCE and service evaluation emphasised the importance of reporting the MCDA total score with and without the cost criterion. The proposed decision-support framework has the potential to assist decision-makers in strengthening the local commissioning process for integrated care. Although further exploration is required to determine its broader applicability and effectiveness, the proposed framework establishes a basis to enhance local population health management in England, underpinned by real-world evidence

Erratum to: Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition) (Autophagy, 12, 1, 1-222, 10.1080/15548627.2015.1100356

non present