The Online Elicitation of Personal Utility Functions (OPUF) tool: a new method for valuing health states

Introduction Standard valuation methods, such as TTO and DCE are inefficient. They require data from hundreds if not thousands of participants to generate value sets. Here, we present the Online elicitation of Personal Utility Functions (OPUF) tool; a new type of online survey for valuing EQ-5D-5L health states using more efficient, compositional elicitation methods, which even allow estimating value sets on the individual level. The aims of this study are to report on the development of the tool, and to test the feasibility of using it to obtain individual-level value sets for the EQ-5D-5L. Methods We applied an iterative design approach to adapt the PUF method, previously developed by Devlin et al., for use as a standalone online tool. Five rounds of qualitative interviews, and one quantitative pre-pilot were conducted to get feedback on the different tasks. After each round, the tool was refined and re-evaluated. The final version was piloted in a sample of 50 participants from the UK. A demo of the EQ-5D-5L OPUF survey is available at: https://eq5d5l.me Results On average, it took participants about seven minutes to complete the OPUF Tool. Based on the responses, we were able to construct a personal EQ-5D-5L value set for each of the 50 participants. These value sets predicted a participants' choices in a discrete choice experiment with an accuracy of 80%. Overall, the results revealed that health state preferences vary considerably on the individual-level. Nevertheless, we were able to estimate a group-level value set for all 50 participants with reasonable precision. Discussion We successfully piloted the OPUF Tool and showed that it can be used to derive a group-level as well as personal value sets for the EQ-5D-5L. Although the development of the online tool is still in an early stage, there are multiple potential avenues for further research.

Nephrology considerations in the management of durable and temporary mechanical circulatory support

Durable and temporary mechanical circulatory support (MCS) use is growing for a range of cardiovascular indications. Kidney dysfunction is common in persons evaluated for or receiving durable or temporary MCS, and portends worse outcomes. This kidney dysfunction can be due to pre-existing kidney chronic kidney disease (CKD), acute kidney injury (AKI) related to acute cardiovascular disease necessitating MCS, AKI due to cardiac procedures, and due to acute and chronic MCS effects and complications. Durable MCS, with implantable continuous flow pumps, is used for long-term support in advanced HF refractory to guideline directed medical and device therapy, either permanently or as a bridge to heart transplantation. Temporary MCS-encompassing in this review intra-aortic balloon pumps (IABPs), axial flow pumps, centrifugal flow pumps, and venoarterial ECMO-is used for diverse situations: high risk percutaneous coronary interventions (PCI), acute decompensated heart failure (HF), cardiogenic shock, and resuscitation following cardiac arrest. The wide adoption of MCS makes it imperative to improve understanding of the effects of MCS on kidney health/function, and of kidney health/function on MCS outcomes. The complex structure and functions of the kidney, and the complex health states of individuals receiving MCS, makes investigations in this area challenging, and current knowledge is limited. Fortunately, the increasing nephrology toolbox of non-invasive kidney health/function assessments may enable development and testing of individualized management strategies and therapeutics in the future. We review technology, epidemiology, pathophysiology, clinical considerations, and future directions in MCS and nephrology.

A Head-to-head Comparison of the EQ-5D-3L Index Scores Derived from the Two EQ-5D-3L Value Sets for China

Background: Two EQ-5D-3L (3L) value sets (developed in 2014 and 2018) co-exist in China. The study examined the level of agreement between index scores for all the 243 health states derived from them at both absolute and relative levels and compared the responsiveness of the two indices. Methods: Intraclass correlations coefficient (ICC) and Bland-Altman plot were adopted to assess the degree of agreement between the two indices at the absolute level. Health gains for 29,403 possible transitions between pairs of 3L health states were calculated to assess the agreement at the relative level. Their responsiveness for the transitions was assessed using Cohen effect size.Results：The mean (standard deviation, SD) value was 0.427 (0.206) and 0.649 (0.189) for the 3L2014 and 3L2018 index scores, respectively. Although the ICC value showed good agreement (i.e., 0.896), 88.9% (216/243) of the points were beyond the minimum important difference limit according to the Bland-Altman plot. The mean health gains for the 29,403 health transitions was 0.234 (3L2014 index score) and 0.216 (3L2018 index score). The two indices predicted consistent transitions in 23,720 (80.7%) of 29,403 pairs. For the consistent pairs, Cohen effective size value was 1.05 (3L2014 index score) or 1.06 (3L2018 index score); and the 3L2014 index score only yielded 0.007 more utility gains. However, the results based on the two measures varied substantially according to the direction and magnitude of health change. Conclusion：The 3L2014 and 3L2018 index scores are not interchangeable. The choice between them is likely to influence QALYs estimations.

Performing Cost-Effectiveness Analyses to Support Policy Making: Key Lessons From the Assessment of Aducanumab

The purpose of this paper is to describe the process and the methods of cost-effectiveness analysis for clinicians interested in joining or leading aspects of this branch of evidence-based research. Cost-effectiveness is a useful tool for policymakers and is considered a starting point for discussions of fair pricing. Clinicians are important members of teams conducting cost-effectiveness analyses, particularly as it relates to integrating their clinical expertise into the decisions around the design and conduct of the analysis. Their input is essential in assuring that models adequately reflect clinical practice and are informed by expert judgments of how existing data can best be interpreted to build a comprehensive analysis of the clinical and economic outcomes of different treatment options. We illustrate specific contributions that clinicians are well positioned to make in these teams using a recent cost-effectiveness analysis of aducanumab that was conducted to support fair drug pricing. While discussing these contributions, we explain key components of a cost-effectiveness analysis, such as time horizon, health states, and perspective, to support the understanding of the methods of cost-effectiveness by the clinical researchers and to promote a common dialogue among these multidisciplinary teams.

Interpretable machine learning for high-dimensional trajectories of aging health

We have built a computational model for individual aging trajectories of health and survival, which contains physical, functional, and biological variables, and is conditioned on demographic, lifestyle, and medical background information. We combine techniques of modern machine learning with an interpretable interaction network, where health variables are coupled by explicit pair-wise interactions within a stochastic dynamical system. Our dynamic joint interpretable network (DJIN) model is scalable to large longitudinal data sets, is predictive of individual high-dimensional health trajectories and survival from baseline health states, and infers an interpretable network of directed interactions between the health variables. The network identifies plausible physiological connections between health variables as well as clusters of strongly connected health variables. We use English Longitudinal Study of Aging (ELSA) data to train our model and show that it performs better than multiple dedicated linear models for health outcomes and survival. We compare our model with flexible lower-dimensional latent-space models to explore the dimensionality required to accurately model aging health outcomes. Our DJIN model can be used to generate synthetic individuals that age realistically, to impute missing data, and to simulate future aging outcomes given arbitrary initial health states.

Visualization and monitoring of damaging-healing processes of polymers by AIEgen-loaded multifunctional microcapsules

Polymeric materials play an essential and ubiquitous role in modern societies, but they are inevitably damaged during service, which can lead to compromised performance or even direct failure. The sensitive detection and dynamic monitoring of the health states of polymers is thus crucial to increase their reliability, safety, and lifetime. Herein, a facile fluorescence-based approach that can achieve the nondestructive, on-site, real-time, full-field, and sensitive visualization and monitoring of damaging-healing processes of polymers is demonstrated. By embedding novel UV-blocking microcapsules containing a diisocyanate solution of aggregation-induced emission luminogens (AIEgens) into a polymer matrix, the damaged regions of the composite show turn-on fluorescence and dual signal changes in both fluorescence intensity and fluorescence color can be observed during the healing processes. The invisible information of the static health states and dynamic healing processes can be directly and semi-quantitatively visualized by naked eyes based on the collective effects of AIE and twisted intramolecular charge transfer. In addition to the autonomous damage-reporting, self-healing, and health indication functionalities, the microcapsule-embedded polymeric coatings possess excellent photo- and water-protection capabilities, which are appealing to various practical applications.

Measuring the acceptability of EQ-5D-3L health states for different ages: a new adaptive survey methodology

Background Acceptable health and sufficientarianism are emerging concepts in health resource allocation. We defined acceptability as the proportion of the general population who consider a health state acceptable for a given age. Previous studies surveyed the acceptability of health problems separately per EQ-5D-3L domain, while the acceptability of health states with co-occurring problems was barely explored. Objective To quantify the acceptability of 243 EQ-5D-3L health states for six ages from 30 to 80 years: 1458 health state–age combinations (HAcs), denoted as the acceptability set of EQ-5D-3L. Methods In 2019, an online representative survey was conducted in the Hungarian general population. We developed a novel adaptive survey algorithm and a matching statistical measurement model. The acceptability of problems was evaluated separately per EQ-5D-3L domain, followed by joint evaluation of up to 15 HAcs. The selection of HAcs depended on respondents’ previous responses. We used an empirical Bayes measurement model to estimate the full acceptability set. Results 1375 respondents (female: 50.7%) were included with mean (SD) age of 46.7 (14.6) years. We demonstrated that single problems that were acceptable separately for a given age were less acceptable when co-occurring jointly (p < 0.001). For 30 years of age, EQ-5D-3L health states of ‘11112’ (11.9%) and ‘33333’ (1%), while for 80 years of age ‘21111’ (93.3%) and ‘33333’ (7.4%) had highest and lowest acceptability (% of population), respectively. Conclusion The acceptability set of EQ-5D-3L quantifies societal preferences concerning age and disease severity. Its measurement profiles and potential role in health resource allocation needs further exploration.

Mejora de la calidad de vida en cuidadores informales de personas dependientes mediante talleres educacionales

Introduction: The ageing of the population is associated with an increase in the number of dependent people, with an estimate of 15% living with a disability. The provision of care to family members entails an added responsibility associated with care-related problems, which can have a negative impact on caregivers. Therefore, we propose to design and evaluate a caregiving programme based on caregiver education, measuring knowledge, pain perception, emotional burden and health-related quality of life. Objective: The main objective is to improve the quality of life of informal caregivers through training interventions, in order to decrease the disability caused by caregiving tasks.Method: 99 caregivers belonging to the Aljarafe-Northern Seville Primary Care Health District participated, divided into control and intervention groups. We designed two educational workshops on care programmes for informal caregivers. They completed a knowledge questionnaire, and different validated scales related to pain, health states and quality of life.Results: Most of the caregivers presented back problems, for which they received pharmaceutical treatment. The implemented intervention was associated with a decrease in pain during basic activities of daily living, care and rest, as well as a reduction in strain index in both groups.Conclusions: Intervention programmes for informal carers of dependent patients are effective in improving the state of health and quality of life of this group, and their implementation should therefore be encouraged in primary care. Introducción: El envejecimiento de la población está asociado a un incremento de personas dependientes, estimándose que el 15% vive con alguna discapacidad. La prestación de cuidados a familiares supone una responsabilidad añadida asociada a problemas relacionados con el cuidado, que pueden repercutir negativamente en los cuidadores. Por ello, planteamos diseñar y evaluar un programa de cuidados, basado en la educación de los cuidadores, midiendo los conocimientos, la percepción del dolor, la carga emocional y la calidad de vida relacionada con la salud. Objetivo: El objetivo principal es mejorar la calidad de vida de los cuidadores informales mediante intervenciones formativas, con el fin de disminuir la incapacidad causada por las tareas del cuidado.Método: Participaron 99 cuidadores pertenecientes al Distrito Sanitario Aljarafe-Sevilla Norte de Atención Primaria, divididos en grupo control e intervención. Diseñamos dos talleres educacionales sobre programas de atención a cuidadores informales. Cumplimentaron un cuestionario de conocimientos, y diferentes escalas validadas relacionadas con el dolor, los estados de salud y la calidad de vida.Resultados: La mayor parte de los cuidadores presentaban problemas de espalda tomando medicación para ello. La intervención implementada se asoció a un descenso del dolor durante actividades básicas de la vida diaria, los cuidados y el descanso, y disminución del índice de esfuerzo en ambos grupos.Conclusiones: Los programas de intervención en cuidadores informales de pacientes dependientes resultan eficaces para mejorar el estado de salud y la calidad de vida de este colectivo por lo que se debe fomentar su realización desde la Atención Primaria.

Estimating Productivity, Detecting Biotic Disturbances and Assessing the Health State of Traditional Olive Groves, Using Nondestructive Phenotypic Techniques

Conservation of traditional olive groves through effective monitoring of their health state is crucial both at a tree and at a population level. In this study, we introduce a comprehensive methodological framework for estimating the traditional olive grove health state, by considering the fundamental phenotypic, spectral, and thermal traits of the olive trees. We obtained phenotypic information from olive trees on the Greek island of Lesvos by combining this with in situ measurement of spectral reflectance and thermal indices to investigate the effect of the olive tree traits on productivity, the presence of the olive leaf spot disease (OLS), and olive tree classification based on their health state. In this context, we identified a suite of important features, derived from linear and logistic regression models, which can explain productivity and accurately evaluate infected and noninfected trees. The results indicated that either specific traits or combinations of them are statistically significant predictors of productivity, while the occurrence of OLS symptoms can be identified by both the olives’ vitality traits and by the thermal variables. Finally, the classification of olive trees into different health states possibly offers significant information to explain traditional olive grove dynamics for their sustainable management.