Building the economic evidence case for social prescribing

Understanding the economic impact of social prescribing remains an urgent priority for the National Academy of Social Prescribing (NASP). As yet it is unclear how much data exists within the different systems to enable economic analyses of the impact of social prescribing schemes to be conducted. The complexity in understanding the economic impact of social prescribing—and indeed all non-clinical community-based approaches to health—is compounded by the multisector nature of social prescribing. Furthermore, a variety of approaches are being used to test similar but different understandings of both cost and value, including social value, cost, benefit and economic value. There are a growing range of reports and peer-reviewed publications that focus on the impact of social prescribing on health and social care demand, some of which have economic analyses and some which remain as potential data sets for economic analyses. At least one third of all outcomes (if not more) are directly related to the social determinants of health1,2 (SDH) which are not taken into account with economic analysis focused only on health service usage. This range of outcomes experienced by service users2-4 is driving many researchers to conduct economic analyses that attempt to assign value to outcomes beyond the health sector, for instance using social return on investment (SROI) and proxy values. Other researchers have discussed the evolution in economic analyses at length and suggest additional components to existing methodologies, e.g., multi criteria decision analysis (MCDA) to account for additional complexity of social prescribing5. Further developments are also being trialled such as the Wellbeing-adjusted Life Years (WELLBY) to understand the economic value attached to wellbeing6, as opposed to the Quality Adjusted Life Years (QALY), which reports the economic value of quality of life. We are entering an era of providing personalised support to people in integrated and multidisciplinary systems with different local population needs. As such, there is a need to evolve the approaches to determining cost and value of social prescribing, and to reach agreements on methodologies that all sectors are willing to accept as sound approaches. Furthermore, as discussed by McDaid and colleagues in 2019 7, there is a need to move beyond the immediate benefits of social prescribing and to explore the longer-term benefits of sustained engagement in non-clinical activities and provision of support to address issues linked to the SDH. This would enable more data to inform the preventative role and economic impact that social prescribing may have, which is currently an evidence gap. This rapid scoping review was commissioned by NASP and additional roundtables were supported by the National Centre for Creative Health and UKRI/AHRC’s ‘Mobilising Community Assets to Tackle Health Inequalities’ research programme (led by University College London). It aims to provide an update to the first economic evidence review from NASP and explore economic data and health and social care usage data in more detail. This rapid scoping review aims to ascertain: What the current literature indicates in terms of cost or value of social prescribing schemes or parts of the social prescribing scheme. If there are potential data sets that report the impact of social prescribing on health service usage that could have economic analysis applied to them. Stakeholder opinions on the methodological approaches for creating the current economic evaluation evidence base for social prescribing and potential future developments that are needed. How these findings can inform a larger programme of research that is needed to establish the economic impact and value of social prescribing across all relevant sectors in the community. As this report contains three separate elements to it, each element will be reported with methods and results, and then key themes will be brought together with recommendations

Changing a semantics: opportunism or courage?

The generalized models for higher-order logics introduced by Leon Henkin, and their multiple offspring over the years, have become a standard tool in many areas of logic. Even so, discussion has persisted about their technical status, and perhaps even their conceptual legitimacy. This paper gives a systematic view of generalized model techniques, discusses what they mean in mathematical and philosophical terms, and presents a few technical themes and results about their role in algebraic representation, calibrating provability, lowering complexity, understanding fixed-point logics, and achieving set-theoretic absoluteness. We also show how thinking about Henkin's approach to semantics of logical systems in this generality can yield new results, dispelling the impression of adhocness. This paper is dedicated to Leon Henkin, a deep logician who has changed the way we all work, while also being an always open, modest, and encouraging colleague and friend.Comment: 27 pages. To appear in: The life and work of Leon Henkin: Essays on his contributions (Studies in Universal Logic) eds: Manzano, M., Sain, I. and Alonso, E., 201

Analysis of lysine recognition and specificity of the Bacillus subtilis L box riboswitch

The ever-changing environment of a bacterial cell requires sophisticated mechanisms to adjust gene expression in response to changes in nutrient availability. L box riboswitch RNAs regulate gene expression in response to cellular lysine (lys) concentrations in the absence of additional regulatory factors. In Bacillus subtilis, binding of lysine (lys) to the L box RNA causes premature transcription termination in the leader region upstream of the lysC coding sequence. To date, little is known about the specific RNA–lys interactions required for transcription termination. In this study, we characterize features of the B. subtilis lysC leader RNA responsible for lys specificity, and structural elements of the lys molecule required for recognition. The wild-type lysC leader RNA can recognize and discriminate between lys and lys analogs. We identified leader RNA variants with mutations in the lys-binding pocket that exhibit changes in the specificity of ligand recognition. These data demonstrate that lysC leader RNA specificity is the result of recognition of ligand features through a series of distinct interactions between lys and nucleotides that comprise the lys-binding pocket, and provide insight into the molecular mechanisms employed by L box riboswitch RNAs to bind and recognize lys

Completeness in hybrid type theory

We show that basic hybridization (adding nominals and @ operators) makes it possible to give straightforward Henkin-style completeness proofs even when the modal logic being hybridized is higher-order. The key ideas are to add nominals as expressions of type t, and to extend to arbitrary types the way we interpret @i in propositional and first-order hybrid logic. This means: interpret @iαa, where αa is an expression of any type a, as an expression of type a that rigidly returns the value that αa receives at the i-world. The axiomatization and completeness proofs are generalizations of those found in propositional and first-order hybrid logic, and (as is usual in hybrid logic) we automatically obtain a wide range of completeness results for stronger logics and languages. Our approach is deliberately low-tech. We don’t, for example, make use of Montague’s intensional type s, or Fitting-style intensional models; we build, as simply as we can, hybrid logic over Henkin’s logic.submittedVersionFil: Areces, Carlos Eduardo. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina.Fil: Blackburn, Patrick. University of Roskilde. Centre for Culture and Identity. Department of Philosophy and Science Studies; Dinamarca.Fil: Huertas, Antonia. Universitat Oberta de Catalunya; España.Fil: Manzano, María. Universidad de Salamanca; España.Ciencias de la Computació

Ethnic differences in early onset multimorbidity and associations with health service use, long-term prescribing, years of life lost, and mortality: A cross-sectional study using clustering in the UK Clinical Practice Research Datalink

BACKGROUND: The population prevalence of multimorbidity (the existence of at least 2 or more long-term conditions [LTCs] in an individual) is increasing among young adults, particularly in minority ethnic groups and individuals living in socioeconomically deprived areas. In this study, we applied a data-driven approach to identify clusters of individuals who had an early onset multimorbidity in an ethnically and socioeconomically diverse population. We identified associations between clusters and a range of health outcomes. METHODS AND FINDINGS: Using linked primary and secondary care data from the Clinical Practice Research Datalink GOLD (CPRD GOLD), we conducted a cross-sectional study of 837,869 individuals with early onset multimorbidity (aged between 16 and 39 years old when the second LTC was recorded) registered with an English general practice between 2010 and 2020. The study population included 777,906 people of White ethnicity (93%), 33,915 people of South Asian ethnicity (4%), and 26,048 people of Black African/Caribbean ethnicity (3%). A total of 204 LTCs were considered. Latent class analysis stratified by ethnicity identified 4 clusters of multimorbidity in White groups and 3 clusters in South Asian and Black groups. We found that early onset multimorbidity was more common among South Asian (59%, 33,915) and Black (56% 26,048) groups compared to the White population (42%, 777,906). Latent class analysis revealed physical and mental health conditions that were common across all ethnic groups (i.e., hypertension, depression, and painful conditions). However, each ethnic group also presented exclusive LTCs and different sociodemographic profiles: In White groups, the cluster with the highest rates/odds of the outcomes was predominantly male (54%, 44,150) and more socioeconomically deprived than the cluster with the lowest rates/odds of the outcomes. On the other hand, South Asian and Black groups were more socioeconomically deprived than White groups, with a consistent deprivation gradient across all multimorbidity clusters. At the end of the study, 4% (34,922) of the White early onset multimorbidity population had died compared to 2% of the South Asian and Black early onset multimorbidity populations (535 and 570, respectively); however, the latter groups died younger and lost more years of life. The 3 ethnic groups each displayed a cluster of individuals with increased rates of primary care consultations, hospitalisations, long-term prescribing, and odds of mortality. Study limitations include the exclusion of individuals with missing ethnicity information, the age of diagnosis not reflecting the actual age of onset, and the exclusion of people from Mixed, Chinese, and other ethnic groups due to insufficient power to investigate associations between multimorbidity and health-related outcomes in these groups. CONCLUSIONS: These findings emphasise the need to identify, prevent, and manage multimorbidity early in the life course. Our work provides additional insights into the excess burden of early onset multimorbidity in those from socioeconomically deprived and diverse groups who are disproportionately and more severely affected by multimorbidity and highlights the need to ensure healthcare improvements are equitable

Modal Ω-Logic: Automata, Neo-Logicism, and Set-Theoretic Realism

This essay examines the philosophical significance of $\Omega$-logic in Zermelo-Fraenkel set theory with choice (ZFC). The duality between coalgebra and algebra permits Boolean-valued algebraic models of ZFC to be interpreted as coalgebras. The modal profile of $\Omega$-logical validity can then be countenanced within a coalgebraic logic, and $\Omega$-logical validity can be defined via deterministic automata. I argue that the philosophical significance of the foregoing is two-fold. First, because the epistemic and modal profiles of $\Omega$-logical validity correspond to those of second-order logical consequence, $\Omega$-logical validity is genuinely logical, and thus vindicates a neo-logicist conception of mathematical truth in the set-theoretic multiverse. Second, the foregoing provides a modal-computational account of the interpretation of mathematical vocabulary, adducing in favor of a realist conception of the cumulative hierarchy of sets

Complexity of equational theory of relational algebras with standard projection elements

The class $\mathsf{TPA}$ of t rue p airing a lgebras is defined to be the class of relation algebras expanded with concrete set theoretical projection functions. The main results of the present paper is that neither the equational theory of $\mathsf{TPA}$ nor the first order theory of $\mathsf{TPA}$ are decidable. Moreover, we show that the set of all equations valid in $\mathsf{TPA}$ is exactly on the $\Pi ^1_1$ level. We consider the class $\mathsf{TPA}^-$ of the relation algebra reducts of $\mathsf{TPA}$’s, as well. We prove that the equational theory of $\mathsf{TPA}^-$ is much simpler, namely, it is recursively enumerable. We also give motivation for our results and some connections to related work

The Escherichia coli transcriptome mostly consists of independently regulated modules

Underlying cellular responses is a transcriptional regulatory network (TRN) that modulates gene expression. A useful description of the TRN would decompose the transcriptome into targeted effects of individual transcriptional regulators. Here, we apply unsupervised machine learning to a diverse compendium of over 250 high-quality Escherichia coli RNA-seq datasets to identify 92 statistically independent signals that modulate the expression of specific gene sets. We show that 61 of these transcriptomic signals represent the effects of currently characterized transcriptional regulators. Condition-specific activation of signals is validated by exposure of E. coli to new environmental conditions. The resulting decomposition of the transcriptome provides: a mechanistic, systems-level, network-based explanation of responses to environmental and genetic perturbations; a guide to gene and regulator function discovery; and a basis for characterizing transcriptomic differences in multiple strains. Taken together, our results show that signal summation describes the composition of a model prokaryotic transcriptome