Co-production in healthcare services: What we know, how we can evaluate it

Background In times of increasing population aging, higher incidence of chronic diseases and higher expectations regarding public service provision, healthcare services are under increasing strain to cut costs while keeping quality. In this context, debates on the importance of promoting systems of co-produced health between stakeholders have gained considerable traction both in the literature and in policy debates of the public sector (Dunston et al., 2009, Voorberg et al. 2015; European Commission 2010). Co-production occurs \u201cwhen public service organizations partner with external entities, including other public organizations, third sector, or service user, to jointly produce services that they previously produced on their own\u201d (Thomas, 2013, p. 788). In this perspective, co-production is not only a patient involvement tool, but mainly a managerial tool, where partner in the production process could influence the methods used to organise and manage the service delivery (Sorrentino et al., 2015; Brandsen and Honingh, 2015; Gilardi et al., 2016). Despite this widespread acceptance, minimal consensus exists on the mechanisms for evaluating the actual impacts of the co-production in healthcare sector. More specifically, little has been produced on how the results of these changing structures, practices and goals in healthcare management and provision can be monitored and evaluated (Hardyman et al., 2015; Gilardi et al., 2016; Palumbo, 2016). Objectives The study aims at filling this gap by developing a conceptual framework for assessing co-production in healthcare. Specifically, drawing on existing literature on co-production in healthcare, we develop an original analytical evaluation framework with respect to: i) the multidimensional perspectives to be taken into consideration; ii) the dimensions to be analysed; iii) the methods that allow implementing our framework in practice. Methodolody First of all, a quantitative bibliometric analysis, using Bibliometrix software (Aria and Cuccurullo, 2017), is carried out. The reference database chosen is WoS and the inclusion criterion is \u201cco-production AND heath* OR coproduction AND health*\u201d in topic. Moreover, the search is refined by language, i.e. English, and type of publication, i.e. journal academic article. No time limitation is selected. After deleting non-inherent papers, our final sample was made up of 213 papers. As second stage, a qualitative content analysis based on PRISMA protocol is developed, focusing on those papers targeting evaluation issues. Finally, a preliminary co-production evaluation model proposal is proposed and discussed. Main results The study shows an increasing attention on the co-production topic, as highlighted by an annual percentage growth rate of about 26% and the big increase in the last 5 years in number of publications. The countries with a highest number of publications and collaborations are UK (mainly England), Netherlands, Australia and USA. As expected, the most repeated keyword is co-production, however, it is interesting to underline the presence of \u201cmental health\u201d and \u201cpublic health\u201d, that can be assumed as the main topic of studies analyzed. Nonetheless, only few studies focus on the evaluation of outcomes. Among them, the content analysis has revealed a predominantly mono-dimensional and mono-stakeholder approach. Specifically, clinical, economic or psychological-social - mainly in terms of patient satisfaction \u2013 impacts (i.e. Lwembe et al., 2016; Harvey et al., 2017) are assessed. The analysis reveals that one of the main challenges of assessing co-production lies in its multi-dimensional nature; thus a multiple perspectives framework has to be adopted. To contribute filling this gap, we developed a preliminary multidimensional (i.e. performance indicators) and multi-stakeholder (i.e. different actors involved) evaluation model (Figure 1). Specifically, the framework takes into account the three main outcome domains \u2013 i) economic, ii) managerial/organisational and iii) clinical \u2013 and three main stakeholders involved \u2013 i) hospital, ii) healthcare professionals, iii) patients and their families. The economic and efficiency measures concerning direct and indirect cost for hospital and patients/family, should be integrated with clinical and managerial measures for each stakeholder: 1. Hospital: administrative efficiency, activating capacity, inclusiveness of decision making, stability/flexibility of rules, conflict resolution and collaboration climate, frequency of interaction. 2 Patient (and caregiver or family): objective (i.e. compliance) and subjective (i.e. quality of life, quality of care perception, patient satisfaction) indicators. 3. Healthcare professional and staff: objective (e.g. turnover rate, absences, injuries and work-related ill health) and subjective (e.g. burnout, satisfaction, healthcare professional engagement, occupational health, risk perception) indicators

A comprehensive framework for the activation, management, and evaluation of Co-production in the public sector

Co-production analyses the practices in which state or firms and lay actors work together in any phase of the production cycle. In the public sector, citizens are not seen as mere recipients of services but as co-producers at different stages. Scholarly interest in co-production has grown steadily in the past years. However, the research has yet to integrate the many co-production concepts into a distinctive theoretical comprehensive framework able to strengthen the understanding of the interrelated dynamics at play. The article conducts a systematic in- depth qualitative review of the co-production literature for the public sector. The results highlight the main components into four pillars of a comprehensive theoretical framework to guide scholars and practitioners in the activation and management of co-production as well as in the evaluation of its outcomes. The article concludes by formulating a future research agenda for co-production in the public sector

A Comparison Of Different Technologies For Thrust Vectoring In A Linear Aerospike

The aerospike nozzle represents an interesting technology for Single-Stage-To-Orbit vehicles because of its self-adapting capability. It is possible to get thrust vectoring capabilities in different ways. A straightforward solution consists in applying differential throttling to multiple combustion chambers which feed the nozzle. An alternative technology, which can be used in the presence of a common combustion chamber, is represented by fluidic thrust vectoring which requires the injection of a secondary flow from a slot on the wall. In this work, the flow field in a linear aerospike nozzle is numerically investigated by means of RANS simulations and both differential throttling and shock vectoring are studied. A parametric study is performed to evaluate the potential of the two technologies

N-terminal and C-terminal domains of calmodulin mediate FADD and TRADD interaction

FADD (Fas–associated death domain) and TRADD (Tumor Necrosis Factor Receptor 1-associated death domain) proteins are important regulators of cell fate in mammalian cells. They are both involved in death receptors mediated signaling pathways and have been linked to the Toll-like receptor family and innate immunity. Here we identify and characterize by database search analysis, mutagenesis and calmodulin (CaM) pull-down assays a calcium-dependent CaM binding site in the α-helices 1–2 of TRADD death domain. We also show that oxidation of CaM methionines drastically reduces CaM affinity for FADD and TRADD suggesting that oxidation might regulate CaM-FADD and CaM-TRADD interactions. Finally, using Met-to-Leu CaM mutants and binding assays we show that both the N- and C-terminal domains of CaM are important for binding

Numerical Simulation of a Vectored Axisymmetric Nozzle

A CFD based approach to the fully three-dimensional simulation of vectored nozzle is presented. The underlying tech- nology used is based on an active flow control technique known as Fluidic Thrust-Vectoring. The flow governing equations are solved by using a finite volume discretization of the compressible Unsteady RANS equations. The numerical results obtained are compared with the experimental data found in the open literature

La gestione delle operations in tempo di crisi: le prime 10 lezioni apprese dalle Aziende Sanitarie

La gestione delle operations \ue8 centrale per affrontare problemi di standardizzazione, riorganizzazione e riprogettazione di flussi e percorsi di pazienti e beni sanitari con l\u2019obiettivo di eliminare o ridurre la variabilit\ue0. Questo contributo intende offrire una riflessione su come le aziende sanitarie e gli ospedali abbiano affrontato l\u2019emergenza dovuta alla pandemia da COVID-19 dal punto di vista della gestione delle operations. A tale scopo sono state analizzate le esperienze di sette Aziende Sanitarie presenti nelle Regioni italiane pi\uf9 colpite dalla pandemia: Lombardia, Emilia Romagna, Piemonte e Toscana. Sei sono i driver fondamentali su cui le Aziende Sanitarie hanno agito per rispondere alla crisi: i) la struttura organizzativa e i meccanismi operativi a supporto delle decisioni; ii) le reti ospedaliere per la gestione dei flussi dei pazienti; iii) l\u2019asset management e il lay out fisico; iv) la riorganizzazione dei flussi dei beni sanitari e dei dispositivi; v) le competenze dei professionisti; vi) le tecnologie. Dall\u2019analisi sono emerse 10 lezioni fondamentali da apprendere per la gestione delle operations, su cui basare la programmazione delle successive fasi della pandemia.Operations management is a central topic to address standardization issues, redesign of patient and medical supplies processes and flows with the aim of eliminating or reducing variability. This work aims to contribute to the debate on hospitals\u2019 ability to deal with the COVID-19 pandemic emergency. The experiences of seven healthcare organizations located in the most affected Italian regions were analyzed: Lombardy, Emilia Romagna, Piedmont and Tuscany. There are six fundamental drivers managed by the healthcare organizations to tackle the crisis: i) the organizational structure and decision support systems; ii) hospital networks for the management of patient flows; iii) asset management and physical lay out; iv) the redesign of medical supplies flows; v) the skills of professionals; vi) new health technologies. The analysis revealed 10 fundamental lessons to be learned for operations management, enabling the healthcare managers and professionals to plan the responses to the next phases of the pandemic

Characterization of the fecal microbiome in cats with inflammatory bowel disease or alimentary small cell lymphoma.

Feline chronic enteropathy (CE) is a common gastrointestinal disorder in cats and mainly comprises inflammatory bowel disease (IBD) and small cell lymphoma (SCL). Both IBD and SCL in cats share features with chronic enteropathies such as IBD and monomorphic epitheliotropic intestinal T-cell lymphoma in humans. The aim of this study was to characterize the fecal microbiome of 38 healthy cats and 27 cats with CE (13 cats with IBD and 14 cats with SCL). Alpha diversity indices were significantly decreased in cats with CE (OTU p = 0.003, Shannon Index p = 0.008, Phylogenetic Diversity p = 0.019). ANOSIM showed a significant difference in bacterial communities, albeit with a small effect size (P = 0.023, R = 0.073). Univariate analysis and LEfSE showed a lower abundance of facultative anaerobic taxa of the phyla Firmicutes (families Ruminococcaceae and Turicibacteraceae), Actinobacteria (genus Bifidobacterium) and Bacteroidetes (i.a. Bacteroides plebeius) in cats with CE. The facultative anaerobic taxa Enterobacteriaceae and Streptococcaceae were increased in cats with CE. No significant difference between the microbiome of cats with IBD and those with SCL was found. Cats with CE showed patterns of dysbiosis similar to those in found people with IBD