How to Cost the Implementation of Major System Change for Economic Evaluations: Case Study Using Reconfigurations of Specialist Cancer Surgery in Part of London, England.

BACKGROUND: Studies have been published regarding the impact of major system change (MSC) on care quality and outcomes, but few evaluate implementation costs or include them in cost-effectiveness analysis (CEA). This is despite large potential costs of MSC: change planning, purchasing or repurposing assets, and staff time. Implementation costs can influence implementation decisions. We describe our framework and principles for costing MSC implementation and illustrate them using a case study. METHODS: We outlined MSC implementation stages and identified components, using a framework conceived during our work on MSC in stroke services. We present a case study of MSC of specialist surgery services for prostate, bladder, renal and oesophagogastric cancers, focusing on North Central and North East London and West Essex. Health economists collaborated with qualitative researchers, clinicians and managers, identifying key reconfiguration stages and expenditures. Data sources (n = approximately 100) included meeting minutes, interviews, and business cases. National Health Service (NHS) finance and service managers and clinicians were consulted. Using bottom-up costing, items were identified, and unit costs based on salaries, asset costs and consultancy fees assigned. Itemised costs were adjusted and summed. RESULTS: Cost components included options appraisal, bidding process, external review; stakeholder engagement events; planning/monitoring boards/meetings; and making the change: new assets, facilities, posts. Other considerations included hospital tariff changes; costs to patients; patient population; and lifetime of changes. Using the framework facilitated data identification and collection. The total adjusted implementation cost was estimated at £7.2 million, broken down as replacing robots (£4.0 million), consultancy fees (£1.9 million), staff time costs (£1.1 million) and other costs (£0.2 million). CONCLUSIONS: These principles can be used by funders, service providers and commissioners planning MSC and researchers evaluating MSC. Health economists should be involved early, alongside qualitative and health-service colleagues, as retrospective capture risks information loss. These analyses are challenging; many cost factors are difficult to identify, access and measure, and assumptions regarding lifetime of the changes are important. Including implementation costs in CEA might make MSC appear less cost effective, influencing future decisions. Future work will incorporate this implementation cost into the full CEAs of the London Cancer MSC. TRIAL REGISTRATION: Not applicable

An Investigation into the Poor Survival of an Endangered Coho Salmon Population

To investigate reasons for the decline of an endangered population of coho salmon (O. kisutch), 190 smolts were acoustically tagged during three consecutive years and their movements and survival were estimated using the Pacific Ocean Shelf Tracking project (POST) array. Median travel times of the Thompson River coho salmon smolts to the lower Fraser River sub-array were 16, 12 and 10 days during 2004, 2005 and 2006, respectively. Few smolts were recorded on marine arrays. Freshwater survival rates of the tagged smolts during their downstream migration were 0.0–5.6% (0.0–9.0% s.e.) in 2004, 7.0% (6.2% s.e.) in 2005, and 50.9% (18.6% s.e.) in 2006. Overall smolt-to-adult return rates exhibited a similar pattern, which suggests that low freshwater survival rates of out-migrating smolts may be a primary reason for the poor conservation status of this endangered coho salmon population

Differential Ligand Binding to a Human Cytomegalovirus Chemokine Receptor Determines Cell Type–Specific Motility

While most chemokine receptors fail to cross the chemokine class boundary with respect to the ligands that they bind, the human cytomegalovirus (HCMV)-encoded chemokine receptor US28 binds multiple CC-chemokines and the CX3C-chemokine Fractalkine. US28 binding to CC-chemokines is both necessary and sufficient to induce vascular smooth muscle cell (SMC) migration in response to HCMV infection. However, the function of Fractalkine binding to US28 is unknown. In this report, we demonstrate that Fractalkine binding to US28 not only induces migration of macrophages but also acts to inhibit RANTES-mediated SMC migration. Similarly, RANTES inhibits Fractalkine-mediated US28 migration in macrophages. While US28 binding of both RANTES and Fractalkine activate FAK and ERK-1/2, RANTES signals through Gα12 and Fractalkine through Gαq. These findings represent the first example of differential chemotactic signaling via a multiple chemokine family binding receptor that results in migration of two different cell types. Additionally, the demonstration that US28-mediated chemotaxis is both ligand-specific and cell type–specific has important implications in the role of US28 in HCMV pathogenesis

A Synthesis of Tagging Studies Examining the Behaviour and Survival of Anadromous Salmonids in Marine Environments

This paper synthesizes tagging studies to highlight the current state of knowledge concerning the behaviour and survival of anadromous salmonids in the marine environment. Scientific literature was reviewed to quantify the number and type of studies that have investigated behaviour and survival of anadromous forms of Pacific salmon (Oncorhynchus spp.), Atlantic salmon (Salmo salar), brown trout (Salmo trutta), steelhead (Oncorhynchus mykiss), and cutthroat trout (Oncorhynchus clarkii). We examined three categories of tags including electronic (e.g. acoustic, radio, archival), passive (e.g. external marks, Carlin, coded wire, passive integrated transponder [PIT]), and biological (e.g. otolith, genetic, scale, parasites). Based on 207 papers, survival rates and behaviour in marine environments were found to be extremely variable spatially and temporally, with some of the most influential factors being temperature, population, physiological state, and fish size. Salmonids at all life stages were consistently found to swim at an average speed of approximately one body length per second, which likely corresponds with the speed at which transport costs are minimal. We found that there is relatively little research conducted on open-ocean migrating salmonids, and some species (e.g. masu [O. masou] and amago [O. rhodurus]) are underrepresented in the literature. The most common forms of tagging used across life stages were various forms of external tags, coded wire tags, and acoustic tags, however, the majority of studies did not measure tagging/handling effects on the fish, tag loss/failure, or tag detection probabilities when estimating survival. Through the interdisciplinary application of existing and novel technologies, future research examining the behaviour and survival of anadromous salmonids could incorporate important drivers such as oceanography, tagging/handling effects, predation, and physiology

Measurement of the electron reconstruction efficiency at LHCb

The single electron track-reconstruction efficiency is calibrated using a sample corresponding to 1.3 fb−1 of pp collision data recorded with the LHCb detector in 2017. This measurement exploits B+→ J/ψ(e+e−)K+ decays, where one of the electrons is fully reconstructed and paired with the kaon, while the other electron is reconstructed using only the information of the vertex detector. Despite this partial reconstruction, kinematic and geometric constraints allow the B meson mass to be reconstructed and the signal to be well separated from backgrounds. This in turn allows the electron reconstruction efficiency to be measured by matching the partial track segment found in the vertex detector to tracks found by LHCb's regular reconstruction algorithms. The agreement between data and simulation is evaluated, and corrections are derived for simulated electrons in bins of kinematics. These correction factors allow LHCb to measure branching fractions involving single electrons with a systematic uncertainty below 1%