PREVENTION OF AVIAN INFLUENZA EPIDEMIC : WHAT POLICY SHOULD WE CHOOSE?

Joint Research on Environmental Science and Technology for the Eart

Making sense of evidence in management decisions: the role of research-based knowledge on innovation adoption and implementation in health care

Background: Although innovation can improve patient care, implementing new ideas is often challenging. Previous research found that professional attitudes, shaped in part by health policies and organisational cultures, contribute to differing perceptions of innovation ‘evidence’. However, we still know little about how evidence is empirically accessed and used by organisational decision-makers when innovations are introduced. Aims and objectives: We aimed to investigate the use of different sources and types of evidence in innovation decisions to answer the following questions: how do managers make sense of evidence? What role does evidence play in management decision-making when adopting and implementing innovations in health care? How do wider contextual conditions and intraorganisational capacity influence research use and application by health-care managers? Methods: Our research design comprised multiple case studies with mixed methods. We investigated technology adoption and implementation in nine acute-care organisations across England. We employed structured survey questionnaires, in-depth interviews and documentary analysis. The empirical setting was infection prevention and control. Phase 1 focused on the espoused use of evidence by 126 non-clinical and clinical hybrid managers. Phase 2 explored the use of evidence by managers in specific technology examples: (1) considered for adoption; (2) successfully adopted and implemented; and (3) rejected or discontinued. Findings: (1) Access to, and use of, evidence types and sources varied greatly by profession. Clinicians reported a strong preference for science-based, peer-reviewed, published evidence. All groups called upon experiential knowledge and expert opinion. Nurses overall drew upon a wider range of evidence sources and types. Non-clinical managers tended to sequentially prioritise evidence on cost from national-level sources, and local implementation trials. (2) A sizeable proportion of professionals from all groups, including experienced staff, reported difficulty in making sense of evidence. Lack of awareness of existing implementation literature, lack of knowledge on how to translate information into current practice, and lack of time and relevant skills were reported as key reasons for this. (3) Infection outbreaks, financial pressures, performance targets and trusted relationships with suppliers seemed to emphasise a pragmatic and less rigorous approach in sourcing for evidence. Trust infrastructure redevelopment projects, and a strong emphasis on patient safety and collaboration, appeared to widen scope for evidence use. (4) Evidence was continuously interpreted and (re)constructed by professional identity, organisational role, team membership, audience and organisational goals. (5) Doctors and non-clinical managers sourced evidence plausible to self. Nursing staff also sought acceptance of evidence from other groups. (6) We found diverse ‘evidence templates’ in use: ‘biomedical-scientific’, ‘practice-based’, ‘rational-policy’. These represented shared cognitive models which defined what constituted acceptable and credible evidence in decisions. Nurses drew on all diverse ‘templates’ to make sense of evidence and problems; non-clinical managers drew mainly on the practice-based and rational-policy templates; and doctors drew primarily on the biomedical-scientific template. Conclusions: An evidence-based management approach that inflexibly applies the principles of evidence-based medicine, our findings suggest, neglects how evidence is actioned in practice and how codified research knowledge inter-relates with other ‘evidence’ also valued by decision-makers. Local processes and professional and microsystem considerations played a significant role in adoption and implementation. This has substantial implications for the effectiveness of large-scale projects and systems-wide policy

Serious electronic games as behavioural change interventions in healthcare-associated infections and infection prevention and control: a scoping review of the literature and future directions

Background The uptake of improvement initiatives in infection prevention and control (IPC) has often proven challenging. Innovative interventions such as ‘serious games’ have been proposed in other areas to educate and help clinicians adopt optimal behaviours. There is limited evidence about the application and evaluation of serious games in IPC. The purposes of the study were: a) to synthesise research evidence on the use of serious games in IPC to support healthcare workers’ behaviour change and best practice learning; and b) to identify gaps across the formulation and evaluation of serious games in IPC. Methods A scoping study was conducted using the methodological framework developed by Arksey and O’Malley. We interrogated electronic databases (Ovid MEDLINE, Embase Classic + Embase, PsycINFO, Scopus, Cochrane, Google Scholar) in December 2015. Evidence from these studies was assessed against an analytic framework of intervention formulation and evaluation. Results Nine hundred sixty five unique papers were initially identified, 23 included for full-text review, and four finally selected. Studies focused on intervention inception and development rather than implementation. Expert involvement in game design was reported in 2/4 studies. Potential game users were not included in needs assessment and game development. Outcome variables such as fidelity or sustainability were scarcely reported. Conclusions The growing interest in serious games for health has not been coupled with adequate evaluation of processes, outcomes and contexts involved. Explanations about the mechanisms by which game components may facilitate behaviour change are lacking, further hindering adoption

Code-Sharing in Cost-of-Illness Calculations: An Application to Antibiotic-Resistant Bloodstream Infections

Data Availability Statement: The linked JANIS-DPC dataset analyzed for this study is not fully available due to patient identifiable data being present. However, JANIS does provide surveillance data in its open report available. Requests to access the datasets should be directed to https://janis.mhlw.go.jp/english/about/index.html.Copyright © 2020 Naylor, Yamashita, Iwami, Kunisawa, Mizuno, Castro-Sánchez, Imanaka, Ahmad and Holmes. Background: More data-driven evidence is needed on the cost of antibiotic resistance. Both Japan and England have large surveillance and administrative datasets. Code sharing of costing models enables reduced duplication of effort in research. Objective: To estimate the burden of antibiotic-resistant Staphylococcus aureus bloodstream infections (BSIs) in Japan, utilizing code that was written to estimate the hospital burden of antibiotic-resistant Escherichia coli BSIs in England. Additionally, the process in which the code-sharing and application was performed is detailed, to aid future such use of code-sharing in health economics. Methods: National administrative data sources were linked with voluntary surveillance data within the Japan case study. R software code, which created multistate models to estimate the excess length of stay associated with different exposures of interest, was adapted from previous use and run on this dataset. Unit costs were applied to estimate healthcare system burden in 2017 international dollars (I$). Results: Clear supporting documentation alongside open-access code, licensing, and formal communication channels, helped the re-application of costing code from the English setting within the Japanese setting. From the Japanese healthcare system perspective, it was estimated that there was an excess cost of I$6,392 per S. aureus BSI, whilst oxacillin resistance was associated with an additional I$8,155. Conclusions: S. aureus resistance profiles other than methicillin may substantially impact hospital costs. The sharing of costing models within the field of antibiotic resistance is a feasible way to increase burden evidence efficiently, allowing for decision makers (with appropriate data available) to gain rapid cost-of-illness estimates.HPRU-2012-1004

Code-sharing in Cost-of-illness Calculations: An Application to Antibiotic-Resistant Bloodstream Infections

Background: More data-driven evidence is needed on the cost of antibiotic resistance. Both Japan and England have large surveillance and administrative datasets. Code sharing of costing models enables reduced duplication of effort in research. Objective: To estimate the burden of antibiotic-resistant Staphylococcus aureus bloodstream infections (BSIs) in Japan, utilizing code that was written to estimate the hospital burden of antibiotic-resistant Escherichia coli BSIs in England. Additionally, the process in which the code-sharing and application was performed is detailed, to aid future such use of code-sharing in health economics. Methods: National administrative data sources were linked with voluntary surveillance data within the Japan case study. R software code, which created multistate models to estimate the excess length of stay associated with different exposures of interest, was adapted from previous use and run on this dataset. Unit costs were applied to estimate healthcare system burden in 2017 international dollars (I$). Results: Clear supporting documentation alongside open-access code, licensing and formal communication channels, helped the re-application of costing code from the English setting within the Japanese setting. From the Japanese healthcare system perspective, it was estimated that there was an excess cost of I$6,392 per S. aureus BSI, whilst oxacillin resistance was associated with an additional I$8,155. Conclusions: S. aureus resistance profiles other than methicillin may substantially impact hospital costs. The sharing of costing models within the field of antibiotic resistance is a feasible way to increase burden evidence efficiently, allowing for decision makers (with appropriate data available) to gain rapid cost-of-illness estimates

Comparison of national strategies to reduce methicillin-resistant Staphylococcus aureus (MRSA) infections in Japan and England

Background National responses to healthcare-associated infections vary between high-income countries but when analysed for contextual comparability, interventions can be assessed for transferability. Aim To identify learning from country-level approaches to addressing meticillin-resistant Staphylococcus aureus (MRSA) in Japan and England. Methods A longitudinal analysis (2000-17), comparing epidemiological trends and policy interventions. Data from 441 textual sources concerning infection prevention and control (IPC), surveillance, and antimicrobial stewardship interventions were systematically coded for: type - mandatory requirements, recommendations, or national campaigns; method - restrictive, persuasive, structural in nature; level of implementation - macro (national), meso (organisational), micro (individual) levels. Healthcare organisational structures and role of media were also assessed. Findings In England significant reduction has been achieved in number of reported MRSA bloodstream infections. In Japan, in spite of reductions, MRSA remains a predominant infection. Both countries face new threats in the emergence of drug-resistant Escherichia coli. England has focused on national mandatory and structural interventions, supported by a combination of outcomes-based incentives and punitive mechanisms, and multidisciplinary IPC hospital teams. Japan has focused on (non-mandatory) recommendations and primarily persuasive interventions, supported by process-based incentives, with voluntary surveillance. Areas for development in Japan include resourcing of dedicated data management support and implementation of national campaigns for healthcare professionals and the public. Conclusion Policy interventions need to be relevant to local epidemiological trends, while acceptable within health system cultures and public expectations. Cross-national learning can help inform the right mix of interventions to create sustainable and resilient systems for future infection and economic challenges

Healthy Campus Trial: A multiphase optimization strategy (MOST) fully factorial trial to optimize the smartphone cognitive behavioral therapy (CBT) app for mental health promotion among university students: Study protocol for a randomized controlled trial

This is the final version. Available from the publisher via the DOI in this record.After the publication of the primary findings, the de-identified and completely anonymized individual participant-level dataset will be posted on the UMIN-ICDR website (http://www.umin.ac.jp/icdr/index-j.html) so that it can be accessed by qualified researchers.Background: Youth in general and college life in particular are characterized by new educational, vocational, and interpersonal challenges, opportunities, and substantial stress. It is estimated that 30-50% of university students meet criteria for some mental disorder, especially depression, in any given year. The university has traditionally provided many channels to promote students' mental health, but until now only a minority have sought such help, possibly owing to lack of time and/or to stigma related to mental illness. Smartphone-delivered cognitive behavioral therapy (CBT) shows promise for its accessibility and effectiveness. However, its most effective components and for whom it is more (or less) effective are not known. Methods/design: Based on the multiphase optimization strategy framework, this study is a parallel-group, multicenter, open, fully factorial trial examining five smartphone-delivered CBT components (self-monitoring, cognitive restructuring, behavioral activation, assertion training, and problem solving) among university students with elevated distress, defined as scoring 5 or more on the Patient Health Questionnaire-9 (PHQ-9). The primary outcome is change in PHQ-9 scores from baseline to week 8. We will estimate specific efficacy of the five components and their interactions through the mixed-effects repeated-measures analysis and propose the most effective and efficacious combinations of components. Effect modification by selected baseline characteristics will be examined in exploratory analyses. Discussion: The highly efficient experimental design will allow identification of the most effective components and the most efficient combinations thereof among the five components of smartphone CBT for university students. Pragmatically, the findings will help make the most efficacious CBT package accessible to a large number of distressed university students at reduced cost; theoretically, they will shed light on the underlying mechanisms of CBT and help further advance CBT for depression

The impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants

Introduction: A key feature of the COVID-19 pandemic has been the emergence of SARS-CoV-2 variants with different transmission characteristics. However, when a novel variant arrives in a host population, it will not necessarily lead to many cases. Instead, it may fade out, due to stochastic effects and the level of immunity in the population. Immunity against novel SARS-CoV-2 variants may be influenced by prior exposures to related viruses, such as other SARS-CoV-2 variants and seasonal coronaviruses, and the level of cross-reactive immunity conferred by those exposures. Methods: Here, we investigate the impact of cross-reactive immunity on the emergence of SARS-CoV-2 variants in a simplified scenario in which a novel SARS-CoV-2 variant is introduced after an antigenically related virus has spread in the population. We use mathematical modelling to explore the risk that the novel variant invades the population and causes a large number of cases, as opposed to fading out with few cases. Results: We find that, if cross-reactive immunity is complete (i.e. someone infected by the previously circulating virus is not susceptible to the novel variant), the novel variant must be more transmissible than the previous virus to invade the population. However, in a more realistic scenario in which cross-reactive immunity is partial, we show that it is possible for novel variants to invade, even if they are less transmissible than previously circulating viruses. This is because partial cross-reactive immunity effectively increases the pool of susceptible hosts that are available to the novel variant compared to complete cross-reactive immunity. Furthermore, if previous infection with the antigenically related virus assists the establishment of infection with the novel variant, as has been proposed following some experimental studies, then even variants with very limited transmissibility are able to invade the host population. Discussion: Our results highlight that fast assessment of the level of cross-reactive immunity conferred by related viruses against novel SARS-CoV-2 variants is an essential component of novel variant risk assessments