Improving health and well-being through community health champions: a thematic evaluation of a programme in Yorkshire and Humber.

AIMS: The contribution that lay people can make to the public health agenda is being increasingly recognised in research and policy literature. This paper examines the role of lay workers (referred to as 'community health champions') involved in community projects delivered by Altogether Better across Yorkshire and Humber. The aim of the paper is to describe key features of the community health champion approach and to examine the evidence that this type of intervention can have an impact on health. METHODS: A qualitative approach was taken to the evaluation, with two strands to gathering evidence: interviews conducted with different stakeholder groups including project leads, key partners from community and statutory sectors and community workers, plus two participatory workshops to gather the views of community health champions. Seven projects (from a possible 12) were identified to be involved in the evaluation. Those projects that allowed the evaluation team to explore fully the champion role (training, infrastructure, etc.) and how that works in practice as a mechanism for empowerment were selected. In total, 29 semi-structured interviews were conducted with project staff and partners, and 30 champions, varying in terms of age, gender, ethnicity and disability, took part in the workshops. RESULTS: Becoming a community health champion has health benefits such as increased self-esteem and confidence and improved well-being. For some champions, this was the start of a journey to other opportunities such as education or paid employment. There were many examples of the influence of champions extending to the wider community of family, friends and neighbours, including helping to support people to take part in community life. Champions recognised the value of connecting people through social networks, group activities, and linking people into services and the impact that that had on health and well-being. Project staff and partners also recognised that champions were promoting social cohesiveness and helping to integrate people into their community. CONCLUSIONS: The recent public health White Paper suggested that the Altogether Better programme is improving individual and community health as well as increasing social capital, voluntary activity and wider civic participation. This evaluation supports this statement and suggests that the community health champion role can be a catalyst for change for both individuals and communities

Improving the evidence base of Markov models used to estimate the costs of scaling up antiretroviral programmes in resource-limited settings

<p>Abstract</p> <p>Background</p> <p>Despite concerns about affordability and sustainability, many models of the lifetime costs of antiretroviral therapy (ART) used in resource limited settings are based on data from small research cohorts, together with pragmatic assumptions about life-expectancy. This paper revisits these modelling assumptions in order to provide input to future attempts to model the lifetime costs and the costs of scaling up ART.</p> <p>Methods</p> <p>We analysed the determinants of costs and outcomes in patients receiving ART in line with standard World Health Organization (WHO) guidelines for resource poor settings in a private sector managed ART programme in South Africa. The cohort included over 5,000 patients with up to 4 years (median 19 months) on ART. Generalized linear and Cox proportional hazards regression models were used to establish cost and outcome determinants respectively.</p> <p>Results</p> <p>The key variables associated with changes in mean monthly costs were: being on the second line regimen; receiving ART from 4 months prior to 4 months post treatment initiation; having a recent or current CD4 count <50 cells/µL or 50-199 cells/µl; having mean ART adherence <75% as determined by monthly pharmacy refill data; and having a current or recent viral load >100,000 copies/mL. In terms of the likelihood of dying, the key variables were: baseline CD4 count<50 cells/µl (particularly during the first 4 months on treatment); current CD4 count <50 cells/µl and 50-199 cells/µl (particularly during later periods on treatment); and being on the second line regimen. Being poorly adherent and having an unsuppressed viral load was also associated with a higher likelihood of dying.</p> <p>Conclusions</p> <p>While there are many unknowns associated with modelling the resources needed to scale-up ART, our analysis has suggested a number of key variables which can be used to improve the state of the art of modelling ART. While the magnitude of the effects associated with these variables would be likely to differ in other settings, the variables influencing costs and survival are likely to be generalizable. This is of direct relevance to those concerned about assessing the long-term costs and sustainability of expanded access to ART.</p

Automatic de-identification of textual documents in the electronic health record: a review of recent research

<p>Abstract</p> <p>Background</p> <p>In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here.</p> <p>Methods</p> <p>This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers.</p> <p>Results</p> <p>The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries.</p> <p>Conclusions</p> <p>In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication.</p

The interaction between a sexually transferred steroid hormone and a female protein regulates oogenesis in the malaria mosquito anopheles gambiae

Molecular interactions between male and female factors during mating profoundly affect the reproductive behavior and physiology of female insects. In natural populations of the malaria mosquito Anopheles gambiae, blood-fed females direct nutritional resources towards oogenesis only when inseminated. Here we show that the mating-dependent pathway of egg development in these mosquitoes is regulated by the interaction between the steroid hormone 20-hydroxy-ecdysone (20E) transferred by males during copulation and a female Mating-Induced Stimulator of Oogenesis (MISO) protein. RNAi silencing of MISO abolishes the increase in oogenesis caused by mating in blood-fed females, causes a delay in oocyte development, and impairs the function of male-transferred 20E. Co-immunoprecipitation experiments show that MISO and 20E interact in the female reproductive tract. Moreover MISO expression after mating is induced by 20E via the Ecdysone Receptor, demonstrating a close cooperation between the two factors. Male-transferred 20E therefore acts as a mating signal that females translate into an increased investment in egg development via a MISO-dependent pathway. The identification of this male–female reproductive interaction offers novel opportunities for the control of mosquito populations that transmit malaria

Acceptability of prison-based take-home naloxone programmes among a cohort of incarcerated men with a history of regular injecting drug use

Background: Take-home naloxone (THN) programmes are an evidence-based opioid overdose prevention initiative. Elevated opioid overdose risk following prison release means release from custody provides an ideal opportunity for THN initiatives. However, whether Australian prisoners would utilise such programmes is unknown. We examined the acceptability of THN in a cohort of male prisoners with histories of regular injecting drug use (IDU) in Victoria, Australia. Methods: The sample comprised 380 men from the Prison and Transition Health (PATH) Cohort Study; all of whom reported regular IDU in the 6 months prior to incarceration. We asked four questions regarding THN during the pre-release baseline interview, including whether participants would be willing to participate in prison-based THN. We describe responses to these questions along with relationships between before- and during-incarceration factors and willingness to participate in THN training prior to release from prison. Results: Most participants (81%) reported willingness to undertake THN training prior to release. Most were willing to resuscitate a friend using THN if they were trained (94%) and to be revived by a trained peer (91%) using THN. More than 10 years since first injection (adjusted odds ratio [AOR] 2.22, 95%CI 1.03-4.77), having witnessed an opioid overdose in the last 5 years (AOR 2.53, 95%CI 1.32-4.82), having ever received alcohol or other drug treatment in prison (AOR 2.41, 95%CI 1.14-5.07) and injecting drugs during the current prison sentence (AOR 4.45, 95%CI 1.73-11.43) were significantly associated with increased odds of willingness to participate in a prison THN programme. Not specifying whether they had injected during their prison sentence (AOR 0.37, 95%CI 0.18-0.77) was associated with decreased odds of willingness to participate in a prison THN training. Conclusion: Our findings suggest that male prisoners in Victoria with a history of regular IDU are overwhelmingly willing to participate in THN training prior to release. Factors associated with willingness to participate in prison THN programmes offer insights to help support the implementation and uptake of THN programmes to reduce opioid-overdose deaths in the post-release period

Developing a manually annotated clinical document corpus to identify phenotypic information for inflammatory bowel disease

<p>Abstract</p> <p>Background</p> <p>Natural Language Processing (NLP) systems can be used for specific Information Extraction (IE) tasks such as extracting phenotypic data from the electronic medical record (EMR). These data are useful for translational research and are often found only in free text clinical notes. A key required step for IE is the manual annotation of clinical corpora and the creation of a reference standard for (1) training and validation tasks and (2) to focus and clarify NLP system requirements. These tasks are time consuming, expensive, and require considerable effort on the part of human reviewers.</p> <p>Methods</p> <p>Using a set of clinical documents from the VA EMR for a particular use case of interest we identify specific challenges and present several opportunities for annotation tasks. We demonstrate specific methods using an open source annotation tool, a customized annotation schema, and a corpus of clinical documents for patients known to have a diagnosis of Inflammatory Bowel Disease (IBD). We report clinician annotator agreement at the document, concept, and concept attribute level. We estimate concept yield in terms of annotated concepts within specific note sections and document types.</p> <p>Results</p> <p>Annotator agreement at the document level for documents that contained concepts of interest for IBD using estimated Kappa statistic (95% CI) was very high at 0.87 (0.82, 0.93). At the concept level, F-measure ranged from 0.61 to 0.83. However, agreement varied greatly at the specific concept attribute level. For this particular use case (IBD), clinical documents producing the highest concept yield per document included GI clinic notes and primary care notes. Within the various types of notes, the highest concept yield was in sections representing patient assessment and history of presenting illness. Ancillary service documents and family history and plan note sections produced the lowest concept yield.</p> <p>Conclusion</p> <p>Challenges include defining and building appropriate annotation schemas, adequately training clinician annotators, and determining the appropriate level of information to be annotated. Opportunities include narrowing the focus of information extraction to use case specific note types and sections, especially in cases where NLP systems will be used to extract information from large repositories of electronic clinical note documents.</p

Towards a methodology for cluster searching to provide conceptual and contextual "richness" for systematic reviews of complex interventions: case study (CLUSTER)

Background Systematic review methodologies can be harnessed to help researchers to understand and explain how complex interventions may work. Typically, when reviewing complex interventions, a review team will seek to understand the theories that underpin an intervention and the specific context for that intervention. A single published report from a research project does not typically contain this required level of detail. A review team may find it more useful to examine a “study cluster”; a group of related papers that explore and explain various features of a single project and thus supply necessary detail relating to theory and/or context. We sought to conduct a preliminary investigation, from a single case study review, of techniques required to identify a cluster of related research reports, to document the yield from such methods, and to outline a systematic methodology for cluster searching. Methods In a systematic review of community engagement we identified a relevant project – the Gay Men’s Task Force. From a single “key pearl citation” we conducted a series of related searches to find contextually or theoretically proximate documents. We followed up Citations, traced Lead authors, identified Unpublished materials, searched Google Scholar, tracked Theories, undertook ancestry searching for Early examples and followed up Related projects (embodied in the CLUSTER mnemonic). Results Our structured, formalised procedure for cluster searching identified useful reports that are not typically identified from topic-based searches on bibliographic databases. Items previously rejected by an initial sift were subsequently found to inform our understanding of underpinning theory (for example Diffusion of Innovations Theory), context or both. Relevant material included book chapters, a Web-based process evaluation, and peer reviewed reports of projects sharing a common ancestry. We used these reports to understand the context for the intervention and to explore explanations for its relative lack of success. Additional data helped us to challenge simplistic assumptions on the homogeneity of the target population. Conclusions A single case study suggests the potential utility of cluster searching, particularly for reviews that depend on an understanding of context, e.g. realist synthesis. The methodology is transparent, explicit and reproducible. There is no reason to believe that cluster searching is not generalizable to other review topics. Further research should examine the contribution of the methodology beyond improved yield, to the final synthesis and interpretation, possibly by utilizing qualitative sensitivity analysis

Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at √s = 7 TeV with the ATLAS detector

This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of √s = 7 TeV;{\rm Te}{\rm V}$and correspond to an integrated luminosity of$4.6\;{\rm f}{{{\rm b}}^{-1}}$. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of-mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum${{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}$and pseudorapidity$|\eta |\lt 1.9$, is measured to be${{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente