Public Involvement in research within care homes: Benefits and challenges in the APPROACH Study

Public involvement in research (PIR) can improve research design and recruitment. Less is known about how PIR enhances the experience of participation and enriches the data collection process. In a study to evaluate how UK care homes and primary health care services achieve integrated working to promote older people’s health, PIR was integrated throughout the research processes. Objectives This paper aims to present one way in which PIR has been integrated into the design and delivery of a multi-site research study based in care homes. Design A prospective case study design, with an embedded qualitative evaluation of PIR activity. Setting and Participants Data collection was undertaken in six care homes in three sites in England. Six PIR members participated: all had prior personal or work experience in care homes. Data Collection Qualitative data collection involved discussion groups, and site-specific meetings to review experiences of participation, benefits and challenges, and completion of structured fieldwork notes after each care home visit. Results PIR members supported: recruitment, resident and staff interviews and participated in data interpretation. Benefits of PIR work were resident engagement that minimised distress and made best use of limited research resources. Challenges concerned communication and scheduling. Researcher support for PIR involvement was resource intensive. Discussion and Conclusions Clearly defined roles with identified training and support facilitated involvement in different aspectsPublic Involvement in Research members of the research team: Gail Capstick, Marion Cowie, Derek Hope, Rita Hewitt, Alex Mendoza, John Willmott. Also the involvement of Steven Iliffe and Heather Gag

Machine learning to refine decision making within a syndromic surveillance service

Background: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of public health importance. All alarms must be assessed to confirm whether they are of public health importance. In England, approximately 100 alarms are generated daily and, although their analysis is formalised through a risk assessment process, the process requires notable time, training, and maintenance of an expertise base to determine which alarms are of public health importance. The process is made more complicated by the observation that only 0.1% of statistical alarms are deemed to be of public health importance. Therefore, the aims of this study were to evaluate machine learning as a tool for computer-assisted human decision-making when assessing statistical alarms. Methods: A record of the risk assessment process was obtained from Public Health England for all 67505 statistical alarms between August 2013 and October 2015. This record contained information on the characteristics of the alarm (e.g. size, location). We used three Bayesian classifiers- naïve Bayes, tree-augmented naïve Bayes and Multinets - to examine the risk assessment record in England with respect to the final ‘Decision’ outcome made by an epidemiologist of ‘Alert’, ‘Monitor’ or ‘No-action’. Two further classifications based upon tree-augmented naïve Bayes and Multinets were implemented to account for the predominance of ‘No-action’ outcomes. Results: The attributes of each individual risk assessment were linked to the final decision made by an epidemiologist, providing confidence in the current process. The naïve Bayesian classifier performed best, correctly classifying 51.5% of ‘Alert’ outcomes. If the ‘Alert’ and ‘Monitor’ actions are combined then performance increases to 82.6% correctly classified. We demonstrate how a decision support system based upon a naïve Bayes classifier could be operationalised within an operational syndromic surveillance system. Conclusions: Within syndromic surveillance systems, machine learning techniques have the potential to make risk assessment following statistical alarms more automated, robust, and rigorous. However, our results also highlight the importance of specialist human input to the process

Using emergency department syndromic surveillance to investigate the impact of a national vaccination program: A retrospective observational study

BackgroundRotavirus infection is a common cause of gastroenteritis in children worldwide, with a high mortality burden in developing countries, particularly during the first two years of life. Rotavirus vaccination was introduced into the United Kingdom childhood vaccination schedule in July 2013, with high coverage (>90%) achieved by June 2016. We used an emergency department (ED) syndromic surveillance system to assess the impact of the rotavirus vaccination programme, specifically through the demonstration of any immediate and continuing impact on ED gastroenteritis visits in England.MethodsThis retrospective, observational study used syndromic surveillance data collected from 3 EDs in the two years before (July 2011-June 2013) and 3 years post (July 2013-June 2016) introduction of rotavirus vaccination. The weekly levels of ED visits for gastroenteritis (by age group and in total) during the period before rotavirus vaccination was first described alongside the findings of laboratory surveillance of rotavirus during the same period. An interrupted time-series analysis was then performed to demonstrate the impact of rotavirus vaccination introduction on gastroenteritis ED visit levels.ResultsDuring the two years before vaccine introduction ED visits for gastroenteritis in total and for the 0-4 years age group were seen to rise and fall in line with the seasonal rotavirus increases reported by laboratory surveillance. ED gastroenteritis visits by young children were lower in the three years following introduction of rotavirus vaccination (reduced from 8% of visits to 6% of visits). These attendance levels in young children (0-4years) remained higher than in older age groups, however the previously large seasonal increases in children were greatly reduced, from peaks of 16% to 3-10% of ED visits per week.ConclusionsED syndromic surveillance demonstrated a reduction in gastroenteritis visits following rotavirus vaccine introduction. This work establishes ED syndromic surveillance as a platform for rapid impact assessment of future vaccine programmes

Retrospective Observational Study of Atypical Winter Respiratory Illness Season Using Real-Time Syndromic Surveillance, England, 2014-15

During winter 2014–15, England experienced severe strains on acute health services. We investigated whether syndromic surveillance could contribute to understanding of the unusually high level of healthcare needs. We compared trends for several respiratory syndromic indicators from that winter to historical baselines. Cumulative and mean incidence rates were compared by winter and age group. All-age influenza-like illness was at expected levels; however, severe asthma and pneumonia levels were above those expected. Across several respiratory indicators, cumulative incidence rates during 2014–15 were similar to those of previous years, but higher for older persons; we saw increased rates of acute respiratory disease, including influenza like illness, severe asthma, and pneumonia, in the 65–74- and >75-year age groups. Age group–specific statistical algorithms may provide insights into the burden on health services and improve early warning in future winters

A Methodological Framework for the Evaluation of Syndromic Surveillance Systems: A Case Study of England

Background: Syndromic surveillance complements traditional public health surveillance by collecting and analysing health indicators in near real time. The rationale of syndromic surveillance is that it may detect health threats faster than traditional surveillance systems permitting more timely, and hence potentially more effective public health action. The effectiveness of syndromic surveillance largely relies on the methods used to detect aberrations. Very few studies have evaluated the performance of syndromic surveillance systems and consequently little is known about the types of events that such systems can and cannot detect. Methods: We introduce a framework for the evaluation of syndromic surveillance systems that can be used in any setting based upon the use of simulated scenarios. For a range of scenarios this allows the time and probability of to be determined and uncertainty is fully incorporated. In addition, we demonstrate how such a framework can model the benefits of increases in the number of centres reporting syndromic data and also determine the minimum size of outbreaks that can or cannot be detected. Here, we demonstrate its utility using simulations of national influenza outbreaks and localised outbreaks of cryptosporidiosis. Results: Influenza outbreaks are consistently detected with larger outbreaks being detected in a more timely manner. Small cryptosporidiosis outbreaks (<1000 symptomatic individuals) are unlikely to be detected. We also demonstrate the advantages of having multiple syndromic data streams (e.g. emergency attendance data, telephone helpline data, general practice consultation data) as different streams are able to detect different types outbreaks with different efficacy (e.g. emergency attendance data are useful for the detection of pandemic influenza but not for outbreaks of cryptosporidiosis). We also highlight that for any one disease, the utility of data streams may vary geographically, and that the detection ability of syndromic surveillance varies seasonally (e.g. an influenza outbreak starting in July is detected sooner than one starting later in the year). We argue that our framework constitutes a useful tool for public health emergency preparedness in multiple settings. Conclusions: The proposed framework allows the exhaustive evaluation of any syndromic surveillance system and constitutes a useful tool for emergency preparedness and response

The influence of a major sporting event upon emergency department attendances; A retrospective cross-national European study

Major sporting events may influence attendance levels at hospital emergency departments (ED). Previous research has focussed on the impact of single games, or wins/losses for specific teams/countries, limiting wider generalisations. Here we explore the impact of the Euro 2016 football championships on ED attendances across four participating nations (England, France, Northern Ireland, Wales), using a single methodology. Match days were found to have no significant impact upon daily ED attendances levels. Focussing upon hourly attendances, ED attendances across all countries in the four hour pre-match period were statistically significantly lower than would be expected (OR 0.97, 95% CI 0.94–0.99) and further reduced during matches (OR 0.94, 95% CI 0.91–0.97). In the 4 hour post-match period there was no significant increase in attendances (OR 1.01, 95% CI 0.99–1.04). However, these impacts were highly variable between individual matches: for example in the 4 hour period following the final, involving France, the number of ED attendances in France increased significantly (OR 1.27, 95% CI 1.13–1.42). Overall our results indicate relatively small impacts of major sporting events upon ED attendances. The heterogeneity observed makes it difficult for health providers to predict how major sporting events may affect ED attendances but supports the future development of compatible systems in different countries to support cross-border public health surveillance

Administering anticipatory medications in end-of-life care: A qualitative study of nursing practice in the community and in nursing homes

Background: In the United Kingdom, an approach to improving end-of-life care has been the introduction of ‘just in case’ or ‘anticipatory’ medications. Nurses are often responsible for deciding when to use anticipatory medications, but little is known about their experiences. Aim: To examine nurses’ decisions, aims and concerns when using anticipatory medications. Design: An ethnographic study in two UK regions, using observations and interviews with nurses working in community and nursing home teams (n = 8). Findings: Observations (n = 83) and interviews (n = 61) with community nurses. Nurses identified four ‘conditions’ that needed to be established before they implemented anticipatory medications: (1) irreversibility; (2) inability to take oral medication; (3) where the patient was able, they should consent and (4) decision had to be independent of demands or requests from patient’s relatives. By using anticipation medications, nurses sought to enable patients to be ‘comfortable and settled’ by provision of gradual relief of symptoms at the lowest dose possible. They aimed to respond quickly to needs, seeking to avoid hospital admission or medical call-out, while adhering to local prescribing policies. Worries included distinguishing between pain and agitation, balancing risks of under- and over-medication and the possibility of hastening death. Conclusion: Nurses take a leading role in the administration of anticipatory medications. Nurses apply consideration and caution to the administration of anticipatory medications but some experience emotional burden. Education, training and experience played a role in the nurses’ confidence and should continue to be central to efforts to improving the quality of palliative care in the community and nursing homes

Overview of the Far Ultraviolet Spectroscopic Explorer Mission

The Far Ultraviolet Spectroscopic Explorer satellite observes light in the far-ultraviolet spectral region, 905 - 1187 A with high spectral resolution. The instrument consists of four coaligned prime-focus telescopes and Rowland spectrographs with microchannel plate detectors. Two of the telescope channels use Al:LiF coatings for optimum reflectivity from approximately 1000 to 1187 A and the other two use SiC coatings for optimized throughput between 905 and 1105 A. The gratings are holographically ruled to largely correct for astigmatism and to minimize scattered light. The microchannel plate detectors have KBr photocathodes and use photon counting to achieve good quantum efficiency with low background signal. The sensitivity is sufficient to examine reddened lines of sight within the Milky Way as well as active galactic nuclei and QSOs for absorption line studies of both Milky Way and extra-galactic gas clouds. This spectral region contains a number of key scientific diagnostics, including O VI, H I, D I and the strong electronic transitions of H2 and HD.Comment: To appear in FUSE special issue of the Astrophysical Journal Letters. 6 pages + 4 figure

A core outcome set for nonpharmacological community-based interventions for people living with dementia at home: A systematic review of outcome measurement instruments

YesIt is questionable whether existing outcome measurement instruments (OMIs) in dementia research reflect what key stakeholders' value. We attained consensus from over 300 key stakeholders, including people living with dementia, and identified 13 core outcome items for use in nonpharmacological and community-based interventions for people with dementia living at home. In this systematic review we review OMIs that have previously been used in dementia care research to determine how, or even if, the 13 core outcome items can be measured. We extracted self-reported OMIs from trials, reviews and reports of instrument development. Searches were undertaken in the ALOIS database, Medline, PsycINFO, CINAHL, socINDEX and COSMIN database. We aimed to assess the psychometric properties of OMI items for face validity with the core outcome items, content validity, internal consistency and responsiveness. We held a co-research workshop involving people living with dementia and care partners in order to ratify the findings. In total 347 OMIs were located from 354 sources. Of these 76 OMIs met the inclusion criteria. No OMIs were deemed to have sufficient face validity for the COS items, and no OMIs proceeded to further assessment. The 'best' available OMI is the Engagement and Independence in Dementia Questionnaire (EID-Q). This study provides a practical resource for those designing dementia research trials. Being able to measure the COS items would herald a paradigm shift for dementia research, be responsive to what key stakeholders value and enhance the ability to make comparisons.This study was funded jointly by the Economic and Social Research Council (ESRC) and the National Institute for Health Research (NIHR). ESRC is part of UK Research and Innovation (UKRI)