The implementation of intentional rounding using participatory action research

Author version made available according to Publisher copyright policy.‘Intentional’/’hourly rounding’ is defined as regular checks of individual patients carried out by health professionals at set intervals, rather than a response to a summons via a call bell. Intentional rounding places patients at the heart of the ward routine including the acknowledgement of patient preferences and in anticipation of their needs. The aim of this study was to implement intentional rounding using Participatory Action Research to increase patient care, increase staff productivity and the satisfaction of care provision from both patients and staff. Outcomes of the study revealed a drop in call bell use, no observable threats to patient safety, nursing staff and patient satisfaction with care provision. However, any future studies should consider staff skill mix issues, including the needs of newly graduated nursing staff as well as the cognitive status of patients when implementing intentional rounding on acute care wards

Pyxel 1.0: an open source Python framework for detector and end-to-end instrument simulation

Detector modeling is becoming more and more critical for the development of new instruments in scientific space missions and ground-based experiments. Modeling tools are often developed from scratch by each individual project and not necessarily shared for reuse by a wider community. To foster knowledge transfer, reusability, and reliability in the instrumentation community, we developed Pyxel, a framework for the simulation of scientific detectors and instruments. Pyxel is an open-source and collaborative project, based on Python, developed as an easy-to-use tool that can host and pipeline any kind of detector effect model. Recently, Pyxel has achieved a new milestone: the public release and launch of version 1.0, which simplified third-party contributions and improved ease of use even further. Since its launch, Pyxel has been experiencing a growing user community and is being used to simulate a variety of detectors. We give a tour of Pyxel’s version 1.0 changes and new features, including a new interface, parallel computing, and new detectors and models. We continue with an example of using Pyxel as a tool for model optimization and calibration. Finally, we describe an example of how Pyxel and its features can be used to develop a full-scale end-to-end instrument simulator

Statistical Analysis of Molecular Signal Recording

A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed a “molecular ticker tape”, in which an engineered DNA polymerase (DNAP) writes time-varying signals into DNA in the form of nucleotide misincorporation patterns. Here, we define a theoretical framework quantifying the expected capabilities of molecular ticker tapes as a function of experimental parameters. We present a decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters, directly from misincorporation rates as determined by sequencing. We explore the requirements for accurate signal decoding, particularly the constraints on (1) the polymerase biochemical parameters, and (2) the amplitude, temporal resolution, and duration of the time-varying input signals. Our results suggest that molecular recording devices with kinetic properties similar to natural polymerases could be used to perform experiments in which neural activity is compared across several experimental conditions, and that devices engineered by combining favorable biochemical properties from multiple known polymerases could potentially measure faster phenomena such as slow synchronization of neuronal oscillations. Sophisticated engineering of DNAPs is likely required to achieve molecular recording of neuronal activity with single-spike temporal resolution over experimentally relevant timescales.United States. Defense Advanced Research Projects Agency. Living Foundries ProgramGoogle (Firm)New York Stem Cell Foundation. Robertson Neuroscience Investigator AwardNational Institutes of Health (U.S.) (EUREKA Award 1R01NS075421)National Institutes of Health (U.S.) (Transformative R01 1R01GM104948)National Institutes of Health (U.S.) (Single Cell Grant 1 R01 EY023173)National Institutes of Health (U.S.) (Grant 1R01DA029639)National Institutes of Health (U.S.) (Grant 1R01NS067199)National Science Foundation (U.S.) (CAREER Award CBET 1053233)National Science Foundation (U.S.) (Grant EFRI0835878)National Science Foundation (U.S.) (Grant DMS1042134)Paul G. Allen Family Foundation (Distinguished Investigator in Neuroscience Award

Identifying paediatric nursing-sensitive outcomes in linked administrative health data

There is increasing interest in the contribution of the quality of nursing care to patient outcomes. Due to different casemix and risk profiles, algorithms for administrative health data that identify nursing-sensitive outcomes in adult hospitalised patients may not be applicable to paediatric patients. The study purpose was to test adult algorithms in a paediatric hospital population and make amendments to increase the accuracy of identification of hospital acquitted events. The study also aimed to determine whether the use of linked hospital records improved the likelihood of correctly identifying patient outcomes as nursing sensitive rather than being related to their pre-morbid conditions. Algorithm for nursing-sensitive outcomes used in adult populations have to be amended before application to paediatric populations. Using unlinked individual hospitalisation records to estimate rates of nursing-sensitive outcomes is likely to result in inaccurate rates

Functionality and feedback: a realist synthesis of the collation, interpretation and utilisation of patient-reported outcome measures data to improve patient care

Background: The feedback of patient-reported outcome measures (PROMs) data is intended to support the care of individual patients and to act as a quality improvement (QI) strategy. Objectives: To (1) identify the ideas and assumptions underlying how individual and aggregated PROMs data are intended to improve patient care, and (2) review the evidence to examine the circumstances in which and processes through which PROMs feedback improves patient care. Design: Two separate but related realist syntheses: (1) feedback of aggregate PROMs and performance data to improve patient care, and (2) feedback of individual PROMs data to improve patient care. Interventions: Aggregate – feedback and public reporting of PROMs, patient experience data and performance data to hospital providers and primary care organisations. Individual – feedback of PROMs in oncology, palliative care and the care of people with mental health problems in primary and secondary care settings. Main outcome measures: Aggregate – providers’ responses, attitudes and experiences of using PROMs and performance data to improve patient care. Individual – providers’ and patients’ experiences of using PROMs data to raise issues with clinicians, change clinicians’ communication practices, change patient management and improve patient well-being. Data sources: Searches of electronic databases and forwards and backwards citation tracking. Review methods: Realist synthesis to identify, test and refine programme theories about when, how and why PROMs feedback leads to improvements in patient care. Results: Providers were more likely to take steps to improve patient care in response to the feedback and public reporting of aggregate PROMs and performance data if they perceived that these data were credible, were aimed at improving patient care, and were timely and provided a clear indication of the source of the problem. However, implementing substantial and sustainable improvement to patient care required system-wide approaches. In the care of individual patients, PROMs function more as a tool to support patients in raising issues with clinicians than they do in substantially changing clinicians’ communication practices with patients. Patients valued both standardised and individualised PROMs as a tool to raise issues, but thought is required as to which patients may benefit and which may not. In settings such as palliative care and psychotherapy, clinicians viewed individualised PROMs as useful to build rapport and support the therapeutic process. PROMs feedback did not substantially shift clinicians’ communication practices or focus discussion on psychosocial issues; this required a shift in clinicians’ perceptions of their remit. Strengths and limitations: There was a paucity of research examining the feedback of aggregate PROMs data to providers, and we drew on evidence from interventions with similar programme theories (other forms of performance data) to test our theories. Conclusions: PROMs data act as ‘tin openers’ rather than ‘dials’. Providers need more support and guidance on how to collect their own internal data, how to rule out alternative explanations for their outlier status and how to explore the possible causes of their outlier status. There is also tension between PROMs as a QI strategy versus their use in the care of individual patients; PROMs that clinicians find useful in assessing patients, such as individualised measures, are not useful as indicators of service quality. Future work: Future research should (1) explore how differently performing providers have responded to aggregate PROMs feedback, and how organisations have collected PROMs data both for individual patient care and to improve service quality; and (2) explore whether or not and how incorporating PROMs into patients’ electronic records allows multiple different clinicians to receive PROMs feedback, discuss it with patients and act on the data to improve patient care

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

fisheries and tourism social economic and ecological trade offs in coral reef systems

Coastal communities are exerting increasingly more pressure on coral reef ecosystem services in the Anthropocene. Balancing trade-offs between local economic demands, preservation of traditional values, and maintenance of both biodiversity and ecosystem resilience is a challenge for reef managers and resource users. Consistently, growing reef tourism sectors offer more lucrative livelihoods than subsistence and artisanal fisheries at the cost of traditional heritage loss and ecological damage. Using a systematic review of coral reef fishery reconstructions since the 1940s, we show that declining trends in fisheries catch and fish stocks dominate coral reef fisheries globally, due in part to overfishing of schooling and spawning-aggregating fish stocks vulnerable to exploitation. Using a separate systematic review of coral reef tourism studies since 2013, we identify socio-ecological impacts and economic opportunities associated to the industry. Fisheries and tourism have the potential to threaten the ecological stability of coral reefs, resulting in phase shifts toward less productive coral-depleted ecosystem states. We consider whether four common management strategies (unmanaged commons, ecosystem-based management, co-management, and adaptive co-management) fulfil ecological conservation and socioeconomic goals, such as living wage, job security, and maintenance of cultural traditions. Strategies to enforce resource exclusion and withhold traditional resource rights risk social unrest; thus, the coexistence of fisheries and tourism industries is essential. The purpose of this chapter is to assist managers and scientists in their responsibility to devise implementable strategies that protect local community livelihoods and the coral reefs on which they rely

A global reference for human genetic variation

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.We thank the many people who were generous with contributing their samples to the project: the African Caribbean in Barbados; Bengali in Bangladesh; British in England and Scotland; Chinese Dai in Xishuangbanna, China; Colombians in Medellin, Colombia; Esan in Nigeria; Finnish in Finland; Gambian in Western Division – Mandinka; Gujarati Indians in Houston, Texas, USA; Han Chinese in Beijing, China; Iberian populations in Spain; Indian Telugu in the UK; Japanese in Tokyo, Japan; Kinh in Ho Chi Minh City, Vietnam; Luhya in Webuye, Kenya; Mende in Sierra Leone; people with African ancestry in the southwest USA; people with Mexican ancestry in Los Angeles, California, USA; Peruvians in Lima, Peru; Puerto Ricans in Puerto Rico; Punjabi in Lahore, Pakistan; southern Han Chinese; Sri Lankan Tamil in the UK; Toscani in Italia; Utah residents (CEPH) with northern and western European ancestry; and Yoruba in Ibadan, Nigeria. Many thanks to the people who contributed to this project: P. Maul, T. Maul, and C. Foster; Z. Chong, X. Fan, W. Zhou, and T. Chen; N. Sengamalay, S. Ott, L. Sadzewicz, J. Liu, and L. Tallon; L. Merson; O. Folarin, D. Asogun, O. Ikpwonmosa, E. Philomena, G. Akpede, S. Okhobgenin, and O. Omoniwa; the staff of the Institute of Lassa Fever Research and Control (ILFRC), Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria; A. Schlattl and T. Zichner; S. Lewis, E. Appelbaum, and L. Fulton; A. Yurovsky and I. Padioleau; N. Kaelin and F. Laplace; E. Drury and H. Arbery; A. Naranjo, M. Victoria Parra, and C. Duque; S. Däkel, B. Lenz, and S. Schrinner; S. Bumpstead; and C. Fletcher-Hoppe. Funding for this work was from the Wellcome Trust Core Award 090532/Z/09/Z and Senior Investigator Award 095552/Z/11/Z (P.D.), and grants WT098051 (R.D.), WT095908 and WT109497 (P.F.), WT086084/Z/08/Z and WT100956/Z/13/Z (G.M.), WT097307 (W.K.), WT0855322/Z/08/Z (R.L.), WT090770/Z/09/Z (D.K.), the Wellcome Trust Major Overseas program in Vietnam grant 089276/Z.09/Z (S.D.), the Medical Research Council UK grant G0801823 (J.L.M.), the UK Biotechnology and Biological Sciences Research Council grants BB/I02593X/1 (G.M.) and BB/I021213/1 (A.R.L.), the British Heart Foundation (C.A.A.), the Monument Trust (J.H.), the European Molecular Biology Laboratory (P.F.), the European Research Council grant 617306 (J.L.M.), the Chinese 863 Program 2012AA02A201, the National Basic Research program of China 973 program no. 2011CB809201, 2011CB809202 and 2011CB809203, Natural Science Foundation of China 31161130357, the Shenzhen Municipal Government of China grant ZYC201105170397A (J.W.), the Canadian Institutes of Health Research Operating grant 136855 and Canada Research Chair (S.G.), Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research (M.K.D.), a Le Fonds de Recherche duQuébec-Santé (FRQS) research fellowship (A.H.), Genome Quebec (P.A.), the Ontario Ministry of Research and Innovation – Ontario Institute for Cancer Research Investigator Award (P.A., J.S.), the Quebec Ministry of Economic Development, Innovation, and Exports grant PSR-SIIRI-195 (P.A.), the German Federal Ministry of Education and Research (BMBF) grants 0315428A and 01GS08201 (R.H.), the Max Planck Society (H.L., G.M., R.S.), BMBF-EPITREAT grant 0316190A (R.H., M.L.), the German Research Foundation (Deutsche Forschungsgemeinschaft) Emmy Noether Grant KO4037/1-1 (J.O.K.), the Beatriu de Pinos Program grants 2006 BP-A 10144 and 2009 BP-B 00274 (M.V.), the Spanish National Institute for Health Research grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER (A.O.), Ewha Womans University (C.L.), the Japan Society for the Promotion of Science Fellowship number PE13075 (N.P.), the Louis Jeantet Foundation (E.T.D.), the Marie Curie Actions Career Integration grant 303772 (C.A.), the Swiss National Science Foundation 31003A_130342 and NCCR “Frontiers in Genetics” (E.T.D.), the University of Geneva (E.T.D., T.L., G.M.), the US National Institutes of Health National Center for Biotechnology Information (S.S.) and grants U54HG3067 (E.S.L.), U54HG3273 and U01HG5211 (R.A.G.), U54HG3079 (R.K.W., E.R.M.), R01HG2898 (S.E.D.), R01HG2385 (E.E.E.), RC2HG5552 and U01HG6513 (G.T.M., G.R.A.), U01HG5214 (A.C.), U01HG5715 (C.D.B.), U01HG5718 (M.G.), U01HG5728 (Y.X.F.), U41HG7635 (R.K.W., E.E.E., P.H.S.), U41HG7497 (C.L., M.A.B., K.C., L.D., E.E.E., M.G., J.O.K., G.T.M., S.A.M., R.E.M., J.L.S., K.Y.), R01HG4960 and R01HG5701 (B.L.B.), R01HG5214 (G.A.), R01HG6855 (S.M.), R01HG7068 (R.E.M.), R01HG7644 (R.D.H.), DP2OD6514 (P.S.), DP5OD9154 (J.K.), R01CA166661 (S.E.D.), R01CA172652 (K.C.), P01GM99568 (S.R.B.), R01GM59290 (L.B.J., M.A.B.), R01GM104390 (L.B.J., M.Y.Y.), T32GM7790 (C.D.B., A.R.M.), P01GM99568 (S.R.B.), R01HL87699 and R01HL104608 (K.C.B.), T32HL94284 (J.L.R.F.), and contracts HHSN268201100040C (A.M.R.) and HHSN272201000025C (P.S.), Harvard Medical School Eleanor and Miles Shore Fellowship (K.L.), Lundbeck Foundation Grant R170-2014-1039 (K.L.), NIJ Grant 2014-DN-BX-K089 (Y.E.), the Mary Beryl Patch Turnbull Scholar Program (K.C.B.), NSF Graduate Research Fellowship DGE-1147470 (G.D.P.), the Simons Foundation SFARI award SF51 (M.W.), and a Sloan Foundation Fellowship (R.D.H.). E.E.E. is an investigator of the Howard Hughes Medical Institute

Antarcticness: Inspirations and imaginaries

International audienc