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1.
Artigo em Inglês | MEDLINE | ID: mdl-32967163

RESUMO

OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused substantial panic worldwide since its outbreak in December 2019. This study uses social networks to track the evolution of public emotion during COVID-19 in China and analyzes the root causes of these public emotions from an event-driven perspective. METHODS: A dataset was constructed using microblogs (n = 125,672) labeled with COVID-19-related super topics (n = 680) from 40,891 users from 1 December 2019 to 17 February 2020. Based on the skeleton and key change points of COVID-19 extracted from microblogging contents, we tracked the public's emotional evolution modes (accumulated emotions, emotion covariances, and emotion transitions) by time phase and further extracted the details of dominant social events. RESULTS: Public emotions showed different evolution modes during different phases of COVID-19. Events about the development of COVID-19 remained hot, but generally declined, and public attention shifted to other aspects of the epidemic (e.g., encouragement, support, and treatment). CONCLUSIONS: These findings suggest that the public's feedback on COVID-19 predated official accounts on the microblog platform. There were clear differences in the trending events that large users (users with many fans and readings) and common users paid attention to during each phase of COVID-19.


Assuntos
Blogging/estatística & dados numéricos , Infecções por Coronavirus/psicologia , Coronavirus , Emoções , Armazenamento e Recuperação da Informação/métodos , Pneumonia Viral/psicologia , Mídias Sociais/estatística & dados numéricos , Betacoronavirus , China , Infecções por Coronavirus/epidemiologia , Humanos , Pandemias , Pneumonia Viral/epidemiologia
2.
J Toxicol Sci ; 45(8): 449-473, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32741897

RESUMO

Although peroxisome proliferator-activated receptor α (PPARα) agonists are obviously hepatocarcinogenic in rodents, they have been widely used for dyslipidemia and proven to be safe for clinical use without respect to the species difference. It is established that PPARα acts as a part of the transcription factor complex, but its precise mechanism is still unknown. Using the data of Toxicogenomics Database, reliable genes responsive to PPARα agonists, clofibrate, fenofibrate and WY-14,643, in rat liver, were extracted from both in vivo and in vitro data, and sorted by their fold increase. It was found that there were many genes responding to fibrates exclusively in vivo. Most of the in vivo specific genes appear to be unrelated to lipid metabolism and are not upregulated in the kidney. Fifty-seven genes directly related to cell proliferation were extracted from in vivo data, but they were not induced in vitro at all. Analysis of PPAR-responsive elements could not explain the observed difference in induction. To evaluate possible interaction between neighboring genes in gene expression, the correlation of the fold changes of neighboring genes for 22 drugs with various PPARα agonistic potencies were calculated for the genes showing more than 2.5 fold induction by 3 fibrates in vivo, and their genomic location was compared with that of the human orthologue. In the present study, many candidates of genes other than lipid metabolism were selected, and these could be good starting points to elucidate the mechanism of PPARα agonist-induced rodent-specific toxicity.


Assuntos
Bases de Dados Genéticas , Fenofibrato/toxicidade , Loci Gênicos/genética , Armazenamento e Recuperação da Informação/métodos , Metabolismo dos Lipídeos/genética , Fígado/metabolismo , PPAR alfa/agonistas , Pirimidinas/toxicidade , Animais , Epistasia Genética , Expressão Gênica , Estudos de Associação Genética , Masculino , Ratos Sprague-Dawley , Especificidade da Espécie
3.
Bone Joint J ; 102-B(7_Supple_B): 99-104, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32600201

RESUMO

AIMS: Natural Language Processing (NLP) offers an automated method to extract data from unstructured free text fields for arthroplasty registry participation. Our objective was to investigate how accurately NLP can be used to extract structured clinical data from unstructured clinical notes when compared with manual data extraction. METHODS: A group of 1,000 randomly selected clinical and hospital notes from eight different surgeons were collected for patients undergoing primary arthroplasty between 2012 and 2018. In all, 19 preoperative, 17 operative, and two postoperative variables of interest were manually extracted from these notes. A NLP algorithm was created to automatically extract these variables from a training sample of these notes, and the algorithm was tested on a random test sample of notes. Performance of the NLP algorithm was measured in Statistical Analysis System (SAS) by calculating the accuracy of the variables collected, the ability of the algorithm to collect the correct information when it was indeed in the note (sensitivity), and the ability of the algorithm to not collect a certain data element when it was not in the note (specificity). RESULTS: The NLP algorithm performed well at extracting variables from unstructured data in our random test dataset (accuracy = 96.3%, sensitivity = 95.2%, and specificity = 97.4%). It performed better at extracting data that were in a structured, templated format such as range of movement (ROM) (accuracy = 98%) and implant brand (accuracy = 98%) than data that were entered with variation depending on the author of the note such as the presence of deep-vein thrombosis (DVT) (accuracy = 90%). CONCLUSION: The NLP algorithm used in this study was able to identify a subset of variables from randomly selected unstructured notes in arthroplasty with an accuracy above 90%. For some variables, such as objective exam data, the accuracy was very high. Our findings suggest that automated algorithms using NLP can help orthopaedic practices retrospectively collect information for registries and quality improvement (QI) efforts. Cite this article: Bone Joint J 2020;102-B(7 Supple B):99-104.


Assuntos
Artroplastia de Quadril , Artroplastia do Joelho , Armazenamento e Recuperação da Informação/métodos , Processamento de Linguagem Natural , Sistema de Registros , Algoritmos , Confiabilidade dos Dados , Humanos , Qualidade da Assistência à Saúde , Estudos Retrospectivos
4.
Stud Health Technol Inform ; 270: 208-212, 2020 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-32570376

RESUMO

This paper presents five document retrieval systems for a small (few thousands) and domain specific corpora (weekly peer-reviewed medical journals published in French) as well as an evaluation methodology to quantify the models performance. The proposed methodology does not rely on external annotations and therefore can be used as an ad hoc evaluation procedure for most document retrieval tasks. Statistical models and vector space models are empirically compared on a synthetic document retrieval task. For our dataset size and specificities the statistical approaches consistently performed better than its vector space counterparts.


Assuntos
Armazenamento e Recuperação da Informação/métodos , Idioma , Medical Subject Headings , Modelos Estatísticos , Processamento de Linguagem Natural , Humanos
5.
Stud Health Technol Inform ; 270: 282-286, 2020 Jun 16.
Artigo em Inglês | MEDLINE | ID: mdl-32570391

RESUMO

In this paper, we present and discuss two new measures of inter- and intra-rater agreement to assess the reliability of the raters, and hence of their labeling, in multi-rater setings, which are common in the production of ground truth for machine learning models. Our proposal is more conservative of other existing agreement measures, as it considers a more articulated notion of agreement by chance, based on an empirical estimation of the precision (or reliability) of the single raters involved. We discuss the measures in light of a realistic annotation tasks that involved 13 expert radiologists in labeling the MRNet dataset.


Assuntos
Armazenamento e Recuperação da Informação/métodos , Aprendizado de Máquina , Variações Dependentes do Observador , Radiologistas , Registros Eletrônicos de Saúde , Humanos , Radiologia , Reprodutibilidade dos Testes
6.
PLoS One ; 15(6): e0232791, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32479504

RESUMO

BACKGROUND: Constructing a medical image feature database according to the category of disease can achieve a quick retrieval of images with similar pathological features. Therefore, this approach has important application values in the fields such as auxiliary diagnosis, teaching, research, and telemedicine. METHODS: Based on the deep convolutional neural network, an image classifier applicable to brain disease was designed to distinguish between the image features of the different brain diseases with similar anatomical structures. Through the extraction and analysis of visual features, the images were labelled with the corresponding semantic features of a specific disease category, which can establish an association between the visual features of brain images and the semantic features of the category of disease which will permit to construct a disease category feature database of brain images. RESULTS: Based on the similarity measurement and the matching strategy of high-dimensional visual feature, a high-precision retrieval of brain image with semantics category was achieved, and the constructed disease category feature database of brain image was tested and evaluated through large numbers of pathological image retrieval experiments, the accuracy and the effectiveness of the proposed approach was verified. CONCLUSION: The disease category feature database of brain image constructed by the proposed approach achieved a quick and effective retrieval of images with similar pathological features, which is beneficial to the categorization and analysis of intractable brain diseases. This provides an effective application tool such as case-based image data management, evidence-based medicine and clinical decision support.


Assuntos
Encefalopatias/classificação , Interpretação de Imagem Assistida por Computador/métodos , Reconhecimento Automatizado de Padrão/métodos , Algoritmos , Encéfalo/diagnóstico por imagem , Encefalopatias/diagnóstico por imagem , Bases de Dados Factuais , Sistemas de Apoio a Decisões Clínicas , Humanos , Armazenamento e Recuperação da Informação/métodos , Redes Neurais de Computação , Neuroimagem/métodos
8.
PLoS One ; 15(5): e0230950, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32365122

RESUMO

A pharmacogenomics-based pathway represents a series of reactions that occur between drugs and genes in the human body after drug administration. PG-path is a pharmacogenomics-based pathway that standardizes and visualizes the components (nodes) and actions (edges) involved in pharmacokinetic and pharmacodynamic processes. It provides an intuitive understanding of the drug response in the human body. A pharmacokinetic pathway visualizes the absorption, distribution, metabolism, and excretion (ADME) at the systemic level, and a pharmacodynamic pathway shows the action of the drug in the target cell at the cellular-molecular level. The genes in the pathway are displayed in locations similar to those inside the body. PG-path allows personalized pathways to be created by annotating each gene with the overall impact degree of deleterious variants in the gene. These personalized pathways play a role in assisting tailored individual prescriptions by predicting changes in the drug concentration in the plasma. PG-path also supports counseling for personalized drug therapy by providing visualization and documentation.


Assuntos
Biologia Computacional/métodos , Redes e Vias Metabólicas/genética , Preparações Farmacêuticas/metabolismo , Farmacogenética/métodos , Medicina de Precisão/métodos , Software , Bases de Dados Genéticas , Tratamento Farmacológico/métodos , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/genética , Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos/metabolismo , Absorção Gastrointestinal/genética , Estudos de Associação Genética , Humanos , Inativação Metabólica/efeitos dos fármacos , Inativação Metabólica/genética , Armazenamento e Recuperação da Informação/métodos , Redes e Vias Metabólicas/efeitos dos fármacos , Modelos Teóricos
9.
PLoS One ; 15(5): e0232547, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32413094

RESUMO

Scientific information extraction is a crucial step for understanding scientific publications. In this paper, we focus on scientific keyphrase extraction, which aims to identify keyphrases from scientific articles and classify them into predefined categories. We present a neural network based approach for this task, which employs the bidirectional long short-memory (LSTM) to represent the sentences in the article. On top of the bidirectional LSTM layer in our neural model, conditional random field (CRF) is used to predict the label sequence for the whole sentence. Considering the expensive annotated data for supervised learning methods, we introduce self-training method into our neural model to leverage the unlabeled articles. Experimental results on the ScienceIE corpus and ACL keyphrase corpus show that our neural model achieves promising performance without any hand-designed features and external knowledge resources. Furthermore, it efficiently incorporates the unlabeled data and achieve competitive performance compared with previous state-of-the-art systems.


Assuntos
Aprendizado Profundo , Armazenamento e Recuperação da Informação/métodos , Redes Neurais de Computação , Modelos Estatísticos , Processamento de Linguagem Natural , Publicações
10.
PLoS One ; 15(5): e0232942, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32453750

RESUMO

The recent decrease in cost and time to sequence and assemble of complete genomes created an increased demand for data storage. As a consequence, several strategies for assembled biological data compression were created. Vertical compression tools implement strategies that take advantage of the high level of similarity between multiple assembled genomic sequences for better compression results. However, current reviews on vertical compression do not compare the execution flow of each tool, which is constituted by phases of preprocessing, transformation, and data encoding. We performed a systematic literature review to identify and compare existing tools for vertical compression of assembled genomic sequences. The review was centered on PubMed and Scopus, in which 45726 distinct papers were considered. Next, 32 papers were selected according to the following criteria: to present a lossless vertical compression tool; to use the information contained in other sequences for the compression; to be able to manipulate genomic sequences in FASTA format; and no need prior knowledge. Although we extracted performance compression results, they were not compared as the tools did not use a standardized evaluation protocol. Thus, we conclude that there's a lack of definition of an evaluation protocol that must be applied by each tool.


Assuntos
Compressão de Dados/métodos , Armazenamento e Recuperação da Informação/métodos , Análise de Sequência de DNA/métodos , Algoritmos , Genoma , Genômica/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Publicações , Software
11.
Hum Genet ; 139(10): 1285-1297, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32385526

RESUMO

During the past decade, genetic studies of schizophrenia have become one of the most exciting and fast-moving areas. Hundreds of genes implicated in schizophrenia have been identified by genetic, epigenetic, and gene expression studies. However, how to systematically and efficiently use these published data to pinpoint the causal genes becomes a major challenge in schizophrenia research. Here, we release an updated version of a comprehensive database for schizophrenia research, SZDB2.0 ( www.szdb.org ), which accompanies significant data expansion and feature improvements, as well as functionality optimization. Compared with the first version (SZDB), the current database has the following updates: (1) We added the newly published genome-wide association study (GWAS) of schizophrenia from CLOZUK + PGC, which is the largest GWAS for schizophrenia; (2) We included a polygenic risk score calculator; (3) In the refined "Gene" module of SZDB2.0, we collated genetic, gene expression, methylation, and integrative results of all available schizophrenia studies; (4) In the "CNV (copy number variation)" module, we collated the results of all 77 CNV publications about schizophrenia; (5) We also updated other data, including gene expression quantitative trait loci (eQTL), transcript QTL, methylation QTL, and protein-protein interaction data, based on the information from the latest literatures. We optimized the query interface of SZDB2.0 for a better visualization and data retrieval. The updated SZDB2.0 will advance the research of schizophrenia.


Assuntos
Bases de Dados Genéticas , Epigênese Genética , Predisposição Genética para Doença , Herança Multifatorial , Locos de Características Quantitativas , Esquizofrenia/genética , Variações do Número de Cópias de DNA , Metilação de DNA , Ontologia Genética , Estudo de Associação Genômica Ampla , Humanos , Armazenamento e Recuperação da Informação/métodos , Polimorfismo de Nucleotídeo Único , Córtex Pré-Frontal/metabolismo , Córtex Pré-Frontal/fisiopatologia , Mapeamento de Interação de Proteínas , Risco , Esquizofrenia/diagnóstico , Esquizofrenia/fisiopatologia
12.
J Am Med Inform Assoc ; 27(9): 1431-1436, 2020 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-32365190

RESUMO

TREC-COVID is an information retrieval (IR) shared task initiated to support clinicians and clinical research during the COVID-19 pandemic. IR for pandemics breaks many normal assumptions, which can be seen by examining 9 important basic IR research questions related to pandemic situations. TREC-COVID differs from traditional IR shared task evaluations with special considerations for the expected users, IR modality considerations, topic development, participant requirements, assessment process, relevance criteria, evaluation metrics, iteration process, projected timeline, and the implications of data use as a post-task test collection. This article describes how all these were addressed for the particular requirements of developing IR systems under a pandemic situation. Finally, initial participation numbers are also provided, which demonstrate the tremendous interest the IR community has in this effort.


Assuntos
Betacoronavirus , Infecções por Coronavirus , Armazenamento e Recuperação da Informação , Pandemias , Pneumonia Viral , Humanos , Armazenamento e Recuperação da Informação/métodos , Ferramenta de Busca
13.
Artigo em Inglês | MEDLINE | ID: covidwho-72521

RESUMO

The outbreak of Corona Virus Disease 2019 (COVID-19) is a grave global public health emergency. Nowadays, social media has become the main channel through which the public can obtain information and express their opinions and feelings. This study explored public opinion in the early stages of COVID-19 in China by analyzing Sina-Weibo (a Twitter-like microblogging system in China) texts in terms of space, time, and content. Temporal changes within one-hour intervals and the spatial distribution of COVID-19-related Weibo texts were analyzed. Based on the latent Dirichlet allocation model and the random forest algorithm, a topic extraction and classification model was developed to hierarchically identify seven COVID-19-relevant topics and 13 sub-topics from Weibo texts. The results indicate that the number of Weibo texts varied over time for different topics and sub-topics corresponding with the different developmental stages of the event. The spatial distribution of COVID-19-relevant Weibo was mainly concentrated in Wuhan, Beijing-Tianjin-Hebei, the Yangtze River Delta, the Pearl River Delta, and the Chengdu-Chongqing urban agglomeration. There is a synchronization between frequent daily discussions on Weibo and the trend of the COVID-19 outbreak in the real world. Public response is very sensitive to the epidemic and significant social events, especially in urban agglomerations with convenient transportation and a large population. The timely dissemination and updating of epidemic-related information and the popularization of such information by the government can contribute to stabilizing public sentiments. However, the surge of public demand and the hysteresis of social support demonstrated that the allocation of medical resources was under enormous pressure in the early stage of the epidemic. It is suggested that the government should strengthen the response in terms of public opinion and epidemic prevention and exert control in key epidemic areas, urban agglomerations, and transboundary areas at the province level. In controlling the crisis, accurate response countermeasures should be formulated following public help demands. The findings can help government and emergency agencies to better understand the public opinion and sentiments towards COVID-19, to accelerate emergency responses, and to support post-disaster management.


Assuntos
Infecções por Coronavirus/epidemiologia , Armazenamento e Recuperação da Informação/métodos , Pneumonia Viral/epidemiologia , Opinião Pública , Mídias Sociais , China/epidemiologia , Humanos , Pandemias
14.
Br J Nurs ; 29(8): 481-483, 2020 Apr 23.
Artigo em Inglês | MEDLINE | ID: mdl-32324469

RESUMO

This article follows on from a previous article on how to carry out a literature search (Watson, 2020) and looks at how you can enhance your search by going beyond journal databases to using search engines, websites and grey literature sources. Ways to evaluate the resources you find, the use of critical appraisal tools and factors to consider when presenting your results are also discussed.


Assuntos
Bases de Dados Bibliográficas , Armazenamento e Recuperação da Informação/métodos , Ferramenta de Busca , Viés , Humanos , Internet , Publicações Periódicas como Assunto
15.
Artigo em Inglês | MEDLINE | ID: mdl-32316647

RESUMO

The outbreak of Corona Virus Disease 2019 (COVID-19) is a grave global public health emergency. Nowadays, social media has become the main channel through which the public can obtain information and express their opinions and feelings. This study explored public opinion in the early stages of COVID-19 in China by analyzing Sina-Weibo (a Twitter-like microblogging system in China) texts in terms of space, time, and content. Temporal changes within one-hour intervals and the spatial distribution of COVID-19-related Weibo texts were analyzed. Based on the latent Dirichlet allocation model and the random forest algorithm, a topic extraction and classification model was developed to hierarchically identify seven COVID-19-relevant topics and 13 sub-topics from Weibo texts. The results indicate that the number of Weibo texts varied over time for different topics and sub-topics corresponding with the different developmental stages of the event. The spatial distribution of COVID-19-relevant Weibo was mainly concentrated in Wuhan, Beijing-Tianjin-Hebei, the Yangtze River Delta, the Pearl River Delta, and the Chengdu-Chongqing urban agglomeration. There is a synchronization between frequent daily discussions on Weibo and the trend of the COVID-19 outbreak in the real world. Public response is very sensitive to the epidemic and significant social events, especially in urban agglomerations with convenient transportation and a large population. The timely dissemination and updating of epidemic-related information and the popularization of such information by the government can contribute to stabilizing public sentiments. However, the surge of public demand and the hysteresis of social support demonstrated that the allocation of medical resources was under enormous pressure in the early stage of the epidemic. It is suggested that the government should strengthen the response in terms of public opinion and epidemic prevention and exert control in key epidemic areas, urban agglomerations, and transboundary areas at the province level. In controlling the crisis, accurate response countermeasures should be formulated following public help demands. The findings can help government and emergency agencies to better understand the public opinion and sentiments towards COVID-19, to accelerate emergency responses, and to support post-disaster management.


Assuntos
Infecções por Coronavirus/epidemiologia , Armazenamento e Recuperação da Informação/métodos , Pneumonia Viral/epidemiologia , Opinião Pública , Mídias Sociais , China/epidemiologia , Humanos , Pandemias
16.
Telemed J E Health ; 26(6): 725-733, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32298208

RESUMO

Background: Most secondary transmission of COVID-19 is occurring in a hospital setting. To decrease person-to-person contact, health care providers have built many isolation wards. However, out-of-hospital professionals cannot access patient information, which has greatly reduced the efficiency of treatment; it is inconvenient for health care professionals to issue a case discussion with professionals from other wards. This article mainly introduces a mobile telehealth system (MTS) applied to facilitate patient information presentation and case discussion. Materials and Methods: The MTS searches patient information, which is stored in hospital intranet, and uses five modules to display patient information. By a request/response module and a real-time interaction module, we successfully conducted case discussions. In addition, we took measures in three areas to prevent patient information leakage. Results: The system uses mobile collaboration technology to present patient information and support case discussion. MTS was officially launched for 37 days, during which it has been used 3,061 times. Conclusions: The building of the MTS not only provides convenience and benefit for health care professionals, but also reduces person-to-person contact.


Assuntos
Betacoronavirus , Telefone Celular , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/terapia , Registros Eletrônicos de Saúde , Armazenamento e Recuperação da Informação/métodos , Pneumonia Viral/diagnóstico , Pneumonia Viral/terapia , Telemedicina/métodos , Humanos , Pandemias
17.
Br J Nurs ; 29(7): 431-435, 2020 Apr 09.
Artigo em Inglês | MEDLINE | ID: mdl-32279549

RESUMO

Undertaking a literature search can be a daunting prospect. Breaking the exercise down into smaller steps will make the process more manageable. This article suggests 10 steps that will help readers complete this task, from identifying key concepts to choosing databases for the search and saving the results and search strategy. It discusses each of the steps in a little more detail, with examples and suggestions on where to get help. This structured approach will help readers obtain a more focused set of results and, ultimately, save time and effort.


Assuntos
Bases de Dados Bibliográficas , Armazenamento e Recuperação da Informação/métodos , Literatura de Revisão como Assunto , Humanos , Pesquisa em Enfermagem
18.
PLoS One ; 15(4): e0230722, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32271788

RESUMO

With the rapid development of informatization, an increasing number of industries and organizations outsource their data to cloud servers, to avoid the cost of local data management and to share data. For example, industrial Internet of things systems and mobile healthcare systems rely on cloud computing's powerful data storage and processing capabilities to address the storage, provision, and maintenance of massive amounts of industrial and medical data. One of the major challenges facing cloud-based storage environments is how to ensure the confidentiality and security of outsourced sensitive data. To mitigate these issues, He et al. and Ma et al. have recently independently proposed two certificateless public key searchable encryption schemes. In this paper, we analyze the security of these two schemes and show that the reduction proof of He et al.'s CLPAEKS scheme is incorrect, and that Ma et al.'s CLPEKS scheme is not secure against keyword guessing attacks. We then propose a channel-free certificateless searchable public key authenticated encryption (dCLPAEKS) scheme and prove that it is secure against inside keyword guessing attacks under the enhanced security model. Compared with other certificateless public key searchable encryption schemes, this scheme has higher security and comparable efficiency.


Assuntos
Computação em Nuvem/normas , Segurança Computacional/normas , Armazenamento e Recuperação da Informação , Internet das Coisas , Setor Público , Algoritmos , Confidencialidade , Gerenciamento de Dados/métodos , Gerenciamento de Dados/organização & administração , Gerenciamento de Dados/normas , Eficiência Organizacional , Registros Eletrônicos de Saúde/organização & administração , Registros Eletrônicos de Saúde/normas , Troca de Informação em Saúde/normas , Humanos , Armazenamento e Recuperação da Informação/métodos , Armazenamento e Recuperação da Informação/normas , Internet das Coisas/organização & administração , Internet das Coisas/normas , Serviços Terceirizados/organização & administração , Serviços Terceirizados/normas , Setor Público/organização & administração , Setor Público/normas , Tecnologia sem Fio/organização & administração , Tecnologia sem Fio/normas
19.
BMC Health Serv Res ; 20(1): 289, 2020 Apr 06.
Artigo em Inglês | MEDLINE | ID: mdl-32252755

RESUMO

BACKGROUND: Patient safety in home healthcare is largely unexplored. No-harm incidents may give valuable information about risk areas and system failures as a source for proactive patient safety work. We hypothesized that it would be feasible to retrospectively identify no-harm incidents and thus aimed to explore the cumulative incidence, preventability, types, and potential contributing causes of no-harm incidents that affected adult patients admitted to home healthcare. METHODS: A structured retrospective record review using a trigger tool designed for home healthcare. A random sample of 600 home healthcare records from ten different organizations across Sweden was reviewed. RESULTS: In the study, 40,735 days were reviewed. In all, 313 no-harm incidents affected 177 (29.5%) patients; of these, 198 (63.2%) no-harm incidents, in 127 (21.2%) patients, were considered preventable. The most common no-harm incident types were "fall without harm," "deficiencies in medication management," and "moderate pain." The type "deficiencies in medication management" was deemed to have a preventability rate twice as high as those of "fall without harm" and "moderate pain." The most common potential contributing cause was "deficiencies in nursing care and treatment, i.e., delayed, erroneous, omitted or incomplete treatment or care." CONCLUSION: This study suggests that it is feasible to identify no-harm incidents and potential contributing causes such as omission of care using record review with a trigger tool adapted to the context. No-harm incidents and potential contributing causes are valuable sources of knowledge for improving patient safety, as they highlight system failures and indicate risks before an adverse event reach the patient.


Assuntos
Serviços de Assistência Domiciliar , Segurança do Paciente , Medição de Risco , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Bases de Dados Factuais , Feminino , Humanos , Armazenamento e Recuperação da Informação/métodos , Masculino , Erros Médicos/prevenção & controle , Pessoa de Meia-Idade , Estudos Retrospectivos , Medição de Risco/métodos , Suécia , Adulto Jovem
20.
PLoS One ; 15(3): e0229003, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32160189

RESUMO

BACKGROUND: With data becoming a centerpiece of modern scientific discovery, data sharing by scientists is now a crucial element of scientific progress. This article aims to provide an in-depth examination of the practices and perceptions of data management, including data storage, data sharing, and data use and reuse by scientists around the world. METHODS: The Usability and Assessment Working Group of DataONE, an NSF-funded environmental cyberinfrastructure project, distributed a survey to a multinational and multidisciplinary sample of scientific researchers in a two-waves approach in 2017-2018. We focused our analysis on examining the differences across age groups, sub-disciplines of science, and sectors of employment. FINDINGS: Most respondents displayed what we describe as high and mediocre risk data practices by storing their data on their personal computer, departmental servers or USB drives. Respondents appeared to be satisfied with short-term storage solutions; however, only half of them are satisfied with available mechanisms for storing data beyond the life of the process. Data sharing and data reuse were viewed positively: over 85% of respondents admitted they would be willing to share their data with others and said they would use data collected by others if it could be easily accessed. A vast majority of respondents felt that the lack of access to data generated by other researchers or institutions was a major impediment to progress in science at large, yet only about a half thought that it restricted their own ability to answer scientific questions. Although attitudes towards data sharing and data use and reuse are mostly positive, practice does not always support data storage, sharing, and future reuse. Assistance through data managers or data librarians, readily available data repositories for both long-term and short-term storage, and educational programs for both awareness and to help engender good data practices are clearly needed.


Assuntos
Disseminação de Informação , Armazenamento e Recuperação da Informação/métodos , Estudos Interdisciplinares , Percepção , Pesquisadores/psicologia , Adulto , Idoso , Atitude , Humanos , Pessoa de Meia-Idade , Inquéritos e Questionários , Adulto Jovem
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