Provider issues related to patient controlled analgesia and nurse controlled analgesia errors in a pediatric hospital

Background: Medical errors are a danger to patient safety and a significant cause of morbidity and mortality. Additionally, they increase expenditures in an already significantly indebted U.S. health care system. Much confusion exists about definitions of medical errors, which include medication errors and adverse drug events (ADEs). Several federal and international organizations have attempted to standardize definitions in order to streamline data collection, but until these standards are universally adopted, error reports and trends are still subject to questions of validity. Reporting errors, in general, has become a more socially acceptable practice in health care with the advent of several anonymous reporting databases. There have also been several initiatives aimed at reducing the incidence of errors, which range from national programs to intrafacility guidelines. Several pieces of health information technology (HIT) have made an impact on error incidence and data collection, although there is much room for improvement. Patient controlled analgesia (PCA) pumps for pain management have been in existence for decades, and "smart pump" software has improved their safety and ease of programming. PCA use in children presents challenges to clinicians, and the characteristics of providers who write PCA orders and those who program PCA pumps may play a role in the incidence of events related to PCA. This study seeks to elucidate trends in errors as they related to these different PCA providers in a pediatric hospital in the northeastern U.S. and provide recommendations for how PCA practice can be improved in this facility. Methods: Safety Event Reporting System (SERS) reports of PCA events (n = 117) during the period of 2004 - 2012 were analyzed retrospectively to determine several key variables for data analysis. The main focus of this analysis was those variable trends related to providers, including: proportion of events caused by human error, proportion of events related to subcategories of human error, proportion of types of prescribers involved in PCA events, proportion of errors in medical and surgical patients, proportion of errors occurring on day and night shifts for the nursing staff, and proportion of events that were dosing mistakes. Statistical analysis was performed for these results when possible to determine significance. Results: Human errors were implicated in 84.1% of events, whereas PCA pump mechanical errors and software errors were implicated in 7.1% and 7.9% of events, respectively. Statistically significant differences were found in all variables tested, including the proportion of nursing errors (60.9%) versus prescriber errors (28.7%) (p < 0.0002). For types of prescribers, the proportion of PCA events occurring when a M.D. wrote the PCA order (56.41%) was statistically different than when a N.P. wrote the PCA order (39.32%) (p = 0.0129). More surgical patients (61.5%) were affected by PCA events than medical patients (36.8%) (p < 0.0002). There were more events occurring on the nursing staff day shift (59.8%) than the night shift (36.8%) (p = 0.0004). Finally, dosing mistakes (66.7%) were implicated in significantly more PCA events than any other error type (33.3%) (p < 0.0002). Conclusion: Several recommendations for improving the safety of PCA in pediatric pain management are justified by the results of this data analysis. First, further education and simulation for entering PCA orders into the CPOE system is needed for all prescribers. Secondly, further education and simulation in PCA pump programming and system set-up is needed for all nursing staff members. In regard to prescriber credentials, it is recommended that Pain Treatment Service (PTS) staff members train M.D. residents in writing PCA orders and entering them into the CPOE system. Finally, it is recommended that the SERS management team publish standardized error report content and entry format in order to streamline data analysis for quality improvement (QI) purposes

Manual de utilização de ferramenta do Centro Comum de Investigação para validação das mudanças da cobertura vegetal e do uso da terra

O projeto TREES-3 do CCI tem como objetivo avaliar mudanças da cobertura vegetal na região tropical que ocorreram entre 1990 e 2000, e entre 2000-(2005)-2010. Para isto, foram processadas e avaliadas mudanças da cobertura vegetal em uma grande quantidade de imagens de satélite multi-temporais de resolução espacial média (unidades amostrais de 20 km x 20 km de imagens Landsat). Desta forma, o projeto TREES-3 busca avaliar para cada uma das unidades amostrais a cobertura florestal e as mudanças da cobertura vegetal ocorrida num quinquénio ou década com a mais alta precisão possível. A análise da mudança da cobertura vegetal e do uso da terra inclui também uma etapa de validação visual da classificação das imagens de satélite para atribuir as classes definitivas. Para esta etapa, o CCI desenvolveu uma ferramenta computacional chamada ‘‘Ferramenta do CCI para validação das mudanças da cobertura vegetal e do uso da terra’’. Esta ferramenta é utilizada por agentes florestais nacionais ou especialistas em sensoriamento remoto provenientes de países tropicais. Nesta ferramenta, a interpretação visual das imagens de satélite é efetuada de maneira simultânea utilizando imagens de dois períodos diferentes. Desta forma, é possível verificar e ajustar classes de uso da terra que foram previamente definidas. Neste trabalho, a FAO colabora com o CCI no âmbito do projeto de levantamento por sensoriamento remoto para avaliação dos recursos florestais mundiais (FRA). O CCI agregou na ferramenta computacional uma função que permite atribuir classes de uso da terra que fazem parte da classificação utilizada pela FAO. O presente documento, intitulado ‘‘Manual de utilização de ferramenta do Centro Comum de Investigação para validação das mudanças da cobertura vegetal e do uso da terra”, explica o procedimento para instalação da ferramenta e descreve as características da interface gráfica do usuário.JRC.H.3-Forest Resources and Climat

Mapeamento preditivo da vegetação: uso de SIG para modelar a distribuição espacial de espécies arbóreas na Amazônia Central

A distribuição espacial das populações vegetais é abordada na ecologia como uma importante questão devido a sua contribuição ao entendimento de padrões e processos em florestas tropicais. A configuração espacial das populações vegetais é afetada pela interação dos fatores bióticos e abióticos do ambiente. Desta forma, a compreensão dos fatores que estruturam as populações vegetais possibilita a elaboração de modelos de distribuição de espécies. Assim, este trabalho teve como objetivo principal elaborar e validar modelos de capazes de predizer a probabilidade de ocorrência de Aniba roseaodora, Cariniana micrantha, Caryocar villosum, Dinizia excelsa, Dipteryx odorata, Goupia glabra, Manilkara bidentata e Manilkara huberi, Parida multifuga, Parkia pendula, Peltogyne paniculata, Pseudopiptadenia psilostachya em função de variáveis topográficas. A probabilidade de ocorrência dessas 12 espécies arbóreas foi estimada a partir de regressão logística múltipla. Os parâmetros estimados foram incorporados a um SIG e com isso foi obtida a representação espacial das probabilidades de ocorrência estimadas para cada uma das espécies. Os modelos indicaram associação entre a ocorrência dos indivíduos em relação à topografia para 10 espécies. Os modelos estimaram de maneira acurada a ocorrência de 9 espécies. A densidade dos indivíduos variou entre as áreas do modelo e de validação. Para área onde o modelo foi validado houve sobreposição entre a distribuição observada e estimada para as 9 espécies citadas anteriormente. No entanto, houve grande variação entre o acréscimo de acerto de ocorrência para essas espécies. Desta forma, o trabalho aqui apresentado indica que modelos preditivos de distribuição de espécies arbóreas podem predizer com acurácia ocorrência de espécies em determinada área, mas que a extrapolação para outras áreas deve considerar outros fatores, além da topografia

Sistema Brasileiro de Combate ao Tráfico de Pessoas

O tráfico de pessoas sempre esteve presente na sociedade. Nos primórdios, inclusive, era prática institucionalizada e não possuía óbice por parte dos estados. Com o avançar do tempo e dos conceitos da humanidade, principalmente com o reconhecimento da universalidade dos direitos humanos, cada indivíduo passou a ser visto como um sujeito de direitos, o que ocasionou, inclusive, a abolição da escravidão nos mais diversos países. Todavia, a redução do ser humano à condição de coisa persiste, sendo o tráfico de pessoas o meio utilizado pelos criminosos para a exploração ilegal de pessoas, desde o trabalho forçado, à exploração sexual ou até mesmo o tráfico de órgãos. O presente trabalho tem o objetivo de fazer uma introdução ao estudo sobre o tráfico de pessoas, tendo enfoque voltado à realidade brasileira, buscando trazer uma compreensão de como o crime é realizado no território nacional e como o ordenamento jurídico pátrio lida com o delito.O tráfico de pessoas sempre esteve presente na sociedade. Nos primórdios, inclusive, era prática institucionalizada e não possuía óbice por parte dos estados. Com o avançar do tempo e dos conceitos da humanidade, principalmente com o reconhecimento da universalidade dos direitos humanos, cada indivíduo passou a ser visto como um sujeito de direitos, o que ocasionou, inclusive, a abolição da escravidão nos mais diversos países. Todavia, a redução do ser humano à condição de coisa persiste, sendo o tráfico de pessoas o meio utilizado pelos criminosos para a exploração ilegal de pessoas, desde o trabalho forçado, à exploração sexual ou até mesmo o tráfico de órgãos. O presente trabalho tem o objetivo de fazer uma introdução ao estudo sobre o tráfico de pessoas, tendo enfoque voltado à realidade brasileira, buscando trazer uma compreensão de como o crime é realizado no território nacional e como o ordenamento jurídico pátrio lida com o delito

Metacommunity patterns of Amazonian Odonata: The role of environmental gradients and major rivers

Background. We identified and classified damselfly (Zygoptera) and dragonfly (Anisoptera) metacommunities in Brazilian Amazonia, relating species distribution patterns to known biological gradients and biogeographical history. We expected a random distribution of both Zygoptera and Anisoptera within interfluves. At the Amazonian scale, we expected Anisoptera metacommunities to be randomly distributed due to their higher dispersal ability and large environmental tolerance. In contrast, we expected Zygoptera communities to exhibit a Clementsian pattern, limited by the large Amazonia rivers due to their low dispersal ability. Methods. We used a dataset of 58 first-to-third order well-sampled streamlets in four Amazonian interfluves and applied an extension of the Elements of Metacommunity Structure (EMS) framework, in which we order Zygoptera and Anisoptera metacommunities by known spatial and biogeographic predictors. Results. At the Amazonian scale, both Zygoptera and Anisoptera presented a Clementsian pattern, driven by the same environmental and biogeographical predictors, namely biogeographic region (interfluve), annual mean temperature, habitat integrity and annual precipitation. At the interfluve scale, results were less consistent and only partially support our hypothesis. Zygoptera metacommunities at Guiana and Anisoptera metacommunities at Tapajós were classified as random, suggesting that neutral processes gain importance at smaller spatial scales. Discussion. Our findings were consistent with previous studies showing that environmental gradients and major rivers limit the distribution of Odonata communities, supporting that larger Amazonian rivers act as barriers for the dispersal of this group. In addition, the importance of habitat integrity indicates that intactness of riparian vegetation is an important filter shaping metacommunity structure of Amazonian stream Odonata.This work was supported by the Coordination for the Improvement of Higher Education Personnel—CAPES (120147/2016-01), Brazil National Council for Scientific and Technological Development—CNPq (303252/2013-8, 574008/2008-0, 305542/2010-9,478884/2008-7, 314523/2014-6), Brazilian Agriculture Research Corporation EMBRAPA (SEG 02.08.06.005.00), the UK Darwin Initiative (17023), The Nature Conservancy and the Natural Environment Research Council—NERC (NE/F01614X/1 and NE/G000816/1)

The ghosts of forests past and future : deforestation and botanical sampling in the Brazilian Amazon

The remarkable biodiversity of the Brazilian Amazon is poorly documented and threatened by deforestation. When undocumented areas become deforested, in addition to losing the fauna and flora, we lose the opportunity to know which unique species had occupied a habitat. Here we quantify such knowledge loss by calculating how much of the Brazilian Amazon has been deforested and will likely be deforested until 2050 without having its tree flora sufficiently documented. To this end, we analysed 399 147 digital specimens of nearly 6000 tree species in relation to official deforestation statistics and future deforestation scenarios. We find that by 2017, 30% of all the localities where tree specimens had been collected were mostly deforested. Some 300 000 km(2)(12%; 485 25 x 25 km grid cells) of the Brazilian Amazon had been deforested by 2017, without having a single tree specimen recorded. An additional 250 000-900 000 km(2)of severely under-collected rainforest will likely become deforested by 2050. If future tree sampling is to cover this area, sampling effort has to increase two- to six-fold. Nearly 255 000 km(2)or 7% of rainforest in the Brazilian Amazon is easily accessible but does yet but remain under-collected. Our study highlights how progressing deforestation increases the risk of losing undocumented species of a hyper-diverse tree flora.Peer reviewe

Metacommunity patterns of Amazonian Odonata: the role of environmental gradients and major rivers

Background We identified and classified damselfly (Zygoptera) and dragonfly (Anisoptera) metacommunities in Brazilian Amazonia, relating species distribution patterns to known biological gradients and biogeographical history. We expected a random distribution of both Zygoptera and Anisoptera within interfluves. At the Amazonian scale, we expected Anisoptera metacommunities to be randomly distributed due to their higher dispersal ability and large environmental tolerance. In contrast, we expected Zygoptera communities to exhibit a Clementsian pattern, limited by the large Amazonia rivers due to their low dispersal ability. Methods We used a dataset of 58 first-to-third order well-sampled streamlets in four Amazonian interfluves and applied an extension of the Elements of Metacommunity Structure (EMS) framework, in which we order Zygoptera and Anisoptera metacommunities by known spatial and biogeographic predictors. Results At the Amazonian scale, both Zygoptera and Anisoptera presented a Clementsian pattern, driven by the same environmental and biogeographical predictors, namely biogeographic region (interfluve), annual mean temperature, habitat integrity and annual precipitation. At the interfluve scale, results were less consistent and only partially support our hypothesis. Zygoptera metacommunities at Guiana and Anisoptera metacommunities at Tapajós were classified as random, suggesting that neutral processes gain importance at smaller spatial scales. Discussion Our findings were consistent with previous studies showing that environmental gradients and major rivers limit the distribution of Odonata communities, supporting that larger Amazonian rivers act as barriers for the dispersal of this group. In addition, the importance of habitat integrity indicates that intactness of riparian vegetation is an important filter shaping metacommunity structure of Amazonian stream Odonata

Methods to estimate aboveground wood productivity from long-term forest inventory plots

Forest inventory plots are widely used to estimate biomass carbon storage and its change over time. While there has been much debate and exploration of the analytical methods for calculating biomass, the methods used to determine rates of wood production have not been evaluated to the same degree. This affects assessment of ecosystem fluxes and may have wider implications if inventory data are used to parameterise biospheric models, or scaled to large areas in assessments of carbon sequestration. Here we use a dataset of 35 long-term Amazonian forest inventory plots to test different methods of calculating wood production rates. These address potential biases associated with three issues that routinely impact the interpretation of tree measurement data: (1) changes in the point of measurement (POM) of stem diameter as trees grow over time; (2) unequal length of time between censuses; and (3) the treatment of trees that pass the minimum diameter threshold (“recruits”). We derive corrections that control for changing POM height, that account for the unobserved growth of trees that die within census intervals, and that explore different assumptions regarding the growth of recruits during the previous census interval. For our dataset we find that annual aboveground coarse wood production (AGWP; in Mg ha−1 year−1 of dry matter) is underestimated on average by 9.2% if corrections are not made to control for changes in POM height. Failure to control for the length of sampling intervals results in a mean underestimation of 2.7% in annual AGWP in our plots for a mean interval length of 3.6 years. Different methods for treating recruits result in mean differences of up to 8.1% in AGWP. In general, the greater the length of time a plot is sampled for and the greater the time elapsed between censuses, the greater the tendency to underestimate wood production. We recommend that POM changes, census interval length, and the contribution of recruits should all be accounted for when estimating productivity rates, and suggest methods for doing this.European UnionUK Natural Environment Research CouncilGordon and Betty Moore FoundationCASE sponsorship from UNEP-WCMCRoyal Society University Research FellowshipERC Advanced Grant “Tropical Forests in the Changing Earth System”Royal Society Wolfson Research Merit Awar