Classifying nursing organization in wards in Norwegian hospitals: self-identification versus observation

<p>Abstract</p> <p>Background</p> <p>The organization of nursing services could be important to the quality of patient care and staff satisfaction. However, there is no universally accepted nomenclature for this organization. The objective of the current study was to classify general hospital wards based on data describing organizational practice reported by the ward nurse managers, and then to compare this classification with the name used in the wards to identify the organizational model (self-identification).</p> <p>Methods</p> <p>In a cross-sectional postal survey, 93 ward nurse managers in Norwegian hospitals responded to questions about nursing organization in their wards, and what they called their organizational models. K-means cluster analysis was used to classify the wards according to the pattern of activities attributed to the different nursing roles and discriminant analysis was used to interpret the solutions. Cross-tabulation was used to validate the solutions and to compare the classification obtained from the cluster analysis with that obtained by self-identification. The bootstrapping technique was used to assess the generalizability of the cluster solution.</p> <p>Results</p> <p>The cluster analyses produced two alternative solutions using two and three clusters, respectively. The three-cluster solution was considered to be the best representation of the organizational models: 32 team leader-dominated wards, 23 primary nurse-dominated wards and 38 wards with a hybrid or mixed organization. There was moderate correspondence between the three-cluster solution and the models obtained by self-identification. Cross-tabulation supported the empirical classification as being representative for variations in nursing service organization. Ninety-four per cent of the bootstrap replications showed the same pattern as the cluster solution in the study sample.</p> <p>Conclusions</p> <p>A meaningful classification of wards was achieved through an empirical cluster solution; this was, however, only moderately consistent with the self-identification. This empirical classification is an objective approach to variable construction and can be generally applied across Norwegian hospitals. The classification procedure used in the study could be developed into a standardized method for classifying hospital wards across health systems and over time.</p

On the phylogeny of Mustelidae subfamilies: analysis of seventeen nuclear non-coding loci and mitochondrial complete genomes

<p>Abstract</p> <p>Background</p> <p>Mustelidae, as the largest and most-diverse family of order Carnivora, comprises eight subfamilies. Phylogenetic relationships among these Mustelidae subfamilies remain argumentative subjects in recent years. One of the main reasons is that the mustelids represent a typical example of rapid evolutionary radiation and recent speciation event. Prior investigation has been concentrated on the application of different mitochondrial (mt) sequence and nuclear protein-coding data, herein we employ 17 nuclear non-coding loci (>15 kb), in conjunction with mt complete genome data (>16 kb), to clarify these enigmatic problems.</p> <p>Results</p> <p>The combined nuclear intron and mt genome analyses both robustly support that Taxidiinae diverged first, followed by Melinae. Lutrinae and Mustelinae are grouped together in all analyses with strong supports. The position of Helictidinae, however, is enigmatic because the mt genome analysis places it to the clade uniting Lutrinae and Mustelinae, whereas the nuclear intron analysis favores a novel view supporting a closer relationship of Helictidinae to Martinae. This finding emphasizes a need to add more data and include more taxa to resolve this problem. In addition, the molecular dating provides insights into the time scale of the origin and diversification of the Mustelidae subfamilies. Finally, the phylogenetic performances and limits of nuclear introns and mt genes are discussed in the context of Mustelidae phylogeny.</p> <p>Conclusion</p> <p>Our study not only brings new perspectives on the previously obscured phylogenetic relationships among Mustelidae subfamilies, but also provides another example demonstrating the effectiveness of nuclear non-coding loci for reconstructing evolutionary histories in a group that has undergone rapid bursts of speciation.</p

Variabilidade da prática clínica em enfermagem, uma revisão integrativa

Objetivo: El objetivo de esta revisión de la literatura es examinar qué se ha publicado sobre variabilidad de la práctica clínica desde el enfoque de la enfermería. Métodos: Se realizó una búsqueda bibliográfica en las principales bases de datos internacionales seleccionando aquellos trabajos más relevantes. Resultados: Los resultados se han agrupado en 5 grupos: estudios sobre variaciones respecto a guías y protocolos, estudios que analizan práctica enfermera y de otros profesionales sanitarios, variaciones en procedimientos y cuidados de enfermería, variaciones en la práctica entre enfermeras y médicos y estudios que relacionan la variabilidad con características de profesionales, unidades o centros sanitarios. Conclusión: La mayoría de los trabajos encontrados se han limitado a mostrar la existencia de variabilidad pero pocos han buscado variables que predigan ésta. Futuras investigaciones deberían centrarse en la búsqueda de variables predictivas de la variabilidad para hacer frente a las variaciones injustificadas que se detecten.Objective: The objective of this literature review was to examine what has been published about variability in clinical practice from the focus of nursing. Methods: We performed a literature search in the principal international databases, selecting those most relevant works. Results: The results were clustered into five groups: studies about variations with respect to guidelines and protocols; studies that analyze nursing practice and that of other health professionals; variations in procedures and nursing care; variations in practice between nurses and physicians; and studies that related variability with characteristics of professionals, units or healthcare centers. Conclusion: The majority of papers found were limited to showing the existence of variability, but few sought variables that predicted it. Future investigations should focus on finding predictors of variability to address unjustified variations that are detected