Dataset Information

Mapping patient safety: a large-scale literature review using bibliometric visualisation techniques.

ABSTRACT:

Background

The amount of scientific literature available is often overwhelming, making it difficult for researchers to have a good overview of the literature and to see relations between different developments. Visualisation techniques based on bibliometric data are helpful in obtaining an overview of the literature on complex research topics, and have been applied here to the topic of patient safety (PS).

Methods

On the basis of title words and citation relations, publications in the period 2000-2010 related to PS were identified in the Scopus bibliographic database. A visualisation of the most frequently cited PS publications was produced based on direct and indirect citation relations between publications. Terms were extracted from titles and abstracts of the publications, and a visualisation of the most important terms was created. The main PS-related topics studied in the literature were identified using a technique for clustering publications and terms.

Results

A total of 8480 publications were identified, of which the 1462 most frequently cited ones were included in the visualisation. The publications were clustered into 19 clusters, which were grouped into three categories: (1) magnitude of PS problems (42% of all included publications); (2) PS risk factors (31%) and (3) implementation of solutions (19%). In the visualisation of PS-related terms, five clusters were identified: (1) medication; (2) measuring harm; (3) PS culture; (4) physician; (5) training, education and communication. Both analysis at publication and term level indicate an increasing focus on risk factors.

Conclusions

A bibliometric visualisation approach makes it possible to analyse large amounts of literature. This approach is very useful for improving one's understanding of a complex research topic such as PS and for suggesting new research directions or alternative research priorities. For PS research, the approach suggests that more research on implementing PS improvement initiatives might be needed.

SUBMITTER: Rodrigues SP

PROVIDER: S-EPMC3963077 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mapping patient safety: a large-scale literature review using bibliometric visualisation techniques.

Rodrigues S P SP van Eck N J NJ Waltman L L Jansen F W FW

BMJ open 20140313 3

<h4>Background</h4>The amount of scientific literature available is often overwhelming, making it difficult for researchers to have a good overview of the literature and to see relations between different developments. Visualisation techniques based on bibliometric data are helpful in obtaining an overview of the literature on complex research topics, and have been applied here to the topic of patient safety (PS).<h4>Methods</h4>On the basis of title words and citation relations, publications in ...[more]

PMID: 24625640

Similar Datasets

Project description:BACKGROUND: Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network. RESULTS: We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. CONCLUSIONS: Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level.

Project description:BackgroundThere are many clinical prediction models (CPMs) available to inform treatment decisions for patients with cardiovascular disease. However, the extent to which they have been externally tested, and how well they generally perform has not been broadly evaluated.MethodsA SCOPUS citation search was run on March 22, 2017 to identify external validations of cardiovascular CPMs in the Tufts Predictive Analytics and Comparative Effectiveness CPM Registry. We assessed the extent of external validation, performance heterogeneity across databases, and explored factors associated with model performance, including a global assessment of the clinical relatedness between the derivation and validation data.ResultsWe identified 2030 external validations of 1382 CPMs. Eight hundred seven (58%) of the CPMs in the Registry have never been externally validated. On average, there were 1.5 validations per CPM (range, 0-94). The median external validation area under the receiver operating characteristic curve was 0.73 (25th-75th percentile [interquartile range (IQR)], 0.66-0.79), representing a median percent decrease in discrimination of -11.1% (IQR, -32.4% to +2.7%) compared with performance on derivation data. 81% (n=1333) of validations reporting area under the receiver operating characteristic curve showed discrimination below that reported in the derivation dataset. 53% (n=983) of the validations report some measure of CPM calibration. For CPMs evaluated more than once, there was typically a large range of performance. Of 1702 validations classified by relatedness, the percent change in discrimination was -3.7% (IQR, -13.2 to 3.1) for closely related validations (n=123), -9.0 (IQR, -27.6 to 3.9) for related validations (n=862), and -17.2% (IQR, -42.3 to 0) for distantly related validations (n=717; P<0.001).ConclusionsMany published cardiovascular CPMs have never been externally validated, and for those that have, apparent performance during development is often overly optimistic. A single external validation appears insufficient to broadly understand the performance heterogeneity across different settings.

Dataset Information

Mapping patient safety: a large-scale literature review using bibliometric visualisation techniques.

Background

Methods

Results

Conclusions

Publications

Mapping patient safety: a large-scale literature review using bibliometric visualisation techniques.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets