PubMed Health⌕ Search

PubMed · 10175428

Data mining: a strategy for knowledge development and structure in nursing practice.

Abstract

Data mining is an emerging technique used more widely by the business world than the world of nursing and health care. However, this strategy can be helpful for improving the quality of decision making by clinicians and health care administrators. This paper addresses the concepts and techniques of data mining that could be useful for practicing nurses as well as nurse administrators. Data mining can be an important tool for the development of nursing knowledge and knowledge structures. An example of the use of the technique in an inpatient setting is provided and insights from the process are discussed.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

L R Eriksen, J P Turley, D Denton, S Manning. 1997. Data mining: a strategy for knowledge development and structure in nursing practice.. https://pubmed.ncbi.nlm.nih.gov/10175428/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Clustering individuals using INMTD: a novel versatile multi-view embedding framework integrating omics and imaging data.

MOTIVATION: Combining omics and images can lead to a more comprehensive clustering of individuals than classic single-view approaches. Among the various approaches for multi-view clustering, nonnegative matrix tri-factorization (NMTF) and nonnegative Tucker decomposition (NTD) are advantageous in learning low-rank embeddings with promising interpretability. Besides, there is a need to handle unwanted drivers of clusterings (i.e. confounders). RESULTS: In this work, we introduce a novel multi-view clustering method based on NMTF and NTD, named INMTD, which integrates omics and 3D imaging data to derive unconfounded subgroups of individuals. According to the adjusted Rand index, INMTD outperformed other clustering methods on a synthetic dataset with known clusters. In the application to real-life facial-genomic data, INMTD generated biologically relevant embeddings for individuals, genetics, and facial morphology. By removing confounded embedding vectors, we derived an unconfounded clustering with better internal and external quality; the genetic and facial annotations of each derived subgroup highlighted distinctive characteristics. In conclusion, INMTD can effectively integrate omics data and 3D images for unconfounded clustering with biologically meaningful interpretation. AVAILABILITY AND IMPLEMENTATION: INMTD is freely available at https://github.com/ZuqiLi/INMTD.

Cluster Analysis↗

Fuzzy species among recombinogenic bacteria.

BACKGROUND: It is a matter of ongoing debate whether a universal species concept is possible for bacteria. Indeed, it is not clear whether closely related isolates of bacteria typically form discrete genotypic clusters that can be assigned as species. The most challenging test of whether species can be clearly delineated is provided by analysis of large populations of closely-related, highly recombinogenic, bacteria that colonise the same body site. We have used concatenated sequences of seven house-keeping loci from 770 strains of 11 named Neisseria species, and phylogenetic trees, to investigate whether genotypic clusters can be resolved among these recombinogenic bacteria and, if so, the extent to which they correspond to named species. RESULTS: Alleles at individual loci were widely distributed among the named species but this distorting effect of recombination was largely buffered by using concatenated sequences, which resolved clusters corresponding to the three species most numerous in the sample, N. meningitidis, N. lactamica and N. gonorrhoeae. A few isolates arose from the branch that separated N. meningitidis from N. lactamica leading us to describe these species as 'fuzzy'. CONCLUSION: A multilocus approach using large samples of closely related isolates delineates species even in the highly recombinogenic human Neisseria where individual loci are inadequate for the task. This approach should be applied by taxonomists to large samples of other groups of closely-related bacteria, and especially to those where species delineation has historically been difficult, to determine whether genotypic clusters can be delineated, and to guide the definition of species.

Cluster Analysis↗

A randomized controlled trial of two strategies to implement active sick leave for patients with low back pain.

STUDY DESIGN: Cluster randomized controlled trial. OBJECTIVE: To evaluate the effectiveness of two strategies to improve the use of active sick leave (ASL) for patients with low back pain. SUMMARY OF BACKGROUND DATA: ASL is a public sickness benefit scheme offered to promote early return to modified work for temporarily disabled workers. It was poorly used, and the authors designed two community interventions to strengthen the implementation of ASL based on the results of a study of barriers to use among back pain patients, employers, general practitioners (GPs), and local National Insurance Administration staff. METHODS: Sixty-five municipalities in three counties in Norway, randomly assigned to a passive intervention, a proactive intervention, or a control group. The interventions were targeted at patients on sick leave for low back pain for more than 16 days (n = 6176), their GPs, employers, and local insurance officers. The passive intervention included reminders about ASL on the sick leave form that GPs must complete, a standard agreement to facilitate ASL, targeted information, and a desktop summary for GPs of clinical practice guidelines for low back pain, emphasizing the importance of advice to stay active. The proactive intervention included these elements plus a resource person to facilitate the use of ASL and a continuing education workshop for GPs. The main outcome measure reported here is the proportion of eligible patients that used ASL. RESULTS: ASL was used significantly more in the proactive intervention municipalities (17.7%) compared with the passive intervention and control municipalities (11.5%, P = 0.018). CONCLUSIONS: A passive intervention that addressed identified barriers to the use of ASL did not increase its use. Although modest, a proactive intervention did increase its use. The main impact of the intervention was through direct contact and motivating telephone calls to patients. To the extent that GPs' practice was changed, it was either patient mediated or by patients bypassing their GP.

Cluster Analysis↗