Literature DB >> 27332355

Using a Text-Mining Approach to Evaluate the Quality of Nursing Records.

Hsiu-Mei Chang1, Shwu-Fen Chiou2, Hsiu-Yun Liu1, Hui-Chu Yu1.   

Abstract

Nursing records in Taiwan have been computerized, but their quality has rarely been discussed. Therefore, this study employed a text-mining approach and a cross-sectional retrospective research design to evaluate the quality of electronic nursing records at a medical center in Northern Taiwan. SAS Text Miner software Version 13.2 was employed to analyze unstructured nursing event records. The results show that SAS Text Miner is suitable for developing a textmining model for validating nursing records. The sensitivity of SAS Text Miner was approximately 0.94, and the specificity and accuracy were 0.99. Thus, SAS Text Miner software is an effective tool for auditing unstructured electronic nursing records.

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Year:  2016        PMID: 27332355

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

Review 1.  Resuscitation after global brain ischemia-anoxia.

Authors:  P Safar; A Bleyaert; E M Nemoto; J Moossy; J V Snyder
Journal:  Crit Care Med       Date:  1978 Jul-Aug       Impact factor: 9.296

2.  A text-mining approach to obtain detailed treatment information from free-text fields in population-based cancer registries: A study of non-small cell lung cancer in California.

Authors:  Frances B Maguire; Cyllene R Morris; Arti Parikh-Patel; Rosemary D Cress; Theresa H M Keegan; Chin-Shang Li; Patrick S Lin; Kenneth W Kizer
Journal:  PLoS One       Date:  2019-02-22       Impact factor: 3.240

  2 in total

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