Data Mining Nursing Care Plans of End‐of‐Life Patients: A Study to Improve Healthcare Decision Making. Issue 1 (17th August 2012)

• Record Type: Journal Article
• Authors: Almasalha, Fadi; Xu, Dianhui; Keenan, Gail M.; Khokhar, Ashfaq; Yao, Yingwei; Chen, Yu‐C.; Johnson, Andy; Ansari, R.; Wilkie, Diana J.
• Is Part Of: International Journal of Nursing Knowledge. Volume 24:Issue 1(2013:Feb.)
• Page Start: 15
• Page End: 24
• Publication Date: 2012-08-17
• Subjects: Nursing diagnosis -- Periodicals; Nursing -- Terminology -- Periodicals; Nursing -- Practice -- Periodicals; 616.075
• DOI: 10.1111/j.2047-3095.2012.01217.x
• Languages: English
• ISSNs: 2047-3087

Abstract

<abstract abstract-type="main" xml:lang="en"> <title> <x xml:space="preserve">Abstract</x> </title> <p> <bold>PURPOSE: </bold> To reveal hidden patterns and knowledge present in nursing care information documented with standardized nursing terminologies on end‐of‐life (EOL) hospitalized patients.</p> <p> <bold>METHOD: </bold> 596 episodes of care that included pain as a problem on a patient's care plan were examined using statistical and data mining tools. The data were extracted from the Hands‐On Automated Nursing Data System database of nursing care plan episodes (<italic>n</italic> = 40, 747) coded with NANDA‐I, Nursing Outcomes Classification, and Nursing Intervention Classification (NNN) terminologies. System episode data (episode = care plans updated at every hand‐off on a patient while staying on a hospital unit) had been previously gathered in eight units located in four different healthcare facilities (total episodes = 40, 747; EOL episodes = 1, 425) over 2 years and anonymized prior to this analyses.</p> <p> <bold>RESULTS: </bold> Results show multiple discoveries, including EOL patients with hospital stays (&lt;72 hr) are less likely (<italic>p</italic> &lt; .005) to meet the pain relief goals compared with EOL patients with longer hospital stays.</p> <p> <bold>CONCLUSIONS: </bold> The study demonstrates some major benefits of systematically integrating NNN into electronic health records.</p> </abstract>