title: Data mining nursing care plans of end-of-life patients: a study to improve healthcare decision making.
abstract: OBJECTIVE
  To reveal hidden patterns and knowledge present in nursing care information documented with standardized nursing terminologies on end-of-life (EOL) hospitalized patients.
  
  
  METHODS
  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 (n = 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.
  
  
  RESULTS
  Results show multiple discoveries, including EOL patients with hospital stays (<72 hr) are less likely (p < .005) to meet the pain relief goals compared with EOL patients with longer hospital stays.
  
  
  CONCLUSIONS
  The study demonstrates some major benefits of systematically integrating NNN into electronic health records.
authors: The Applied Science Private University, Amman, Jordan.
authors: Fadi
authors: F
authors: Almasalha
authors: Dianhui
authors: D
authors: Xu
authors: Gail M
authors: GM
authors: Keenan
authors: Ashfaq
authors: A
authors: Khokhar
authors: Yingwei
authors: Y
authors: Yao
authors: Yu-C
authors: YC
authors: Chen
authors: Andy
authors: A
authors: Johnson
authors: R
authors: R
authors: Ansari
authors: Diana J
authors: DJ
authors: Wilkie
mesh_terms: D001331:Automation; D003659:Decision Making, Organizational; D016247:Information Storage and Retrieval; D009732:Nursing Care; D010347:Patient Care Planning; D013727:Terminal Care