Data Mining Nursing Care Plans of End-of-Life Patients: A Study to Improve Healthcare Decision Making

作者：Almasalha Fadi; Xu Dianhui; Keenan Gail M^*; Khokhar Ashfaq; Yao Yingwei; Chen Yu C; Johnson Andy; Ansari R; Wilkie Diana J

来源：International Journal of Nursing Knowledge, 2013, 24(1): 15-24.

DOI：10.1111/j.2047-3095.2012.01217.x

• Data mining
• electronic health record
• end-of-life hospital care
• pain
• plan of care

PURPOSE: To reveal hidden patterns and knowledge present in nursing care information documented with standardized nursing terminologies on end-of-life (EOL) hospitalized patients. METHOD: 596 episodes of care that included pain as a problem on a patient%26apos;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 (%26lt;72hr) are less likely (p%26lt;.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.

• 出版日期2013-2