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

被引:33
作者
Almasalha, Fadi [1 ]
Xu, Dianhui [2 ]
Keenan, Gail M. [4 ,8 ]
Khokhar, Ashfaq [5 ,8 ]
Yao, Yingwei [4 ,8 ]
Chen, Yu-C. [3 ]
Johnson, Andy [6 ,8 ]
Ansari, R. [7 ,8 ]
Wilkie, Diana J. [4 ]
机构
[1] Appl Sci Private Univ, Amman, Jordan
[2] Litepoint Co, Sunnyvale, CA USA
[3] Pixar Animat Studios, Emeryville, CA USA
[4] Univ Illinois, Coll Nursing, Chicago, IL 60607 USA
[5] Univ Illinois, Dept Elect & Comp Engn, Chicago, IL USA
[6] Univ Illinois, Dept Comp Sci, Chicago, IL USA
[7] Univ Illinois, Dept Engn, Chicago, IL USA
[8] Univ Illinois, Chicago, IL USA
基金
美国国家卫生研究院;
关键词
Data mining; electronic health record; end-of-life hospital care; pain; plan of care; KNOWLEDGE DISCOVERY; BAYESIAN NETWORKS; ASSOCIATIONS;
D O I
10.1111/j.2047-3095.2012.01217.x
中图分类号
R47 [护理学];
学科分类号
1011 ;
摘要
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'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 (<72hr) 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.
引用
收藏
页码:15 / 24
页数:10
相关论文
共 37 条
[1]   Record-keeping and routine nursing practice: the view from the wards [J].
Allen, D .
JOURNAL OF ADVANCED NURSING, 1998, 27 (06) :1223-1230
[2]  
[Anonymous], 1996, ADV KNOWLEDGE DISCOV
[3]  
[Anonymous], NURS DIAGN DEF CLASS
[4]   Data mining a diabetic data warehouse [J].
Breault, JL ;
Goodall, CR ;
Fos, PJ .
ARTIFICIAL INTELLIGENCE IN MEDICINE, 2002, 26 (1-2) :37-54
[5]  
Bulechek G., 2007, NURSING INTERVENTION, V5th
[6]  
Cheung R., 2002, Policy, Politics, Nursing Practice, V3, P248
[7]   Effect of a Quality-Improvement Intervention on End-of-Life Care in the Intensive Care Unit A Randomized Trial [J].
Curtis, J. Randall ;
Nielsen, Elizabeth L. ;
Treece, Patsy D. ;
Downey, Lois ;
Dotolo, Danae ;
Shannon, Sarah E. ;
Back, Anthony L. ;
Rubenfeld, Gordon D. ;
Engelberg, Ruth A. .
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2011, 183 (03) :348-355
[8]  
Duan L., 2008, P 3 INFORMS WORKSH D
[9]   Automating the extraction of data from HTML']HTML tables with unknown structure [J].
Embley, DW ;
Tao, C ;
Liddle, SW .
DATA & KNOWLEDGE ENGINEERING, 2005, 54 (01) :3-28
[10]   Data mining issues and opportunities for building nursing knowledge [J].
Goodwin, L ;
VanDyne, M ;
Lin, S ;
Talbert, S .
JOURNAL OF BIOMEDICAL INFORMATICS, 2003, 36 (4-5) :379-388