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김형순 ( Kim Hyoung-Soon ) - Catholic University Seoul St. Mary’s Hospital
박현숙 ( Park Hyun-Sook ) - Catholic University Seoul St. Mary’s Hospital
정현숙 ( Chung Hyun-Sook ) - Catholic University Seoul St. Mary’s Hospital
김미경 ( Kim Mi-Kyoung ) - Catholic University Seoul St. Mary’s Hospital
박은영 ( Park Eun-Young ) - Catholic University Seoul St. Mary’s Hospital
김동연 ( Kim Dong-Yeon ) - Catholic University Seoul St. Mary’s Hospital
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Abstract
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Purpose: The aim of this retrospective study was to analyze spiritual nursing diagnosis records using clinical big data to learn spiritual nursing activities and to help improve spiritual nursing practice in the future.
Methods: Eleven types of spiritual nursing diagnoses were applied to 422,733 patients who were admitted to a certified tertiary hospital between April 2011 and September 2018. Descriptive statistics and x2 tests were used to analyze the characteristics of the patients and nursing records.
Results: There were 51,423 (12.2%) patients who were diagnosed through spiritual nursing. The patients received a total of 59,925 spiritual nursing diagnoses, including duplicate diagnoses. The most common spiritual nursing diagnoses was anxiety (58.4%), followed by dying (16.5%) and helplessness (7.6%) over the past eight years. Spiritual nursing data have a tense and anxious appearance, decreased activity, and decreased speech. Spiritual care plans and interventions have been used to encourage, listen, and express interest in expressing emotions.
Conclusion: Through an analysis of big data, this study found the frequency of various spiritual nursing diagnoses, care plans, and interventions. Improving nurses’ perceptions of the spiritual nursing process, spiritual care education, and ncouraging the performance of spiritual care may be an effective pathway to enhance the spiritual care competence
of nurses.
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KeyWords
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영성, 간호수행, 간호기록, 간호진단, 빅데이터
Spirituality, Nursing care, Nursing record, Nursing diagnosis, Big data
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원문 및 링크아웃 정보
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등재저널 정보
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