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임상 빅데이터를 이용한 영적간호진단 적용 현황 분석

Analysis of the Present Condition of Spiritual Nursing Diagnosis using Clinical Big Data

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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 encouraging the performance of spiritual care may be an effective pathway to enhance the spiritual care competence of nurses.

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