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KMID : 0367020000120040507
Journal of Korean Academic of Adult Nursing
2000 Volume.12 No. 4 p.507 ~ p.516
Application fo NANDA and HHCC to Classification of Nursing Diagnosis in a Hospital-Based Home Health Care
Lee Jin-Kyung

Park Hyeoun-Ae
Abstract
Application of NANDA and HHCC to Classification of Nursing Diagnosis in a Hospital-Based Home Health Care This study examines that Noith American Nursing Diagnosis Association(NANDA) and Home Health Care Classification(HHCC) is appropriate to classify home health care client¡¯s nursing problems and suggests a modified nursing diagnosis classifcation system. Two hundred and forty-nine clients¡¯ records at a general hospital were reviewed and nursing problems were diagnosed according to each classification system. Results of this study are as follows. The major client¡¯s medical diagnosis are pregnancy, childbirth and puerperium. malignant neoplasm, and benign neoplasm. Of four hundred and sixty-three nursing problems, all nursing problems made a diagnos according to HHCC, while three hundred and eighty-five made a diagnosis according to NANDA. The HHCC diagnosis included 78 more nursing problems than NANDA The discrepancy in the results may indicate a significant advantage to HHCC diagnosis because HHCC nomenclature was created empirically from hard data. However, this may be due to limitations in the data collection method so determination of which classification system is more useful is difficult to judge. However, nursing components of the HHCC are more concrete and clearer than human response patterns of the NANDA. Also the HHCC facilitates the documentation of Patient care by computer, while using a conceptual framework consisting of 20 Care Components based on the nursing process: assessment, diagnosis, outcome identification, planning, implementation and evaluation. Accordingly, the practical application of HHCC is more useful than NANDA. Limitations of this study include a retrospective data collecting method and universality of samples. Further research for various samples that use prospective data collection method is recommended.
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