Literature DB >> 24072039

DPC in acute-phase inpatient hospital care. Visualization of amount of nursing care provided and accessibility to nursing care.

C Matsumoto1, Y Uto, F Muranaga, I Kumamoto.   

Abstract

OBJECTIVE: The purpose of this study was to improve accessibility to nursing care by clarifying the relationship between patient characteristics and the amount of nursing care for the Diagnosis Procedure Combination system (DPC).
METHOD: The subjects included 528 lung cancer patients; 170 gastric cancer patients; and 91 colon cancer patients, who were hospitalized from July 1, 2008, to March 31, 2010, at a university hospital. The patients were categorized into groups according to factors that could affect the amount of nursing care. Next, the relationship between the patient characteristics and the amount of nursing care was analyzed. Then the results from this study were used to classify patient characteristics according to the patient type and the amount nursing care required.
RESULTS: The patient characteristics, which affected the amount of nursing care, varied according to each DPC code. The major factors affecting the amount of nursing care were whether the patient had received a surgical (under general anesthetics) treatment or a non-surgical treatment and the level of activities of daily living (ADL) of the hospitalized patients. For those who had received a surgical operation for colon cancer, the patient's age also affected the amount of nursing care.
CONCLUSIONS: The findings show that the method for the visualization of the amount of nursing care based on the classification of patient characteristics can be implemented into the electronic health record system. This method can then be used as a management tool to assure appropriate distribution of nursing resources.

Entities:  

Keywords:  Diagnosis procedure combination (DPC); hospital information system; nursing care; nursing management; patients’ characteristics

Mesh:

Year:  2013        PMID: 24072039     DOI: 10.3414/ME12-01-0090

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  1 in total

1.  Visualization of Data Regarding Infections Using Eye Tracking Techniques.

Authors:  Sunmoo Yoon; Bevin Cohen; Kenrick D Cato; Jianfang Liu; Elaine L Larson
Journal:  J Nurs Scholarsh       Date:  2016-04-07       Impact factor: 3.176

  1 in total

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