Literature DB >> 16099202

Linking nursing care to medical diagnoses: heterogeneity of patient groups.

Lisanne van Beek1, William T F Goossen, Willem A van der Kloot.   

Abstract

AIM: The new budget system for Dutch hospitals makes use of patient groups that are highly homogeneous in terms of diagnosis and treatment combinations (diagnose behandeling combinaties (DBC)). These DBCs are the Dutch DRG variants. The DBC mainly concerns medical care; nursing care is almost regarded as a constant factor. In this study the DBC is linked to the nursing minimum data set for The Netherlands (NMDSN), to explore the degree of homogeneity in terms of nursing care for patient groups that are homogeneous in terms of the DBC.
METHOD: In nine Dutch hospitals, patient information was collected by means of the NMDSN. To answer the question, we performed a secondary data analysis on the NMDSN. First, groups were formed in terms of medical diagnoses as defined in the DBC. Next, explorative statistical analyses were used to form homogeneous groups in terms of nursing diagnoses. These groups were compared in terms of the nursing care interventions and in terms of medical diagnoses. FINDING: Some medical diagnoses seem to be homogeneous, others more heterogeneous in terms of nursing care. DISCUSSION AND
CONCLUSION: Limitations in the study design hinder a firm conclusion. However, the results discourage the use of the medical DBC for nursing care.

Entities:  

Mesh:

Year:  2005        PMID: 16099202     DOI: 10.1016/j.ijmedinf.2005.07.006

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  2 in total

1.  Cost assessment and price setting of inpatient care in The Netherlands. the DBC case-mix system.

Authors:  J B Oostenbrink; F F H Rutten
Journal:  Health Care Manag Sci       Date:  2006-08

2.  Physician nurse care: A new use of UMLS to measure professional contribution: Are we talking about the same patient a new graph matching algorithm?

Authors:  Andrew D Boyd; Karen Dunn Lopez; Camillo Lugaresi; Tamara Macieira; Vanessa Sousa; Sabita Acharya; Abhinaya Balasubramanian; Khawllah Roussi; Gail M Keenan; Yves A Lussier; Jianrong 'John' Li; Michel Burton; Barbara Di Eugenio
Journal:  Int J Med Inform       Date:  2018-02-09       Impact factor: 4.046

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.