Variability of nursing care by APR-DRG and by severity of illness in a sample of nine Belgian hospitals.

BACKGROUND: As soon as Diagnosis related Groups (DRG) were introduced in many hospital financing systems, most nursing research revealed that DRG were not very homogeneous with regard to nursing care. However, few studies are based on All Patient refined Diagnosis related Groups (APR-DRGs) and few of them use recent data. Objectives of this study are: (1) to evaluate if nursing activity is homogeneous by APR-DRG and by severity of illness (SOI) (2) to evaluate the outlier's rate associated with the nursing activity and (3) to compare nursing cost homogeneity per DRG and SOI. METHODS: Study done in 9 Belgian hospitals on a selection of APR-DRG with more than 30 patients (7 638 inpatient stays). The evaluation of the homogeneity is based on coefficients of variation (CV). The 75th percentile + 1.5 × inter-quartile range was used to select high outliers. 25th percentile -1.5 × inter-quartile range was used to select low outliers. Nursing costs per ward were distributed on inpatient stays of each ward following two techniques (the LOS vs. the number of nursing care minutes per stay). RESULTS: The homogeneity of LOS by DRG and by SOI is relatively good (CV: 0.56). The homogeneity of the nursing activity by DRG is less good (CVs between 0.36 and 1.54) and is influenced by nursing activity outliers (high outliers' rate: 5.19%, low outliers' rate: 0.14%). The outlier's rate varies according to the studied variable. The high outliers' rate is higher for nursing activity than for LOS. The homogeneity of nursing costs is higher when costs are based on the LOS of patients than when based on minutes of nursing care (CVs between 0.26 and 1.46 for nursing costs based on LOS and between 0.49 and 2.04 for nursing costs based on minutes of nursing care). CONCLUSIONS: It is essential that the calculation of nursing cost by stay and by DRG for hospital financing purposes was based on nursing activity data, that more reflect resources used in wards, and not on LOS data. The only way to obtain this information is the generalization of computerized nursing files.

Development and validation of nursing resource weights for the Belgian Nursing Minimum Dataset in general hospitals: a Delphi questionnaire survey approach.

BACKGROUND: Internationally, nursing is not well represented in hospital financing systems. In Belgium a nursing weight system exists to adjust budget allocation for differences in nurse staffing requirements, but there is a need for revision. Arguments include the availability of a nursing minimum dataset and the adverse consequences of the current historically based nursing weight system. OBJECTIVES: The development and validation of nursing resource weights for the revised Belgium nursing minimum dataset (NMDS). DESIGN: Two independent cross sectional Delphi-surveys. SETTING AND PARTICIPANTS: A convenience sample of 222 head nurses from 69 Belgian hospitals participated in the cross sectional survey methods. To assess validity 112 patient case records from 61 nursing wards of 35 Belgian general hospitals representing general, surgical, pediatric, geriatric and intensive care were selected. METHODS: Nursing resource weights were constructed based on Delphi survey results by NMDSII intervention. The patient case Delphi survey results were used as the primary source for validation. A series of additional validation measures were calculated, based on the different patient classification systems. Finally, three validated nursing resource weighting systems were compared to the constructed NMDSII weighting system: the use of 'Closon', 'Ghent' and WIN weights. RESULTS: A coherent set of nursing resource weights was developed. The comparison of nurse resource weights, based on the survey per NMDS intervention versus the survey on patient cases, yielded high correlations: r=0.74 to r=0.97 (p<0.01) between three case rating questions, as an indication of reliability in terms of internal consistency, and r=0.90 (p<0.01) between summed intervention weights and patient case weights, as an indication of criterion validity in terms of concurrent validity. Other concurrent validity measures based on summed intervention weights versus patient classification dependency weights showed a correlation ranging from r=0.14 to r=0.74. The correlation of summed intervention weights with the Closon, Ghent and WIN weights ranged from r=0.93 to r=0.96 (p<0.01), as a third indication of concurrent validity. CONCLUSIONS: A system of valid nursing resource weights has been developed. The system should be further validated within an international context.

Adjusting for nursing care case mix in hospital reimbursement: a review of international practice.

The purpose of this study was to examine and review the different ways in which nursing care can be accounted for in a general hospital reimbursement system. The study is based on a literature review and a survey of international experts. It provides a typology of nursing care adjustment methods, using current and past practices of 14 Western countries as key examples. The results of our review indicate that it is necessary to take the variability of nursing care within DRGs into account, not from a cost-accounting perspective, but from a management perspective in terms of correct resource allocation. However, further investigation of these complex relationships is urgently needed.

Revision of the Belgian Nursing Minimum Dataset: From data to information.

The Ministry of Public Health commissioned a research project to the Catholic University of Leuven and the University Hospital of Liège to revise the Belgian Nursing Minimum Dataset (B-NMDS). The study started in 2000 and will end with the implementation of the revised B-NMDS in January 2007. The study entailed four major phases. The first phase involved the development of a conceptual framework based on a literature review and secondary data analysis. The second phase focused on language development and development of a data collection tool. The third phase focused on data collection and validation of the new tool. In the fourth phase the validity and reliability of the dataset was tested. The new dataset is without avail if it is not leading to new information. Four applications of the dataset has been defined from the beginning: evaluation of the appropriateness of stay (AEP) in the hospital, nurse staffing, hospital financing and quality management. The aim of this paper is to describe how the B-NMDS can contribute to each of these applications.