Belgian Nursing Minimum Dataset Research Articles

Validation of standard times and influencing factors during the development of the Workload Indicator for Nursing

A tool to assist in optimal allocation of available nursing resources is of paramount importance. The goals of this study were as follows: (1) to determine whether the standard time values of the Belgian Nursing Minimum Dataset are a valid basis for the development of a Workload Indicator for Nursing; (2) to quantify the impact of factors that most influence nursing workload; and (3) to examine the cross-impact of items of the Belgian Nursing Minimum Dataset. This research project is a prospective observational study with exploratory aspects. The data for this prospective study were collected during September 2010 from a convenience sample of 23 nursing units in four hospitals in Belgium. The data collection included three parts: (1) the registration of the items of the Belgian Nursing Minimum Dataset; (2) the amount of time committed to direct patient care; and (3) analysis of variables, which influence the nursing workload at patient and unit level. The correlation coefficients for the sum of Direct and Indirect Patient Care and the Workload Indicator for Nursing-score of the surgical, internal medicine and intensive care units were 0·85, 0·88 and 0·89 respectively. Significant differences in standard time utilization for nursing activities at the patient level are directly related to the level of mobility assistance required. Units needing significantly more time for Direct and Indirect Patient Care than predicted by the Workload Indicator for Nursing-score had a higher mean number of complex nursing activities per patient. The high correlation coefficients between the total time utilized for direct patient care and the WiN-score indicate that the standard time values of the Belgian Nursing Minimum Dataset are valid.

Determination of standard times of nursing activities based on a Nursing Minimum Dataset

This paper is a report of a study conducted to determine the standard time per nursing activity and the proportion of nursing time covered by the nursing activities of the Belgian Nursing Minimum Dataset compared to the total time of a nurse shift, and to evaluate the correlation between hospital size and standard times of nursing activities. Because of a shrinking workforce and rising workload, nursing managers need tools that help them to allocate their staff to the wards. Such tools should be based on objective time measurements. The study was performed in surgical, internal medicine and elder care wards in an acute hospital care setting. In the first phase, a two-round Delphi-procedure was used to operationalize the definitions of nursing activities. In the second phase, the standard time for each nursing activity was determined, based on data collected over a 6-month period during 2006-2007. A combination of 13,292 work sampling observations by external observers, 3000 recordings of direct time measurement by self-recording and subjective time assessments yielded times that were used to analyse the duration of the nursing activities. A standard time for 102 nursing activities was established. The coverage of the Belgian Nursing Minimum Dataset in the surgical, internal medicine and elder care wards was 47.5%, 46.4% and 51.0% respectively. The Belgian Nursing Minimum Dataset was found to cover almost 70% of direct and indirect nursing care. Further research is needed to assess the impact on the standard times of nursing activities of inefficient organizational structures and different cultural interpretations of the way an activity is conducted.

Using Nursing Interventions Classification as a Framework to Revise the Belgian Nursing Minimum Data Set

To develop the revised Belgian nursing minimum data set (B-NMDS). The Nursing Interventions Classification (NIC, 2nd edition) was used as a framework. Six expert nurse panels (cardiology, oncology, intensive care, pediatrics, geriatrics, chronic care) were consulted. Seventy-nine panelists completed standardized e-mail questionnaires and discussed results in face-to-face meetings. We initially selected 256 of 433 NIC interventions. After panel discussions, plenary meetings, and pretesting, the revised B-NMDS (alpha version) contained 79 items covering 22 NIC classes and 196 NIC interventions. Consensus building promoted acceptance of the B-NMDS, while the NIC provided a good theoretical basis and guaranteed international comparability. The revised B-NMDS instrument can be used to visualize nursing activities in different applications (e.g., financing, staffing allocation).

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.

Benchmarking nurse staffing levels: the development of a nationwide feedback tool

This paper is a report of a study to develop a methodology that corrects nurse staffing for nursing care intensity in a way that allows nationwide benchmarking of nurse staffing data. Although nurse workload measurement systems are recognized to be informative in nurse staffing decisions, they are rarely used. When these systems are used, however, it is only possible to compare units within hospitals, because currently available instruments are not standardized for comparisons beyond hospital boundaries. The Belgian Nursing Minimum Dataset (B-NMDS) contains uniformly measured data about the intensity of nursing care and nurse staffing levels for all hospitals in Belgium. We conducted a retrospective multilevel analysis of the B-NMDS for the year 2003. The sample included 690,258 inpatient days for 298,691 patients, recorded from 1637 acute care nursing units in 115 hospitals. We corrected the number of nursing staff by using different covariates available in the B-NMDS: intensity of nursing care, type of day (week vs. weekend), service type (general vs. intensive) and hospital type (academic vs. general). The multilevel approach allowed us to explain about 70% of the variability in the number of nursing staff per nursing unit using hospital type (P = 0.0053); intensity of nursing care (P < 0.0001) and service type (P < 0.0001) as the only covariates. The feedback tool we developed can inform nurse managers and policymakers about nursing intensity-adjusted nurse staffing levels according to different benchmarks. Our study demonstrates that investing in large nursing datasets is appropriate for the international nursing community.

Nurse staffing and patient outcomes in Belgian acute hospitals: Cross-sectional analysis of administrative data

BackgroundStudies have linked nurse staffing levels (number and skill mix) to several nurse-sensitive patient outcomes. However, evidence from European countries has been limited. ObjectivesThis study examines the association between nurse staffing levels (i.e. acuity-adjusted Nursing Hours per Patient Day, the proportion of registered nurses with a Bachelor's degree) and 10 different patient outcomes potentially sensitive to nursing care. Design-setting-participantsCross-sectional analyses of linked data from the Belgian Nursing Minimum Dataset (general acute care and intensive care nursing units: n=1403) and Belgian Hospital Discharge Dataset (general, orthopedic and vascular surgery patients: n=260,923) of the year 2003 from all acute hospitals (n=115). MethodsLogistic regression analyses, estimated by using a Generalized Estimation Equation Model, were used to study the association between nurse staffing and patient outcomes. ResultsThe mean acuity-adjusted Nursing Hours per Patient Day in Belgian hospitals was 2.62 (S.D.=0.29). The variability in patient outcome rates between hospitals is considerable. The inter-quartile ranges for the 10 patient outcomes go from 0.35 for Deep Venous Thrombosis to 3.77 for failure-to-rescue. No significant association was found between the acuity-adjusted Nursing Hours per Patient Day, proportion of registered nurses with a Bachelor's degree and the selected patient outcomes. ConclusionThe absence of associations between hospital-level nurse staffing measures and patient outcomes should not be inferred as implying that nurse staffing does not have an impact on patient outcomes in Belgian hospitals. To better understand the dynamics of the nurse staffing and patient outcomes relationship in acute hospitals, further analyses (i.e. nursing unit level analyses) of these and other outcomes are recommended, in addition to inclusion of other study variables, including data about nursing practice environments in hospitals.

From a Belgian Nursing minimum dataset to a nursing cost-weight per DRG

From a Belgian Nursing minimum dataset to a nursing cost-weight per DRG

Measuring the intensity of nursing care: Making use of the Belgian Nursing Minimum Data Set

Background The Belgian Nursing Minimum Data Set (B-NMDS) is a nationwide registration of 23 nursing activities. It was developed for the measurement of nursing care in acute hospitals. It is used to support healthcare management & policy decision making such as hospital financing and nurse staffing decisions. Objective To develop a measure of the intensity of nursing care based on information that is available in the B-NMDS. Design–setting–participants Retrospective analysis of the B-NMDS from all Belgian acute hospitals ( n=115) for the year 2003. The sample included 690,258 inpatient days for 298,691 patients that were recorded from 1637 acute care nursing units. Methods The 23 nursing activities were synthesized into one new latent variable by PRINQUAL analysis. This variable was evaluated as a measure of nursing care intensity using key characteristics of the San Joaquin patient classification system, which was designed to measure the intensity of nursing care. Results The main NMDS component from the PRINQUAL analysis accounted for 26.8% of the variance. The distribution of inpatient days over all four San Joaquin categories is: 11.1% (self-care); 40.4% (average care); 30.8% (above average care); 17.7% (intensive care). In 97.5% of the nursing units the intensity of nursing care score of the B-NMDS (main NMDS component) followed the ordinality of the San Joaquin classification system. Furthermore, the San Joaquin categories alone explained more variability—70.2% in the intensity of nursing care measure (main NMDS component) than did other determinants, such as department type, age, diagnostic-related groups (DRG) and severity of illness, hospital type and hospital size together. Conclusion The B-NMDS is an instrument that produces a measure of the intensity of nursing care in acute hospitals.

Revising the Belgian Nursing Minimum Dataset: From concept to implementation

The process of revising the Belgian Nursing Minimum Dataset (B-NMDS) started in 2000 and entailed four major phases. The first phase (June-October 2002) involved the development of a conceptual framework based on a literature review and secondary data analysis. The Nursing Interventions Classification (NIC) was selected as a framework for the revision of the original B-NMDS. The second phase (November 2002-September 2003) focused on language development for six care programs evaluated by panels of clinical experts (N=75). These panels identified the following items as priorities for the revised B-NMDS: hospital financing, nurse staffing allocation, assessment of the appropriateness of hospitalisation, and quality management. During this period, we developed a draft instrument with 92 variables using the NIC. This led to an alpha version of a revised B-NMDS. The third phase (October 2003-December 2004) focused on data collection and validation of the new tool. The revised B-NMDS (alpha version) was tested in 158 nursing wards in 66 Belgian hospitals from December 2003 until March 2004. This test generated data for some 95,000 in-patient days. The interrater reliability of the revised B-NMDS was assessed. The criterion-related validity of the revised B-NMDS was compared to that of the original B-NMDS. The discriminative power of the revised B-NMDS was also assessed to select the most relevant variables for data collection. This resulted in a beta version of the revised B-NMDS in December 2004. The records of the revised B-NMDS were linked to the Hospital Discharge Dataset and other mandatory datasets to integrate the revised B-NMDS into the overall healthcare management system. The fourth phase (January 2005-December 2005) is presently focusing on information management. Nationwide implementation is foreseen by January 2007.

The cross-cultural adaptation of the Belgium Nursing Minimum Data Set to Finnish nursing

Background Nursing has been invisible in most of the international and national healthcare information systems and databases; also in Finland. The use of nursing minimum data set could be one solution to this problem. It is an information system that collects, stores, processes, retrieves, displays and communicates timely information about nursing practice needed for a variety of users and purposes. Objectives To test the cultural applicability of the Belgian Nursing Minimum Data Set (BeNMDS) to Finnish nursing. Methods The study design was methodological. It included testing of the validity, reliability and sensitivity of the BeNMDS. Content validity was tested using content analysis of the Finnish nursing doctorate dissertations, Katie Eriksson's publications of her Nursing Process Model and focus-group interviews of the healthcare administrators. Reliability, construct validity and sensitivity were tested using the data collected with the BeNMDS-tool from patients' nursing notes in Finnish Hospitals. Findings The validity, reliability and sensitivity of the BeNMDS in Finland were mainly good. The study showed, however, that the interventions to describe the patient's spiritual well-being, were missing and the psycho-social care interventions were insufficient in the data set. Conclusion The Finnish version of the BeNMDS has been shown to be valid, reliable and sensitive and applicable to describe nursing practice in Finland. Should the interventions to describe patient's spiritual and psycho-social well-being be included in the data set, Finnish nursing will have a valuable tool available to make nursing visible for the healthcare information systems and databases.

Frequency of intravenous medication administration to hospitalised patients: secondary data-analysis of the Belgian Nursing Minimum Data Set

The purpose of this study was to investigate the frequency of intravenous medication administration with Belgian hospitalised patients. Factors, which might influence this frequency of administration, were also studied. Research questions were investigated by secondary data-analysis of the Belgian Nursing Minimum Data Set. The randomised sample consisted of 1,035,681 observations on 421,530 patients. Results of this study demonstrate that one out of three (34%) hospitalised patients received intravenous medication. Medical diagnoses, for which most intravenous medications were administered, were oncological diseases: myeloid (77.9%) and lymphoid (69.4%) leukaemia. Elderly (6.7%) and female (31.2%) patients received significantly less intravenous medication than respectively young (32.9%) ( χ 2=98411, df=1, p<0.001) and male (38%) ( χ 2=2033, df=1, p<0.001) patients. Patients with intravenous medication administration were labour intensive for nursing staff.