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. (C) 2007 Elsevier Ltd. All rights reserved

Aggegrate production control of hospitals

The paper considers the level of aggregate production control in hospitals and looks in particular to the allocation of hospital resources. It describes an allocation procedure that takes the patient flow as point of departure. The paper describes a production control perspective to this problem, that is based on principles used in industrial settings. The results show that hospitals may benefit from this type of business-like approaches to improve workflow and capacity management

Resource utilisation and quality of care: a logistic approach

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Behavioural hyperventilation as a novel clinical condition associated with central sleep apnoea: A report of three cases

Contains fulltext : 110372.pdf (publisher's version ) (Closed access)Central sleep apnoea (CSA) is a disorder characterised by repetitive episodes of decreased ventilation due to complete or partial reduction in the central neural outflow to the respiratory muscles. Hyperventilation plays a prime role in the pathogenesis of CSA. Chronic heart failure and dwelling at high altitude are classical conditions in which CSA is induced by hyperventilation. Hyperventilation syndrome (HVS) is a prevalent behavioural condition in which minute ventilation exceeds metabolic demands, resulting in haemodynamic and chemical changes that produce characteristic dysphoric symptoms. HVS is frequently caused by anxiety disorders and panic attacks. Until now, medical literature has focussed primarily on daytime symptoms of behavioural hyperventilation. It is currently unknown how this condition may affect sleep. Three cases are reported in which behavioural hyperventilation was associated with occurrence of significant central sleep apnoea, which was not present during normal tidal breathing in steady sleep. Therefore, behavioural hyperventilation should be added to the list of known clinical conditions associated with CSA