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OBJECTIVE: Health outcomes may be influenced by organizational and management characteristics. We hypothesized that neonatal intensive care unit managerial practices and organizational processes could affect outcomes of births 500-1499 g, and we assessed this in eight neonatal intensive care units. DESIGN: Multiple-center cohort. SETTING: Eight acute care neonatal intensive care units in Washington, DC. PATIENTS: Infants weighing 500-1499 g, born from October 1, 1994, to February 19, 1997, to a resident of Washington, DC. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Outcomes included 28-day survival/death, bronchopulmonary dysplasia (BPD), periventricular/intraventricular hemorrhage or periventricular leukomalacia (PIVH/PVL), retinopathy of prematurity (ROP), length of hospital stay, and days of mechanical ventilation. Managerial practices and organizational processes were rated by nurses (n = 218), physicians (n = 73), and respiratory therapists (n = 77). Risk-adjusted logistic and linear mixed models were used to assess the association of outcomes with the caregiver ratings. A lower incidence of PIVH/PVL was associated with better overall scores (p =.0036) and better subscores for leadership (p <.0001), coordination (p =.047), and conflict resolution (p =.020). Better values of the respiratory therapists', nurses', and physicians' scores were associated with lower mortality rates (p =.045) and BPD (p =.0057), PIVH/PVL (p <.0001), and ROP (p =.049), respectively. In multivariate analysis, the joint effects of the professional groups' scores were associated with the incidence of PIVH/PVL (p =.0047); the nurses' scores were associated with lower incidence of PIVH/PVL (p =.0051). The association between the respiratory therapists' scores and lower mortality rate (p =.025) also remained significant in multivariate analysis. CONCLUSIONS: We found that the organizational processes and managerial practices as rated by healthcare professionals in neonatal intensive care units were associated with the development of mortality and chronic, severe morbidity. We did not identify specific processes or practices that accounted for our results. [ABSTRACT FROM AUTHOR]

BACKGROUND: Risk-adjusted severity of illness is frequently used in clinical research and quality assessments. Although there are multiple methods designed for neonates, they have been infrequently compared and some have not been assessed in large samples of very low birth weight (VLBW; <1500 g) infants. OBJECTIVES: To test and compare published neonatal mortality prediction models, including Clinical Risk Index for Babies (CRIB), Score for Neonatal Acute Physiology (SNAP), SNAP-Perinatal Extension (SNAP-PE), Neonatal Therapeutic Interventions Scoring System, the National Institute of Child Health and Human Development (NICHD) network model, and other individual admission factors such as birth weight, low Apgar score (<7 at 5 minutes), and small for gestational age status in a cohort of VLBW infants from the Washington, DC area. METHODS: Data were collected on 476 VLBW infants admitted to 8 neonatal intensive care units between October 1994 and February 1997. The calibration (closeness of total observed deaths to the predicted total) of models with published coefficients (SNAP-PE, CRIB, and NICHD) was assessed using the standardized mortality ratio. Discrimination was quantified as the area under the curve (AUC) for the receiver operating characteristic curves. Calibrated models were derived for the current database using logistic regression techniques. Goodness-of-fit of predicted to observed probabilities of death was assessed with the Hosmer-Lemeshow goodness-of-fit test. RESULTS: The calibration of published algorithms applied to our data was poor. The standardized mortality ratios for the NICHD, CRIB, and SNAP-PE models were.65,.56, and.82, respectively. Discrimination of all the models was excellent (range:.863-.930). Surprisingly, birth weight performed much better than in previous analyses, with an AUC of.869. The best models using both 12- and 24-hour postadmission data, significantly outperformed the best model based on birth data only but were not significantly different from each other. The variables in the best model were birth weight, birth weight squared, low 5-minute Apgar score, and SNAP (AUC =.930). CONCLUSION: Published models for severity of illness overpredicted hospital mortality in this set of VLBW infants, indicating a need for frequent recalibration. Discrimination for these severity of illness scores remains excellent. Birth variables should be reevaluated as a method to control for severity of illness in predicting mortality. [ABSTRACT FROM AUTHOR]

Computer assisted analysis and simulation of biochemical pathways can improve the understanding of the structure and the dynamics of cell processes considerably. The construction and quantitative analysis of kinetic models is often impeded by the lack of reliable data. However, as the topological structure of biochemical systems can be regarded to remain constant in time, a qualitative analysis of a pathway model was shown to be quite promising as it can render a lot of useful knowledge, e.g., about its structural invariants. The topic of this paper are pathways whose substances have reached a dynamic concentration equilibrium (steady state). It is argued that appreciated tools from biochemistry and also low-level Petri nets can yield only part of the desired results, whereas executable high-level net models lead to a number of valuable additional insights by combining symbolic analysis and simulation. [ABSTRACT FROM AUTHOR]