Reducing unplanned extubations in the NICU.

BACKGROUND AND OBJECTIVES: Unplanned extubation can be a significant event that places the patient at risk for adverse events. Our goal was to reduce unplanned extubations to <1 unplanned extubation per 100 patient-intubated days. METHODS: All unplanned extubations in the NICU beginning in October 2009 were audited. Data collected included time of day, patient weight, and patient care activity at the time of the event. Bundles of potentially better practices were implemented in sequential Plan-Do-Study-Act cycles. Rates of unplanned extubation (number per patient-intubated day) for each month were analyzed by using control charts, and causes of unplanned extubation were analyzed by using Pareto charts. RESULTS: We found a significant decrease in the unplanned extubation rate after implementation of the first bundle of potentially better practices in May 2010 (2.38 to 0.41 per 100 patient-intubated days). Several more Plan-Do-Study-Act cycles were conducted to sustain this improvement. A persistent reduction in the unplanned extubation rate (0.58 per 100 patient-intubated days) began in February 2013. Causes included dislodgement during care and procedures and variation in the fixation of the endotracheal tube. The majority of events occurred in very low birth weight infants during the daytime shift. CONCLUSIONS: Unplanned extubations in the NICU can be reduced by education of staff and by implementing standard practices of care. Sustainability of any practice change to improve quality is critically dependent on culture change within the NICU. We suggest that the benchmark for unplanned extubation should be a rate <1 per 100 patient-intubated days.

Dynamic social networks in recovery homes.

Acute treatment aftercare in the form of sober living environments-i.e., recovery houses-provide an inexpensive and effective medium-term treatment alternative for many with substance use disorders. Limited evidence suggests that house-situated social relationships and associated social support are critical determinants of how successful these residential experiences are for their members, but little is known about the mechanisms underlying these relationships. This study explored the feasibility of using dynamic social network modeling to understand house-situated longitudinal associations among individual Alcoholics Anonymous related recovery behaviors, length of residence, dyadic interpersonal trust, and dyadic confidant relationship formation processes. Trust and confidant relationships were measured 3 months apart in U.S. urban-area recovery houses, all of which were part of a network of substance use recovery homes. A stochastic actor-based model was successfully estimated from this data set. Results suggest that confidant relationships are predicted by trust, while trust is affected by recovery behaviors and length of residence. Conceptualizing recovery houses as a set of independent, evolving social networks that can be modeled jointly appears to be a promising direction for research.