Cross motor innervation of the hypoglossal nerve-a pilot study of predictors for successful opening of the soft palate.

PURPOSE: Selective hypoglossal nerve stimulation has proven to be a successful treatment option in patients with obstructive sleep apnea. The aim of this pilot study was to investigate if there is a cross-innervation of the hypoglossal nerve in humans and if patients with this phenotype show a different response to hypoglossal nerve stimulation compared to those with ipsilateral-only innervation METHODS: Nineteen patients who previously received a selective hypoglossal nerve stimulation system (Inspire Medical Systems, Golden Valley, USA) were implanted with a nerve integrity system placing electrodes on both sides of the tongue. Tongue motions were recorded one and two months after surgery from transoral and transnasal views. Polysomnography (PSG) was also performed at two months. Electromyogram (EMG) signals and tongue motions after activation were compared with PSG findings. RESULTS: Cross-innervation showed significant correlation with bilateral tongue movement and bilateral tongue base opening, which were associated with better PSG outcomes. CONCLUSION: Cross motor innervation of the hypoglossal nerve occurs in approximately 50% of humans, which is associated with a positive effect on PSG outcomes. Bilateral stimulation of the hypoglossal nerve may be a solution for non-responding patients with pronounced collapse at the soft palate during drug-induced sleep endoscopy.

Decision Support for the Capacity Management of Bronchoscopy Devices: Optimizing the Cost-Efficient Mix of Reusable and Single-Use Devices Through Mathematical Modeling.

BACKGROUND: Increasing costs of material resources challenge hospitals to stay profitable. Particularly in anesthesia departments and intensive care units, bronchoscopes are used for various indications. Inefficient management of single- and multiple-use systems can influence the hospitals' material costs substantially. Using mathematical modeling, we developed a strategic decision support tool to determine the optimum mix of disposable and reusable bronchoscopy devices in the setting of an intensive care unit. METHODS: A mathematical model with the objective to minimize costs in relation to demand constraints for bronchoscopy devices was formulated. The stochastic model decides whether single-use, multi-use, or a strategically chosen mix of both device types should be used. A decision support tool was developed in which parameters for uncertain demand such as mean, standard deviation, and a reliability parameter can be inserted. Furthermore, reprocessing costs per procedure, procurement, and maintenance costs for devices can be parameterized. RESULTS: Our experiments show for which demand pattern and reliability measure, it is efficient to only use reusable or disposable devices and under which circumstances the combination of both device types is beneficial. CONCLUSIONS: To determine the optimum mix of single-use and reusable bronchoscopy devices effectively and efficiently, managers can enter their hospital-specific parameters such as demand and prices into the decision support tool.The software can be downloaded at: https://github.com/drdanielgartner/bronchomix/.

Long term staff scheduling of physicians with different experience levels in hospitals using column generation.

We present a strategic model to solve the long-term staffing problem of physicians in hospitals using flexible shifts. The objective is to minimize the total number of staff subject to several labor agreements. A wide range of legal restrictions and facility-specific staffing policies are considered. In general, the model is capable to incorporate different experience levels. In the simplest version the model decides about the number of staff for two experience levels, i.e. the number of residents (low experience) versus specialists (high experience). Shifts are constructed implicitly by the model and may have different starting times and several lengths. This allows more flexibility in the scheduling process. We formulate the problem as a mixed-integer program and solve it applying a column generation based heuristic. Using data provided by an anesthesia department of an 1100-bed hospital, computational results demonstrate the usage of the model as decision supporting tool when staffing decision are made by hospital management.