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Background: Multiple studies have investigated the outcome of integrated care programs for chronically ill patients. However, few studies have addressed the specific role hospitals can play in the downstream collaboration for chronic disease management. Our objective here is to provide a comprehensive overview of the role of the hospitals by synthesizing the advantages and disadvantages of hospital interference in the chronic discourse for chronically ill patients found in published empirical studies.Method: Systematic literature review. Two reviewers independently investigated relevant studies using a standardized search strategy.Results: Thirty-two articles were included in the systematic review. Overall, the quality of the included studies is high. Four important themes were identified: the impact of transitional care interventions initiated from the hospital's side, the role of specialized care settings, the comparison of inpatient and outpatient care, and the effect of chronic care coordination on the experience of patients.Conclusion: Our results show that hospitals can play an important role in transitional care interventions and the coordination of chronic care with better outcomes for the patients by taking a leading role in integrated care programs. Above that, the patient experiences are positively influenced by the coordinating role of a specialist. Specialized care settings, as components of the hospital, facilitate the coordination of the care processes. In the future, specialized care centers and primary care could play a more extensive role in care for chronic patients by collaborating. [ABSTRACT FROM AUTHOR]

Background: The wide range of fresh gas flow - vaporizer setting (FGF - FD) combinations used by different anesthesiologists during the wash-in period of inhaled anesthetics indicates that the selection of FGF and FD is based on habit and personal experience. An empirical model could rationalize FGF - FD selection during wash-in. Methods: During model derivation, 50 ASA PS I-II patients received desflurane in O2 with an ADU® anesthesia machine with a random combination of a fixed FGF - FD setting. The resulting course of the end-expired desflurane concentration (FA) was modeled with Excel Solver, with patient age, height, and weight as covariates; NONMEM was used to check for parsimony. The resulting equation was solved for FD, and prospectively tested by having the formula calculate FD to be used by the anesthesiologist after randomly selecting a FGF, a target FA (FAt), and a specified time interval (1 - 5 min) after turning on the vaporizer after which FAtt had to be reached. The following targets were tested: desflurane FAt 3.5% after 3.5 min (n = 40), 5% after 5 min (n = 37), and 6% after 4.5 min (n = 37). Results: Solving the equation derived during model development for FD yields FD=-(e(-FGF*-0.23+FGF*0.24)*(e(FGF*-0.23) *FAt*Ht*0.1-e(FGF*-0.23)*FGF*2.55+40.46-e(FGF*-0.23)*40.46+e(FGF*-0.23+Time/-4.08)* 40.46-e(Time/-4.08)*40.46))/((-1+e(FGF*0.24))*(-1 +e(Time/-4.08))*39.29). Only height (Ht) could be withheld as a significant covariate. Median performance error and median absolute performance error were -2.9 and 7.0% in the 3.5% after 3.5 min group, -3.4 and 11.4% in the 5% after 5 min group, and -16.2 and 16.2% in the 6% after 4.5 min groups, respectively. Conclusions: An empirical model can be used to predict the FGF - FD combinations that attain a target endexpired anesthetic agent concentration with clinically acceptable accuracy within the first 5 min of the start of administration. The sequences are easily calculated in an Excel file and simple to use (one fixed FGF - FD setting), and will minimize agent consumption and reduce pollution by allowing to determine the lowest possible FGF that can be used. Different anesthesia machines will likely have different equations for different agents. [ABSTRACT FROM AUTHOR]