979 resultados para Customer support
Resumo:
Introduction: Individuals with poor social determinants of health aremore likely to receive improper healthcare. Frequent Users (FUs) ofEmergency Departments (ED) (defined as >4 visits in the previous12 months) represent a subgroup of vulnerable patients presentingwith specific medical and social needs. They usually account for highhealthcare costs by overusing the healthcare system. In 2008-2009,FUs accounted for 4% of our ED patients but 17% of all our ED visits.Methods: We conducted a prospective cohort of patients admitted toour ED with vulnerabilities in ≥3 specific domains (somatic or mentaldiseases, risk behaviors, social determinants of health, and healthcareuse). Patients were either directly identified by a multidisciplinary team(two nurses, one social worker, one physician) or referred to that teamby the ED staff during opening hours from July 1st 2010 to April 30th2011.Results: 127 patients were included (67% males), aged 43 years (SD15); 65% were migrants. They had a median of 6 ED visits (interquartilerange (IQR) 8-1) in the previous 12 months, representing a total of 697visits. The most frequently affected domains during the index visit were:71% somatic, 61% psychiatric, 75% risk behaviors, 97% social and84% healthcare use issues. Each case required a median of 234minutes (IQR 300-90) dedicated to assess their outpatient network(99% of the patients), to set up an ambulatory medical follow-up (43%)or a meeting with social services (40%).Conclusions: Vulnerability affected ED patients in more than onedomain. Vulnerable patients have complex needs that were difficult toaddress in the time-pressured ED setting. Although ED consultationoffers immediate access to medical care, EDs are dedicated more foracute short-term somatic care. Caring for a growing number ofvulnerable patients requires a different type of management. Limitedevidence shows that multidisciplinary case-management interventionshave demonstrated positive outcomes in terms of reducing ED useand costs, and improvement of patient's medical and social outcomes.A randomized trial of case-management is underway to confirm theresults of observational studies.
Resumo:
A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.
Resumo:
A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.
Resumo:
A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.
Resumo:
A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.
Resumo:
A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.
Resumo:
A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.
Resumo:
The cytokine BAFF binds to the receptors TACI, BCMA, and BAFF-R on B cells, whereas APRIL binds to TACI and BCMA only. The signaling properties of soluble trimeric BAFF (BAFF 3-mer) were compared with those of higher-order BAFF oligomers. All forms of BAFF bound BAFF-R and TACI, and elicited BAFF-R-dependent signals in primary B cells. In contrast, signaling through TACI in mature B cells or plasmablasts was only achieved by higher-order BAFF and APRIL oligomers, all of which were also po-tent activators of a multimerization-dependent reporter signaling pathway. These results indicate that, although BAFF-R and TACI can provide B cells with similar signals, only BAFF-R, but not TACI, can respond to soluble BAFF 3-mer, which is the main form of BAFF found in circulation. BAFF 60-mer, an efficient TACI agonist, was also detected in plasma of BAFF transgenic and nontransgenic mice and was more than 100-fold more active than BAFF 3-mer for the activation of multimerization-dependent signals. TACI supported survival of activated B cells and plasmablasts in vitro, providing a rational basis to explain the immunoglobulin deficiency reported in TACI-deficient persons.
Resumo:
A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.
Resumo:
Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance
Resumo:
Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.