ALICE (A Large Ion Collider Experiment) is a detector dedicated to the studies with heavy ion collisions exploring the physics of strongly interacting nuclear matter and the quark-gluon plasma at the ...CERN LHC (Large Hadron Collider). After the second long shutdown of the LHC, the ALICE Experiment will be upgraded to make high precision measurements of rare probes at low pT, which cannot be selected with a trigger, and therefore require a very large sample of events recorded on tape. The online computing system will be completely redesigned to address the major challenge of sampling the full 50 kHz Pb-Pb interaction rate increasing the present limit by a factor of 100. This upgrade will also include the continuous un-triggered read-out of two detectors: ITS (Inner Tracking System) and TPC (Time Projection Chamber)) producing a sustained throughput of 1 TB/s. This unprecedented data rate will be reduced by adopting an entirely new strategy where calibration and reconstruction are performed online, and only the reconstruction results are stored while the raw data are discarded. This system, already demonstrated in production on the TPC data since 2011, will be optimized for the online usage of reconstruction algorithms. This implies much tighter coupling between online and offline computing systems. An R&D program has been set up to meet this huge challenge. The object of this paper is to present this program and its first results.
The German Institute for Quality and Efficiency in Health Care (IQWiG) previously tested two preference elicitation methods in pilot projects and regarded them as generally feasible for prioritizing ...outcome-specific results of benefit assessment. The present study aimed to investigate the feasibility of completing a discrete choice experiment (DCE) within 3 months and to determine the relative importance of attributes of periodontal disease and its treatment.
This preference elicitation was conducted alongside the IQWiG benefit assessment of systematic treatments of periodontal diseases. Attributes were defined based on the benefit assessment, literature review, and patients' and periodontologists' interviews. The DCE survey was completed by patients with a history of periodontal disease. Preferences were elicited for the attributes "tooth loss within next 10 years", "own costs for treatment, follow-up visits, re-treatment", "complaints and symptoms", and "frequency of follow-up visits". Patients completed a self-administered questionnaire including 12 choice tasks. Data were analyzed using a random parameters logit model. The relative attribute importance was calculated based on level ranges.
Within 3 months, survey development, data collection among 267 patients, data analysis, and provision of a study report could be completed. The analysis showed that tooth loss (score 0.73) was the most important attribute in patients' decisions, followed by complaints and symptoms (0.22), frequency of follow-up visits (0.02), and costs (0.03) (relative importance scores summing up to 1).
A preference analysis performing a DCE can be generally feasible within 3 months; however, a good research infrastructure and access to patients is required. Outcomes used in benefit assessments might need to be adapted to be used in preference analyses.
PDF
