Rapport från/Report from IEA Task-14 mötet/meeting on solar heating system, Hameln Tyskland/Germany August 1992

Participation as observer at the meeting of Task 14 of IEA's Solar Heating and Cooling Projects held in Hameln, Germany has led to greater understanding of interesting developments underway in several countries. This will be of use during the development of small scale systems suitable for Swedish conditions. A summary of the work carried out by the working groups within Task 14 is given, with emphasis on the Domestic Hot Water group. Experiences of low-flow systems from several countries are related, and the conclusion is drawn that the maximum theoretical possible increase in performance of 20% has not been achieved due to poor heat exchangers and poor stratification in the storage tanks. Positive developments in connecting tubes and pumps is noted. Further participation as observer in Task 14 meetings is desired, and is looked on favourably by the members of the group. Another conclusion is that SERC should carry on with work on Swedish storage tanks, with emphasis on better stratification and heat exchangers, and possible modelling of system components. Finally a German Do-it-Vourself kit is described and judged in comparison with prefabricated models and Swedish Do-it-Yourself kits.

Modeling Hospital Readmissions in Dalarna County, Sweden

Unplanned hospital readmissions increase health and medical care costs and indicate lower the lower quality of the healthcare services. Hence, predicting patients at risk to be readmitted is of interest. Using administrative data of patients being treated in the medical centers and hospitals in the Dalarna County, Sweden, during 2008 – 2016 two risk prediction models of hospital readmission are built. The first model relies on the logistic regression (LR) approach, predicts correctly 2,648 out of 3,392 observed readmission in the test dataset, reaching a c-statistics of 0.69. The second model is built using random forests (RF) algorithm; correctly predicts 2,183 readmission (out of 3,366) and 13,198 non-readmission events (out of 18,982). The discriminating ability of the best performing RF model (c-statistic 0.60) is comparable to that of the logistic model. Although the discriminating ability of both LR and RF risk prediction models is relatively modest, still these models are capable to identify patients running high risk of hospital readmission. These patients can then be targeted with specific interventions, in order to prevent the readmission, improve patients’ quality of life and reduce health and medical care costs.