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.

To achieve safe and respectful maternity care in tertiary level hospitals in Nepal, relatives are a valued addition to the provision of maternity care

Introduction: The White Ribbon Alliance for safe motherhood believes respectful maternity care is the universal right of every childbearing woman. Methods: NHRC in 2012 approved an inquiry of respectful care at facility-based childbirth. Individual-, focus group interviews and content analysis was used for gathering and analysis of data. Findings: The participating women and the SBAs shared similar views, and this was that together the SBAs and relatives ensured the women remained within the comfort and safety zone when giving birth in a tertiary level maternity unit. Conclusion: The SBAs strategy of having relatives provides basic care alongside the provision of medical care by the SBAs is a strategy that Nepal could use to improve the quality of its maternity care without any additional costs. Clinical implication: Prenatal classes might contribute to preparing relatives. Further Research: Further research could evaluate such a strategy in order to determine its effectiveness in reduction of morbidity and mortality.