Managing low-acuity patients in an Emergency Department through simulation-based multiobjective optimization using a neural network metamodel.

This paper deals with Emergency Department (ED) fast-tracks for low-acuity patients, a strategy often adopted to reduce ED overcrowding. We focus on optimizing resource allocation in minor injuries units, which are the ED units that can treat low-acuity patients, with the aim of minimizing patient waiting times and ED operating costs. We formulate this problem as a general multiobjective simulation-based optimization problem where some of the objectives are expensive black-box functions that can only be evaluated through a time-consuming simulation. To efficiently solve this problem, we propose a metamodeling approach that uses an artificial neural network to replace a black-box objective function with a suitable model. This approach allows us to obtain a set of Pareto optimal points for the multiobjective problem we consider, from which decision-makers can select the most appropriate solutions for different situations. We present the results of computational experiments conducted on a real case study involving the ED of a large hospital in Italy. The results show the reliability and effectiveness of our proposed approach, compared to the standard approach based on derivative-free optimization.

Exercise Levels and Preferences in Cancer Patients: A Cross-Sectional Study.

BACKGROUND: Despite the benefits related to physical exercise, large numbers of cancer patients are not sufficiently active. METHODS: To investigate exercise levels and preferences in cancer patients, a cross-sectional study was conducted on a random sample of 392 cancer outpatients who anonymously completed a questionnaire investigating general and medical characteristics, and expressed willingness to participate in exercise programs. Current exercise levels were estimated with the Leisure Score Index (LSI). RESULTS: Most patients (93%) were insufficiently active but 80% declared an interest in exercise programs. Patients preferred oncologist-instructed programs and specified particular exercise needs. Multivariate logistic regression showed that willingness to exercise was associated with education (OR: 1.87; 95% CI: 1.15-3.04 beyond age 14 years vs. up to 14 years) and current physical activity (OR: 1.92; 95% CI: 1.92-3.63 for sweat-inducing activity >2 times/week vs. <1 time/week). Patients given chemotherapy were less inclined to exercise (OR: 0.45; 95% CI: 0.23-0.86) than those who did not. LSI was lower if cancer stage was advanced (ß: -0.36; 95% CI: -0.75 to -0.02) than if it was in remission. High LSI was also associated with longer education, lower BMI, and longer time after diagnosis. CONCLUSION: Cancer patients are insufficiently active but are willing to participate in personalized exercise programs. Information from this survey may help in designing personalized interventions so these patients will achieve sufficient exercise.

Data of patients undergoing rehabilitation programs.

In this data article, we present a dataset made up of personal, social and clinical records related to patients undergoing a rehabilitation program. Data refers to records registered in the "Acceptance/Discharge Report for the rehabilitation area" (ADR) which implements the Italian law (DGR 731/2005) and refer to hospitalization at the rehabilitation hospital of Rome "San Raffaele" in the years from 2015 to 2018 of patients suffering from orthopedic and neurological pathologies. For each ADR report, the clinical status of the patient at the date of acceptance and discharge is reported using, among other, the Barthel index as a measure of the Activities Daily Living of the patient. These data can be used to understand the influence of many different factors in the rehabilitation progress of clinical patients.