Data-driven optimization methodology for admission control in critical care units

Utility of Intermediate Care Units: A Systematic Review Study

Intermediate care units (IMCUs) have become increasingly important in the care of critical and semi-critical patients, particularly during the COVID-19 pandemic. However, there is still no clear definition of their structural characteristics, specialties, types of patients, and the benefits they provide. The aim of this work is to describe the current state of implementation and operation of IMCUs in hospitals and patient care. To achieve this goal, a systematic review was conducted in the Web of Science, Scopus and CINAHL databases, along with a hand search. The research yielded 419 documents, of which 26 were included in this review after applying inclusion and exclusion criteria. The results were highly diverse and were categorized based on the following topics: material resources, human resources, continuity of care, and patient benefits. Despite the different objectives outlined in the studies, all of them demonstrate the numerous benefits provided by an IMCU, along with the increased relevance of this type of unit in recent years. Therefore, this systematic review highlights the benefits of IMCUs in the care of critical patients, as well as the role of health workers in these units.

Patient Mix Optimization in Admission Planning under Multitype Patients and Priority Constraints

Hospital beds are one of the most critical medical resources. Large hospitals in China have caused bed utilization rates to exceed 100% due to long-term extra beds. To alleviate the contradiction between the supply of high-quality medical resources and the demand for hospitalization, in this paper, we address the decision of choosing a case mix for a respiratory medicine department. We aim to generate an optimal admission plan of elective patients with the stochastic length of stay and different resource consumption. We assume that we can classify elective patients according to their registration information before admission. We formulated a general integer programming model considering heterogeneous patients and introducing patient priority constraints. The mathematical model is used to generate a scientific and reasonable admission planning, determining the best admission mix for multitype patients in a period. Compared with model II that does not consider priority constraints, model I proposed in this paper is better in terms of admissions and revenue. The proposed model I can adjust the priority parameters to meet the optimal output under different goals and scenarios. The daily admission planning for each type of patient obtained by model I can be used to assist the patient admission management in large general hospitals.

Optimal age- and sex-based management of the queue to ventilators during the Covid-19 crisis

Triage protocols for intensive care units are based on priorities assigned to presents, but ignore patients about to arrive, so a priority newcomer may not find a ventilator and its associated nursing staff available because they are occupied by a lower-priority patient who however was present at the moment of assignment. Conversely, waiting too long leads to losing elderly patients who could have been saved by ventilators. As age and sex are major determinants of mortality by Covid-19 and have the merit, in contrast to other priority criteria, of being immediately available to health professionals, the criterion is the minimization of the mean mortality rate weighted by age- and sex-specific life expectancies. The dynamics is a queuing process involving mortality and return home flows and competition between ages. The result is the determination of an optimal threshold age that can guide triage.