An Edge Computing Based Smart Healthcare Framework for Resource Management

The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time

55. Coronary artery bypass graft for cardiogenic shock post STEMI patients

Cardiogenic shock (CS) complicating AMI continues to have a high mortality of 60–80% despite early revascularization and adjunctive therapies. AMI-CS complicates 5–7% of cases of STEMI and is a leading cause of hospital death AMI. We studied the outcome of CABG for AMI-CS patients. From 10-2013 to 9-2015, 24 patients with post STEMI cardiogenic shock were admitted and underwent emergency CABG. Mean pre-operative ejection fraction (EF) was 29.7 ± 8.4%. 8 patients were on IABP pre-operatively. Operative mortality rate was 21%. Survival rate was 79% and mean follow-up of 10.21 ± 4.8 months. CABG should be considered for patients with AMI complicated by cardiogenic shock when PCI can not be done

52. Early revascularization on veno-arterial ECMO for patients with cardiogenic shock post stemi

Refractory Cardiogenic shock (CS) complicates 5–7% of cases of ST-elevation myocardial infarction (STEMI), and is a leading cause of hospital death after myocardial infarction. CS complicating acute myocardial infarction continues to have a high mortality of 60–80% despite early revascularization and adjunctive therapies. We studied the effectiveness of veno-arterial (VA) – Extracorporeal Membrane Oxygenator (ECMO) for the patients with CS post STEMI during coronary angiography at our institute. Between January 2014 to April 2015, 8 male patients who suffered from progressive severe refractory CS post STEMI underwent emergent peripheral VA-ECMO implantation while performing cardiopulmonary resuscitation during coronary angiography. 7 patients of underwent PCI, while 1 patient was not amenable to PCI or CABG. The mean duration of support was 8.5 ± 5.8 days. 6 patients were successfully weaned from ECMO. While on ECMO support, 2 patients died. Mean EF after ECMO explantation was 32.5% ± 10.5%. The 30-day survival was 50%. Early revascularization on ECMO allows supporting hemodynamic efficiently in cardiogenic shock patients

Proposal of a smart hospital based on internet of things (IoT) concept

This article proposes the utilization of the Artificial Intelligence (AI) and Automation techniques oriented to a service-based business. Developing and proposing a methodology for the implementation and development of a smart hospital, taking as a foundation a traditional hospital. The approach is based on the analysis of the studied e-health system, focusing on the patient flow. The use of Discrete Event Simulation (DES) models allows a computational model method for recreating the system and detect the system’s bottlenecks. Those blockages are improved by the addition of “smart devices”, implemented in the DES model and this improvement of the patient flow attendance and service quality, what directly influence the reduction of mortality in the Emergency Department (ED). Finally, the social implication is the reduction of the mortality in the ED, what is directly related to the improvement of the service quality and the reduction of the waiting time for the patients1137993104SAMBA: SIPAIM – Miccai biomedical workshop, biomedical information processing and analysis - a Latin American perspective2018Granada, Espanh