Dzhemeli clinic and SAS created an interactive panel for resource allocation and load of personnel

2020: Creation of an interactive panel for resource allocation and load of personnel

On May 18, 2020 it became known that tools of SAS help with resource management for treatment of patients with COVID-19.

University clinic of Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Even the most modern hospitals which the known Roman clinic Dzhemelli is among faced serious calls because of a heavy load on a health care system. In hospital using SAS research projects are kept and the interactive panel which allows to organize better resource allocation and load of personnel was created, to monitor in real time all hospitalization, statements and movements of patients with COVID-19, to conduct monitoring of beds in intensive care unit, to investigate clinical data, etc.

Thanks to solutions of SAS we could organize better resource management and their planning for the short-term and medium term. We also cooperate with SAS in work on the project which is designed to increase the effectiveness of efforts on fight against a disease. We try to predict complications at the infected patients and to predict duration of their stay in hospital. Plus, we can provide to each patient individual recommendations about rehabilitation after a disease, speaks Paolo Sergii, the director of information systems of Dzhemelli clinic.

A system is capable to predict quantity of cases and the corresponding loading in the short term for department of the emergency help. For a hospital and intensive care unit she analyzes diagnostic and therapeutic information from medical records; for control structures – works on the reporting and prompts optimal placement of the resources necessary for treatment of patients with COVID-19; it provides analytical tools on the basis of AI which help to count the steady virologic answer to a pandemic for research laboratories. Many important clinical data on patients with COVID-19 are not structured, tools of text analytics of SAS help to take and arrange such information automatically for extremely short terms.

The pandemic of a deadly disease created unprecedented calls before a state administration, health care systems and ensuring deliveries. SAS works with departments and the medical organizations worldwide, helping to solve the problems connected with a coronavirus of new type using a research and data analysis. Among such tasks:

• The help to stationary medical institutions, clinical hospitals and out-patient link in application of predictive analytics for distribution of the vital resources, requirement for which is especially high.
• Cooperation with public organizations from health sector for creation of epidemiological models which predict influence of a virus on the population and infrastructure.
• Work with government services for optimization of medical resources and increase in availability of medical care to citizens.

Cope with a pandemic of a coronavirus and overcome effects of spread of a virus is extremely difficult task as the virus is little studied, dynamics of incidence constantly changes and the symptomatology is different. But from health care systems and the governments fast understanding of a situation, its assessment and reaction are required. To take adequate measures, multidimensional approach, including a possibility of fast collecting and data integration, forecasting of peaks of demand for resources and identification of hot spots where lack of funds of protection, personnel and the equipment will influence patient care, and taking measures to arrangement of priorities and resource allocation is required, comments Mark Lambrekht, the doctor of science, the director of global practice of SAS of analytics in health care and pharmaceutics.

As specified TAdviser in SAS, the project in Dzhemelli clinic was implemented based on the analytical SAS Viya platform using such products as: SAS Visual Statistics, SAS Visual Forecasting, SAS Visual Text Analytics, SAS/OR Software and SAS Model Manager.