A new software has been developed that now can identify patients who are likely to require ventilator support in an ICU and referral in time and allow for the required arrangements to be made before an emergency occurs.
The software is called Covid Severity Score (CSS) Software consists of an algorithm that measures a set of parameters. It rates each patient against a pre-set dynamic algorithm multiple times and allocates a Covid Severity Score (CSS) mapping it in a graphical trend.
Currently, the technology is being utilised in three community Covid care centres at Kolkata and suburbs including a 100-bed government-mandated Covid care centre at Barrackpore, Kolkata.
The sudden demand in ICU and other emergency requirements during the pandemic have been a challenge for hospitals to manage. Timely information about such situations would help in managing the health crisis better.
The foundation for innovations in health, Kolkata with support from the Science for Equity, Empowerment and Development (SEED) division of the Department of Science & Technology in collaboration with IIT Guwahati, Dr. Kevin Dhaliwal from the University of Edinburgh and Dr. Sayantan Bandopadhyay, formerly WHO (SE Asia Regional Office), have developed an algorithm that measures symptoms, signs, vital parameters, test reports and comorbidities of the COVID positive patients and scores each of them against a pre-set dynamic algorithm thus allocating a Covid Severity Score (CSS).
Through SEED project support, this technology has been made available at primary care e-Health clinics in resource-poor settings.
Benefits
The ‘CSS’ is being routinely monitored several times by ‘remote’ specialist doctors thus reducing the doctor’s consultation time per patient and also reducing doctor’s travel requirements. It can help in the early identification of patients who are likely to require ventilator support in an ICU and referral and reduce hospital referrals for those who do not require critical care support, thus releasing more hospital beds in circulation.
It will also help in providing supervised medical assistance to patients who cannot afford treatment or who are unable to isolate themselves at home owing to poor housing conditions. The facility can tremendously help Covid Care Centres which have the facility of beds and oxygen assistance, but no facility for invasive ventilation.
(Input: PBNS)
