Accepted for/Published in: JMIR Formative Research
Date Submitted: Jan 27, 2021
Date Accepted: May 31, 2021
Date Submitted to PubMed: Dec 20, 2021
Developing and testing of an Early Warning mobileHealth screening and risk scoring application for preventing heath worker in-hospital transmission of Covid-19: A feasibility study.
ABSTRACT
Background:
Hospitals have been identified as very high-risk places for Covid-19 transmission between health workers and non-covid-19 patients. Health care workers are the most at risk population to contract and transmit the infection especially to the already vulnerable non-Covid-19 patients. In Low-income countries, routine testing is not feasible due to the high cost of testing and the high turn around of results therefore presenting the risk of un-controlled transmission within the non Covid-19 treatment wards. This challenge necessitated the development of an affordable intermediary screening tool that would enable early identification of potentially infected health care workers and for early real time DNA-PCR testing prioritization. This would limit the contact time of potentially infected health care workers with the patients but also efficiently utilize the limited testing kits.
Objective:
The aim of this research was therefore to create an intermediary daily early warning screening tool that would identify health care workers with the highest likelihood of having contracted Covid-19 and have these prioritized for DNA-PCR testing and timely intervention. In this way, the exposure time of potentially infected health care workers to patients would be significantly reduce thus minimizing the in-hospital transmission of Covid-19 on the general and non-COVID-19 treatment units.
Methods:
Using the WHO, Ministry of Health of Uganda guidelines on the case definition of Covid-19, we developed a screening questionnaire tool for risk assessment of Covid-19. Specific signs and symptoms were weighted based on how prevalent they were among Covid-19 patients and subsequently an algorithm developed for the various case scenarios of Covid-19. Risk sores were computed based on the symptoms and contact history and a daily risk category assigned based on the risk score. The questionnaire, flow charts and algorithms were then integrated into an android mobile application. Following the launch, Health care workers would submit their daily risk scores and high-risk staff would be selected for testing and further intervention including treatment.
Results:
The primary result of this research project was the development of a mobile based daily early warning system for in-hospital transmission of Covid-19.
Conclusions:
The Early Warning System for in-hospital transmission of Covid-19(EWAS) significantly reduces the interaction of symptomatic health workers with patients therefore minimizing disease transmission on the wards while also identifying and optimizing routine DNA-PCR testing by identifying the health care providers who actually require to have the test done. This application therefore compliments the existing measures to prevent the transmission of Covid-19 in hospital settings. Clinical Trial: N/A
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Copyright
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