Background: During the first phases of the pandemic many apps were launched to tackle the surge of covid-19, among those the CovidGuide app. The app is a conversational agent (CA) with a neural network artificial intelligence(AI) supporting users in defining the right time to treat and point of care for their healthcare problem. To besafe and effective, the advice of the app should be followed by the user. This can help reduce health systemsoverloading. Research questions: Can a self-triage app give safe and effective advice to patients in case of covid19-like symptoms?Can self-triage tools impact on primary care professionals' (notably GPs') burden?Method: CovidGuide database containing consultations results from inception to April 19 2022 was analyzed and themain descriptive statistical analyses were performedResults: On a total number of 374.179 consultations, the most frequent advice given was the indication to see thedoctor today (38% of the consultations). 62% patients were females, 75% in the age range 14-49 years, mainsymptoms reported were viral syndrome not otherwise specified and throat symptoms complaints. 75.692patients, 20% of cases, received indication for self-monitoring with safety net (ie indications on what to do incase of symptoms’ worsening).Conclusions: Data retrieved so far depict the core features of the users of this app: women in age range 14-49 were the most represented category of CovidGuide users. Further exploration of factors influencing intention to complywith the app’s advice, already ongoing, may help understand what brings people to use this kind of app andeventually follow the given advice.Moreover, the huge number of consultations ending with the indications for self-monitoring may beinvestigated to understand whether it is possible to use these tools to decrease PCPs’ burden.
Self-triage tools during covid-19 outbreak: the CovidGuide app experience
Demurtas J;
2022-01-01
Abstract
Background: During the first phases of the pandemic many apps were launched to tackle the surge of covid-19, among those the CovidGuide app. The app is a conversational agent (CA) with a neural network artificial intelligence(AI) supporting users in defining the right time to treat and point of care for their healthcare problem. To besafe and effective, the advice of the app should be followed by the user. This can help reduce health systemsoverloading. Research questions: Can a self-triage app give safe and effective advice to patients in case of covid19-like symptoms?Can self-triage tools impact on primary care professionals' (notably GPs') burden?Method: CovidGuide database containing consultations results from inception to April 19 2022 was analyzed and themain descriptive statistical analyses were performedResults: On a total number of 374.179 consultations, the most frequent advice given was the indication to see thedoctor today (38% of the consultations). 62% patients were females, 75% in the age range 14-49 years, mainsymptoms reported were viral syndrome not otherwise specified and throat symptoms complaints. 75.692patients, 20% of cases, received indication for self-monitoring with safety net (ie indications on what to do incase of symptoms’ worsening).Conclusions: Data retrieved so far depict the core features of the users of this app: women in age range 14-49 were the most represented category of CovidGuide users. Further exploration of factors influencing intention to complywith the app’s advice, already ongoing, may help understand what brings people to use this kind of app andeventually follow the given advice.Moreover, the huge number of consultations ending with the indications for self-monitoring may beinvestigated to understand whether it is possible to use these tools to decrease PCPs’ burden.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
