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4th IEEE International Conference on Computing and Information Sciences, ICCIS 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1730927

ABSTRACT

Social media has become a valuable tool for users to express their opinion and for researchers to analyze public sentiment more efficiently. People respond much quickly towards any issue on social than any other traditional platform. Observing the patient's opinion on social media about the hospital medical facilities is a new trend that several hospitals are adopting recently in the modern world to improve their heal care facilities. After the pandemic of SARS-CoV-2, it has influenced the health care practices of all the world. Initial investigations indicate that patients with comorbidities are more fragile to this SARS-CoV-2 infection. Medical experts suggested postponing the routine treatment of cancer patients. However, few meta-analyses suggested evidence are not sufficient to hold the claim of the frailty of cancer patients to COVID-19. They were not in favor of shelving the scheduled treatments. On the other hand, some medical experts favored postponing cancer patients' scheduled treatments like chemotherapy, which could be a dangerous decision for cancer patients. We conducted the sentiment analysis of the patients with various comorbidities (diseases like diabetes, obesity, and cancer in which patient has to visit the hospital more often) to understand their point of view whether they were satisfied during the pandemic with their treatment or not? How Covid-19 affected their scheduled appointments. To serve the purpose, we gathered more than 150000 relevant tweets from Twitter (Jan 2020 to April 2020) to analyze the sentiment of cancer patients around the world. Our findings demonstrate a surge in the argument about cancer and its treatment after the outbreak of COVID-19. Most of the tweets are reasonable (52.6%) compared to negative ones (24.3%). We developed polarity and subjectivity distribution to better recognize the positivity/negativity in the sentiment. The results reveal that the polarity range of positive tweets is within the range of 0 to 0.5. That means the tendency in the tweets is not negative (it is above zero) nor so much positive too. It is statistical evidence supporting how natural language processing (NLP) can be used to better understand the patient's behavior in real-time. It may facilitate the medical professionals to make better decisions to organize the routine management of cancer patients. © 2021 IEEE.

2.
Health Policy ; 124(12): 1333-1339, 2020 12.
Article in English | MEDLINE | ID: covidwho-910332

ABSTRACT

INTRODUCTION: The increase in access to Emergency Departments (ED) worldwide causes inefficiencies, but also signals its importance. The Coronavirus (Covid-19) outbreak allows to study the reactions of patients to the news about the spreading of the infection, which may have generated the fear that ED was no longer safe. METHODS: We study access to ED of a large teaching hospital in Brescia - one of the most hit provinces in Italy by Covid-19 - during the pandemic (from the announcement of the first cases to the explosion of the pandemic, to months after end of the acute phase) to study how patients reacted to the news that ED could no longer be a safe place. We analyse triage code, mode of arrival to ED, and accesses related to chest and abdominal pain, to evaluate who was discouraged most. RESULTS: Accesses have drastically reduced immediately after the news of the first contagion. During the lockdown accesses and admissions to hospital ward have decreased; this may mean that some patients may have suffered reduced health or increased mortality risks because of this decision. At the end of June accesses to ED and admissions to hospital ward are still lower than usual. DISCUSSION: Fear of contagion and appeals not to use ED directly by Covid-19 patients may have discouraged access also for pressing health need.


Subject(s)
COVID-19/psychology , Emergency Service, Hospital/statistics & numerical data , Fear , Pandemics , Abdominal Pain/epidemiology , Chest Pain/epidemiology , Female , Hospitalization/statistics & numerical data , Humans , Italy/epidemiology , Male , Triage/organization & administration
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