OBJECTIVES: Covid 19 was declared a pandemic by the WHO on March 2020. Brazil emerged as an epicenter of the coronavirus pandemic with more than 12.8 million cases of COVID-19, including over 325,000 fatalities until April 2021. This study evaluates the survival curve and associated factors with mortality after COVID-19 hospitalizations. METHODS: Retrospective analysis until May 2021 from administrative database of 37,462 people. Mortality after hospital discharge was investigated in different groups: presence or absence of comorbidities prior to admission (Charlson Comorbidity Index), age (greater/less than 60 years), sex, mean time hospital stay (up to 13/14+ days) and ICU admission. For survival analysis we used the Kaplan-Meier method. Log-rank test applied to compare curves. 95% confidence interval (CI) and significance when p <0.05. RESULTS: Analysis included 916 patients, mean age 69.1 (95% CI 68.1 to 70.1), 50.0% women (n=458) and 50.0% men (n=458). Hospital stay average was 10.9 days (95% CI 10.1 to 11.7). From hospitalizations, 38.9% admitted in the ICU (n=356). The overall mortality rate during period was 23.1% (n=212), men 24.0% (n=110) and women 22.3% (n=102). Mortality rate during Covid hospitalization was 11.6% (n=106), 10.9% in men (n=50) and 12.2% in women (n=56). Risk of death at any time during the follow-up period was significantly higher when presence of previous comorbidities (p=0.020), age greater than 60 years (p <0.001), ICU stay (p <0.001), and higher average length hospital stay (p=0.001). CONCLUSIONS: During the follow-up period after COVID 19 hospitalization patients aged 60 or over, previous comorbidities, prolonged hospital stay, and ICU admissions showed higher mortality. This observed correlation was used to develop a calculator using artificial intelligence to predict which individuals present high risk of death after COVID-19 hospital discharges and to implement models for monitoring and health management.