A population-based assessment of avoidable hospitalizations and resource use of non-vaccinated patients with COVID-19

Abstract

Objective The coronavirus disease 2019 (COVID-19) pandemic has precipitated a prolonged public health crisis. Numerous public health protections were widely implemented. The availability of effective and safe vaccines for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presented an opportunity to resolve this crisis; however, vaccine uptake was slow and inconsistent. This study evaluated the potential for preventable hospitalizations and avoidable resource use among eligible non-vaccinated persons hospitalized for COVID-19 had these persons been vaccinated. Methods This was a retrospective, population-based cohort study. The population-at-risk were persons aged ≥ 12 years in Alberta (mid-year 2021 population ~ 4.4 million). The primary exposure was vaccination status. The primary outcome was hospitalization with confirmed SARS-CoV-2, and secondary outcomes included avoidable hospitalizations, avoidable hospital bed-days, and the potential cost avoidance related to COVID-19. The study inception period was 27 September 2021 to 25 January 2022. Data on COVID-19 hospitalizations, vaccination status, health services, and costs were obtained from the Government of Alberta and from the Discharge Abstract Database. Results Hospitalizations occurred in 3835, 1907, and 481 persons who were non-vaccinated, fully vaccinated, and boosted (risk of hospitalization/100,000 population: 886, 92, and 43), respectively. For non-vaccinated persons compared with fully vaccinated and boosted persons, the risk ratios (95%CI) of hospitalization were 9.7 (7.9–11.8) and 20.6 (17.9–23.6), respectively. For non-vaccinated persons, estimates of avoidable hospitalizations and bed-days used were 3439 and 36,331 if fully vaccinated and 3764 and 40,185 if boosted. Estimates of cost avoidance for non-vaccinated persons were $101.46 million if fully vaccinated and $110.24 million if boosted. Conclusion Eligible non-vaccinated persons with COVID-19 had tenfold and 21-fold higher risks of hospitalization relative to whether they had been fully vaccinated or boosted, resulting in considerable avoidable hospital bed-days and costs. Supplementary Information The online version contains supplementary material available at 10.17269/s41997-023-00777-2.

Association Between Vaccination Status and Outcomes in Patients Admitted to the ICU With COVID-19*

“…Vaccination is effective to reduce severe cases of SARS-CoV-2 infections requiring ICU admission or MV (13,22,23). A recent retrospective population-based cohort study of 1,053 patients admitted to the ICU showed that the cumulative frequency of ICU admissions for unvaccinated, partially vaccinated, and fully vaccinated patients was 230.6, 30.8, and 5.5/100,000 population, with potential for 1,028 avoidable ICU admissions and total avoidable costs of $61.3 million CAD in one Canadian province (24). However, our study focuses on the unfortunate subset that developed critical illness from COVID-19, and who are often neglected in population-based studies in which ICU admission is often an outcome rather than a study population.…”

Factors Associated with Pneumonia in Patients Hospitalized with COVID-19 and the Role of Vaccination

“…Different types of vaccines have been developed to prevent SARS-CoV-2 infection and subsequent COVID-19 disease [ 12 ]. Numerous studies found, as a result of vaccine administration, a lower incidence of hospitalization for COVID-19 pneumonia, fewer hospitalized patients with respiratory distress and requiring supplemental oxygen, as well as reduced need for ICU admission [ 53 , 54 , 55 ]. In particular, a recent comparative analysis of clinical outcomes conducted in Spain on 232 adult patients hospitalized with COVID-19 showed that a complete vaccination schedule of either mRNA or adenovirus vaccines protected patients from progression to severe disease or death compared to unvaccinated patients [ 56 ].…”

“…Nor did we assess some potential confounding factors, such as previous SARS-CoV-2 infection or time between the data of vaccination and the onset of disease. Moreover, it would have been interesting to consider the effects of the restrictive measures, the risk management, and the communication plans implemented by the government during the pandemic [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 ].…”