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. 2024 Apr 1;7(4):e245786.
doi: 10.1001/jamanetworkopen.2024.5786.

Risk of Potentially Preventable Hospitalizations After SARS-CoV-2 Infection

Collaborators, Affiliations

Risk of Potentially Preventable Hospitalizations After SARS-CoV-2 Infection

Diana J Govier et al. JAMA Netw Open. .

Abstract

Importance: Research demonstrates that SARS-CoV-2 infection is associated with increased risk of all-cause hospitalization. However, no prior studies have assessed the association between SARS-CoV-2 and potentially preventable hospitalizations-that is, hospitalizations for conditions that can usually be effectively managed in ambulatory care settings.

Objective: To examine whether SARS-CoV-2 is associated with potentially preventable hospitalization in a nationwide cohort of US veterans.

Design, setting, and participants: This cohort study used an emulated target randomized trial design with monthly sequential trials to compare risk of a potentially preventable hospitalization among veterans with SARS-CoV-2 and matched comparators without SARS-CoV-2. A total of 189 136 US veterans enrolled in the Veterans Health Administration (VHA) who were diagnosed with SARS-CoV-2 between March 1, 2020, and April 30, 2021, and 943 084 matched comparators were included in the analysis. Data were analyzed from May 10, 2023, to January 26, 2024.

Exposure: SARS-CoV-2 infection.

Main outcomes and measures: The primary outcome was a first potentially preventable hospitalization in VHA facilities, VHA-purchased community care, or Medicare fee-for-service care. Extended Cox models were used to examine adjusted hazard ratios (AHRs) of potentially preventable hospitalization among veterans with SARS-CoV-2 and comparators during follow-up periods of 0 to 30, 0 to 90, 0 to 180, and 0 to 365 days. The start of follow-up was defined as the date of each veteran's first positive SARS-CoV-2 diagnosis, with the same index date applied to their matched comparators.

Results: The 1 132 220 participants were predominantly men (89.06%), with a mean (SD) age of 60.3 (16.4) years. Most veterans were of Black (23.44%) or White (69.37%) race. Veterans with SARS-CoV-2 and comparators were well-balanced (standardized mean differences, all <0.100) on observable baseline clinical and sociodemographic characteristics. Overall, 3.10% of veterans (3.81% of those with SARS-CoV-2 and 2.96% of comparators) had a potentially preventable hospitalization during 1-year follow-up. Risk of a potentially preventable hospitalization was greater among veterans with SARS-CoV-2 than comparators in 4 follow-up periods: 0- to 30-day AHR of 3.26 (95% CI, 3.06-3.46); 0- to 90-day AHR of 2.12 (95% CI, 2.03-2.21); 0- to 180-day AHR of 1.69 (95% CI, 1.63-1.75); and 0- to 365-day AHR of 1.44 (95% CI, 1.40-1.48).

Conclusions and relevance: In this cohort study, an increased risk of preventable hospitalization in veterans with SARS-CoV-2, which persisted for at least 1 year after initial infection, highlights the need for research on ways in which SARS-CoV-2 shapes postinfection care needs and engagement with the health system. Solutions are needed to mitigate preventable hospitalization after SARS-CoV-2.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Maciejewski reported owning Amgen Inc stock due to spouse’s employment. Dr Viglianti reported receiving grant funding from the National Heart, Lung, and Blood Institute during the conduct of the study. Dr O’Hare reported receiving support for flights, meals, and lodging from the National Kidney Foundation Northern California, University of Colorado, and Dialysis Clinic Inc, and a mentorship award and lodging and meeting registration support from the American Society of Nephrology outside the submitted work. Dr Hynes reported receiving grant funding from the US Department of Veterans Affairs Health Services Research and Development (VA HSR&D), PacificSource Health Plan, and the David & Lucille Packard Foundation; personal fees from Quality Insights outside the submitted work; and being co-owner of Van Breemen & Hynes LLC for research consulting. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Cumulative Incidence of Potentially Preventable Hospitalizations During 1-Year Follow-Up Among Veterans With SARS-CoV-2 and Comparators
Cumulative incidence curves are shown with 95% CIs. With day 0 includes potentially preventable hospitalizations on day 0 (index date), and without day 0 excludes these. There is substantial overlap in cumulative incidence and 95% CIs for comparators with and without day 0 hospitalizations. Cumulative incidence individually censors for death and crossover infection.
Figure 2.
Figure 2.. Adjusted Hazard Ratios (AHRs) of Potentially Preventable Hospitalization Among Veterans With SARS-CoV-2 Relative to Comparators
Extended Cox models censor for deaths and crossover infections individually and are adjusted for nonpreventable hospitalizations as a time-varying covariate.
Figure 3.
Figure 3.. Subgroup Adjusted Hazard Ratios (AHRs) of Potentially Preventable Hospitalizations Among Veterans With SARS-CoV-2 Relative to Comparators
Subgroup analyses censored for deaths and crossover infections individually. Elixhauser rehospitalization risk score tertile 1 indicates (−4 to 6); tertile 2, (6 to 24); and tertile 3, (24 to 187), where overlapping score categories are mutually exclusive. Primary care (PC) shortage area indicates veteran residence. All subgroup analyses controlled for nonoutcome hospitalizations. In addition, the following were controlled for in each subgroup analysis due to covariate imbalance within subgroups: for age subanalyses, Medicare Advantage enrollment at index, Care Assessment of Need score category, smoking status, Nosos category, and Gagne score; for COVID-19 wave subanalyses, no additional covariates; for Elixhauser rehospitalization risk score tertile subanalyses, VHA primary care visits in the 24 months prior to index date, VHA specialty care visits in the 24 months prior to index date, and Nosos category; for PC shortage area subanalyses, no additional covariates; and for sex subanalyses, no additional covariates.

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