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Covid-19, Diagnostic History and Mortality from Medicare 1999-2021, In an All-Cause Mortality Approach
1The Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health.
Archives of Internal Medicine Research
|December 27, 2024
Summary
Pre-existing conditions like cancer and heart disease significantly increase mortality risk for individuals with COVID-19 (Coronavirus Disease 2019). Understanding these factors is crucial for managing patient populations and improving outcomes.
Area of Science:
- * Medical Informatics
- * Epidemiology
- * Public Health
Background:
- * SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) infections frequently co-occur with diverse pre-existing clinical conditions in mortality cases.
- * Encounter-level health data from Medicare beneficiaries (1999-2021) were utilized to assess the impact of non-COVID-19 diagnoses on all-cause mortality among COVID-19 positive cases.
Purpose of the Study:
- * To evaluate the influence of non-COVID-19 diagnostic events on all-cause mortality in Medicare beneficiaries diagnosed with COVID-19.
- * To identify prior diagnostic codes from pre-pandemic years that predict mortality risk in COVID-19 patients.
- * To inform patient population management strategies for COVID-19.
Main Methods:
- * Aggregation of encounter-level health records from all Medicare beneficiaries (1999-2021).
- * Construction of odds ratios using diagnostic history, age decile, study year, and survival status.
- * Application of Generalized Linear Models (GLM) to predict Decedent Observation Odds Ratio (DOOR), considering non-COVID conditions and COVID-19 status.
Main Results:
- * High Decedent Observation Odds Ratio (DOOR) measures were observed for diagnostic codes associated with inpatient COVID-19 mortality.
- * Significant DOOR measures were also noted for individuals with specific cancers, cardiac arrest, or acute tubular necrosis.
- * Prior clinical risk factors such as cancer, diabetes, cardiac, and respiratory diseases were identified as meaningful predictors of mortality.
Conclusions:
- * COVID-19 mortality is influenced by the primary infection and the exacerbation of pre-existing conditions.
- * Prior clinical risk factors, including cancer and cardiovascular disease, significantly impact mortality outcomes.
- * Long-COVID conditions are predictable from GLM models and require surviving the acute clinical presentation.
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