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Predictors of Readmission, for Patients with Chronic Obstructive Pulmonary Disease (COPD) - A Systematic Review
Ronald Chow1, Olivia W So1, James H B Im2
1University Health Network, University of Toronto, Toronto, ON, Canada.
Insights
Identifying key predictors for chronic obstructive pulmonary disease (COPD) readmissions can improve patient care. This review details significant factors influencing COPD patient readmission risk.
Area of Science:
- Pulmonary Medicine
- Healthcare Management
- Clinical Epidemiology
Background:
- Chronic obstructive pulmonary disease (COPD) is a leading cause of death globally, imposing a substantial healthcare burden.
- Patient readmission significantly contributes to the high healthcare costs associated with COPD management.
- Effective prediction of readmission is crucial for optimizing patient outcomes and resource allocation.
Purpose of the Study:
- To systematically review and identify significant predictors and prediction scores for all-cause and COPD-related readmissions in patients with COPD.
- To synthesize current evidence on factors influencing COPD patient readmission to inform clinical practice and future research.
Main Methods:
- A comprehensive literature search was conducted across major databases (Ovid MEDLINE, Embase, Cochrane) up to June 2022.
- Studies included patients aged 40+ with COPD and reported readmission data within one year.
- Study quality was assessed, and significant predictors of readmission, along with their statistical significance (p-value), were extracted.
Main Results:
- The review included 242 articles covering over 16 million patients, with a low overall risk of bias.
- Sixty-four significant predictors for all-cause readmission and 23 for COPD-related readmission were identified.
- Key predictors encompass pre-admission characteristics (e.g., prior hospitalization, comorbidities), hospitalization details (e.g., length of stay), investigation results (e.g., anemia, FEV1), and discharge factors (e.g., home oxygen use, discharge destination).
Conclusions:
- Identified predictors can enhance the development of more accurate predictive models for COPD readmissions.
- Clinicians can utilize these findings to improve their assessment of individual patient readmission risk.
- Better risk stratification may lead to targeted interventions, potentially reducing readmission rates and improving patient management.
Introduction:
Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death globally and is responsible for over 3 million deaths annually. One of the factors contributing to the significant healthcare burden for these patients is readmission. The aim of this review is to describe significant predictors and prediction scores for all-cause and COPD-related readmission among patients with COPD.
Methods:
A search was conducted in Ovid MEDLINE, Ovid Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials, from database inception to June 7, 2022. Studies were included if they reported on patients at least 40 years old with COPD, readmission data within 1 year, and predictors of readmission. Study quality was assessed. Significant predictors of readmission and the degree of significance, as noted by the p-value, were extracted for each study. This review was registered on PROSPERO (CRD42022337035).
Results:
In total, 242 articles reporting on 16,471,096 patients were included. There was a low risk of bias across the literature. Of these, 153 studies were observational, reporting on predictors; 57 studies were observational studies reporting on interventions; and 32 were randomized controlled trials of interventions. Sixty-four significant predictors for all-cause readmission and 23 for COPD-related readmission were reported across the literature. Significant predictors included 1) pre-admission patient characteristics, such as male sex, prior hospitalization, poor performance status, number and type of comorbidities, and use of long-term oxygen; 2) hospitalization details, such as length of stay, use of corticosteroids, and use of ventilatory support; 3) results of investigations, including anemia, lower FEV1, and higher eosinophil count; and 4) discharge characteristics, including use of home oxygen and discharge to long-term care or a skilled nursing facility.
Conclusion:
The findings from this review may enable better predictive modeling and can be used by clinicians to better inform their clinical gestalt of readmission risk.
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