Evaluation of hospital outcomes: Predictors of length of stay, rehospitalization and mortality (LOHS)

Background

Public health faces the dual challenge of providing optimal care while managing costs, particularly with an aging population and increasing prevalence of chronic conditions. Public hospitals, which often serve older patients with lower socioeconomic status and higher comorbidities, are under pressure to improve quality while reducing costs. Key quality indicators, such as length of hospital stay (LOHS), rehospitalization, and mortality rates, are essential for monitoring and comparing hospital performance.

Aim and Relevance

This research aims to identify predictors of LOHS, rehospitalization, and mortality in patients with pulmonary embolism (PE), chronic obstructive pulmonary disease (COPD), and community-acquired pneumonia (CAP). By understanding these predictors, the project seeks to:

1. Address modifiable factors to develop strategies for improving patient outcomes.
2. Raise awareness among clinicians about non-modifiable risk profiles.
3. Inform the development of better prediction models.
4. Optimize hospital bed management strategies.
5. Provide evidence-based recommendations for policymakers and healthcare providers.

General Conclusions

• PE Cohort Study: The PESI score, diabetes, serum troponin, and NT-proBNP levels are significant predictors for LOHS, mortality, and rehospitalization. These findings highlight the importance of comprehensive risk assessment for PE patients.
• CAP Cohort Study: Factors such as sex, age, qSOFA score, and presence of cancer significantly influence LOHS, rehospitalization, and mortality. Rehabilitation post-discharge plays a crucial role in rehospitalization rates.
• AECOPD Cohort Study: Oxygen supplementation at admission, age, COPD GOLD III/IV, active cancer, and rehabilitation are significant predictors of LOHS and mortality. The study emphasizes the complexity of predicting rehospitalization in AECOPD patients and suggests incorporating disease course variables for better accuracy.

Overall, the findings underscore the significance of disease-specific and broader health system factors in predicting hospital outcomes. The research aims to enhance patient management, discharge planning, and hospital performance, ultimately contributing to improved public healthcare systems for an aging population with complex chronic conditions.