Trend Analysis and Outcome Prediction in Mechanically Ventilated Patients: A Nationwide Population-Based Study in Taiwan

Objective

To investigate the relationship between changes in patient attributes and hospital attributes over time and to explore predictors of medical utilization and mortality rates in mechanical ventilation (MV) patients in Taiwan.

Background

Providing effective medical care for MV patients is challenging and requires good planning and effective clinical decision making policies. Most studies of MV, however, have only analyzed a single regional ventilator weaning center or respiratory care unit, high-quality population-based studies of MV trends and outcomes are scarce.

Methods

This population-based cohort study retrospectively analyzed 213,945 MV patients treated during 2004-2009.

Results

During the study period, the percentages of MV patients with the following characteristics significantly increased: age ≦ 65 years, treatment at a medical center, and treatment by a high-volume physician. In contrast, the percentages of MV patients treated at local hospitals and by low-volume physicians significantly decreased (P<0.001). Age, gender, Deyo-Charlson co-morbidity index, teaching hospital, hospital level, hospital volume, and physician volume were significantly associated with MV outcome (P<0.001). Over the 6-year period analyzed in this study, the estimated mean hospital treatment cost increased 48.8% whereas mean length of stay decreased 13.9%. The estimated mean overall survival time for MV patients was 16.4 months (SD 0.4 months), and the overall in-hospital 1-, 3-, and 5-year survival rates were 61.0%, 36.7%, 17.3%, and 9.6%, respectively.

Conclusions

These population-based data revealed increases in the percentages of MV patients treated at medical centers and by high-volume physicians, especially in younger patients. Notably, although LOS for MV patients decreased, hospital treatment costs increased. Healthcare providers and patients should recognize that attributes of both the patient and the hospital may affect outcomes.