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Learning Objective 1: The learner will be able to understand current pattern of cardiac rehabilitation in Taiwan.
Learning Objective 2: The learner will be able to knew the trend change of cardiac intervention and cardiac rehabilitation in the past 15 years (1996-2010) in Taiwan.
Cardiac rehabilitation (CR) program is an important step to recovery for patients who received percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) surgery. Although cardiac rehabilitation has been shown to be effective in reducing overall disability and to increase survival rate; the utilization rate post CABG procedure has been reported to be as low as 31% in the United States, and 46% in Taiwan. While the influencing factors for CR utilization in the western countries have been identified in the literature, such phenomenon has not been fully studied in Taiwan. 1) To understand current pattern of cardiac rehabilitation in Taiwan. Specifically, the relationship between CR utilization and its influencing factors such as demographic characteristics, patients’ geographic location, comorbidity, type of cardiac procedure, length of hospital stay, hospital category, hospital location, rehabilitation cost, and total medical cost. 2) To explore the trend change of cardiac intervention and cardiac rehabilitation in the past 15 years (1996-2010) in Taiwan.
Methods:
This will be a secondary data analysis using the dataset from 1) Taiwan National Health Insurance Database (1996-2010) and 2) Registry for contracted medical facilities (HOSB). The inclusion criteria are: Inpatient expenditures by admissions (1996-2010), ICD-9 primary diagnosis code AMI (410.9) or CAD (414.00), and Disposal operation code PTCA (?) or CABG (36.X).
Results:
This study will help to describe the current pattern and the past trend of CR utilization in Taiwan. The findings of this study will have strong clinical implication and contribution to future health policy making.
Conclusion:
The advantage of the large dataset may also be a limitation in that some of the influencing factor variables such as resources availability, transportation, and physicians/hospitals’ endorsement to CR may not be available for analysis.