Objective: To diagnose, compare, and predict the balanced scorecard (BSC) performances within and between hospitals each year. Methods: We used a multi-faceted Rasch Model (MFRM) to analyze BSC data from seven government-run hospitals in Taiwan for 2004 and 2005, and compared the results with traditional parametric and nonparametric methods. Results: Comparison of the results of various statistical tests suggests that the MFRM can be robust enough to predict BSC performance in hospitals. Its distribution-free estimation of latent independent and dependent variable interactions are suitable for small sample sizes, and repeated measurements at various points in time. Conclusions: This study provides examples of the rescaling of hospital performance data through the MFRM. Its findings suggest that hospital executives and researchers should routinely consider rescaling ordinal data by using the Rasch measurement technique to evaluate and predict the BSC responses in hospitals. Copyright © 2012 DRUNPP, Sarajevo.
|Publication status||Published - 2012|
CitationChien, T.-W., Wang, W.-C., Su, S.-B., & Kuo, S.-C. (2012). Comparison of hospital balanced Scorecard (BSC) performance among seven hospitals in Taiwan using the Multi-faceted Rasch Model: Diagnosis and prediction. HealthMED, 6(2), 395-402.
- Multi-faceted Rasch Model
- Nonparametric methods
- Balanced scorecard
- Rasch measurement