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Background: Medication claims are commonly used to calculate the risk adjustment for measuring healthcare cost. The Rx-defined Morbidity Groups (Rx-MG) which combine the use of medication to indicate morbidity have been incorporated into the Adjusted Clinical Groups (ACG) Case Mix System, developed by the Johns Hopkins University. This study aims to verify that the Rx-MG can be used for adjusting risk and for explaining the variations in the healthcare cost in Taiwan. Methods: The Longitudinal Health Insurance Database 2005 (LHID2005) was used in this study. The year 2006 was chosen as the baseline to predict healthcare cost (medication and total cost) in 2007. The final sample size amounted to 793 239 (81%) enrolees, and excluded any cases with discontinued enrolment. Two different kinds of models were built to predict cost: the concurrent model and the prospective model. The predictors used in the predictive models included age, gender, Aggregated Diagnosis Groups (ADG, diagnosis- defined morbidity groups), and Rx-defined Morbidity Groups. Multivariate OLS regression was used in the cost prediction modelling. Results: The concurrent model adjusted for Rx-defined Morbidity Groups for total cost, and controlled for age and gender had a better predictive R-square = 0.618, compared to the model adjusted for ADGs (R² = 0.411). The model combined with Rx-MGs and ADGs performed the best for concurrently predicting total cost (R² = 0.650). For prospectively predicting total cost, the model combined Rx-MGs and ADGs (R² = 0.382) performed better than the models adjusted by Rx-MGs (R² = 0.360) or ADGs (R² = 0.252) only. Similarly, the concurrent model adjusted for Rx-MGs predicting pharmacy cost had a better performance (R-square = 0.615), than the model adjusted for ADGs (R² = 0.431). The model combined with Rx-MGs and ADGs performed the best in concurrently as well as prospectively predicting pharmacy cost (R² = 0.638 and 0.505, respectively). The prospective models showed a remarkable improvement when adjusted by prior cost. Conclusions: The medication-based Rx-Defined Morbidity Groups was useful in predicting pharmacy cost as well as total cost in Taiwan. Combining the information on medication and diagnosis as adjusters could arguably be the best method for explaining variations in healthcare cost. [ABSTRACT FROM AUTHOR]

Background: Although performance measurement for assessing care quality is an emerging area, a system for measuring the quality of cancer care at the hospital level has not been well developed. The purpose of this study was to develop organization-based core measures for colorectal cancer patient care and apply these measures to compare hospital performance. Methods: The development of core measures for colorectal cancer has undergone three stages including a modified Delphi method. The study sample originated from 2004 data in the Taiwan Cancer Database, a national cancer data registry. Eighteen hospitals and 5585 newly diagnosed colorectal cancer patients were enrolled in this study. We used indicator-based and case-based approaches to examine adherences simultaneously. Results: The final core measure set included seventeen indicators (1 pre-treatment, 11 treatment-related and 5 monitoring-related). There were data available for ten indicators. Indicator-based adherence possesses more meaningful application than case-based adherence for hospital comparisons. Mean adherence was 85.8% (79.8% to 91%) for indicator-based and 82.8% (77.6% to 88.9%) for case-based approaches. Hospitals performed well (>90%) for five out of eleven indicators. Still, the performance across hospitals varied for many indicators. The best and poorest system performance was reflected in indicators T5-negative surgical margin (99.3%, 97.2% - 100.0%) and T7-lymph nodes harvest more than twelve(62.7%, 27.6% - 92.2%), both of which related to surgical specimens. Conclusions: In this nationwide study, quality of colorectal cancer care still shows room for improvement. These preliminary results indicate that core measures for cancer can be developed systematically and applied for internal quality improvement. [ABSTRACT FROM AUTHOR]