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Using the Adjusted Clinical Groups System to identify high-risk hemodialysis patients in Taiwan

Published: June 6, 2010
Category: Reports
Authors: Chuang SL, Lee WC, Sun JM
Country: Taiwan
Language: null
Type: Population Health
Setting: Hospital

J Healthc Manag 11:311-326. Published in Chinese.

OBJECTIVES: There has been a rising number and cost of patients with regular hemodialysis in Taiwan. The objective of this study was to quantify patients’ morbidity burdens and to examine the association between patients’ morbidity burdens and mortality.

METHODS: Claims data of patients who received regular hemodialysis therapies in 2005 and at least four months in 2006 were used. The Adjusted Clinical Groups (ACGs) system was used to quantify individual’s morbidity burdens based on age, gender, and ambulatory and inpatient diagnoses. Patients were classified to five morbidity groups by individual’s number of Major Aggregated Diagnosis Groups (Major ADGs): very mild (0-1), mild (2), middle (3), severe (4), and very severe (5-8). The Kaplan-Meier curves was used to present the cumulative mortality rates for patients with varying morbidity burdens, and the Cox proportional hazard model was used to evaluate the associations between morbidity burdens and mortalities.

RESULTS: Claims data of 32,944 patients were analyzed. There were 61.9% patients with 1-2, 19.4% with 3, and 18.7% with 4 or more Major ADGs. Patient’s morbidity burden was significantly associated with his or her likelihood of mortality. Comparing to patients with 0-1 Major ADG, the adjusted hazard ratio was 1.90 for those with 2 Major ADGs, 5.71 for those with 3 Major ADGs, 9.60 for those with 3 Major ADGs, and 10.5 for those with 4 or more ADGs.

CONCLUSION: Using ACG case-mix adjustment tool can quantify patient’s morbidity burdens, which were significantly associated with patient’s mortality risk. The application of ACG system can screen the high-risk patients to disease management programs for better quality of care.

High Risk,Overall Morbidity Burden,Mortality Prediction,Taiwan

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