Abstract

PHP118 Patterns and Predictors of HosPital readmission in taiwan Cheng J.S.1, Ku H.P.1, Chang C.J.2 1Chang Gung University, Tao-Yuan, Taiwan, 2Chang Gung University, Kwei Shan, Tao Yuan, Taiwan Objectives: Hospital readmissions have been an important issue, as they reflect suboptimal quality of medical care and incur high health care expenditures. However, limited information is available on the patterns of hospital readmission in the entire population to support a thorough planning to prevent hospital readmissions. Therefore, this study aimed to examine the patterns and economic burden of hospital readmission in Taiwan, and identify predictors of hospital readmissions. MethOds: This study used the National Health Insurance Research Database of enrollees randomly selected from those enrolled in the National Health Insurance program in 2005. Individuals who were admitted to acute hospitals in 2005 were selected and their readmission patterns one-year after discharge were examined. Cox proportional hazards regression model was adopted to identify predictors of hospital readmission. Results: The 30-day, 6-month and one-year readmission rates were 11%, 25%, and 34%, respectively. During the one-year follow-up, 52% of total health care expenditures were due to hospital readmissions. Of those who were readmitted to hospitals, 56% were readmitted once and took up 29% of the cost of rehospitalization. However, those readmitted for more than three times (5%) accounted for 30% of the cost. The major disease category of the highest 30-day and one-year readmission rates was neoplasms. The disease of the highest 30-day and one-year readmission rates were cancer of bronchus and lung (36%) and cancer of liver and intrahepatic bile duct (74%), respectively, and the most frequent reason for readmission was the disease itself. Age, gender, place of residence, previous hospitalization history, comorbidities, and length of stay of the index hospitalization were risk factors of hospital readmissions. cOnclusiOns: This study identified diseases of higher short-term and long-term readmission rates, causes of shortterm and long-term hospital readmissions, and predictors of hospital readmission. The information is of importance for planning interventions to reduce hospital readmission rate.

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