THE REACTION OF HOSPITALS FOR THE COMING DRGS PAYMENT SYSTEM

Abstract

本研究目的在探討健保局1999年宣佈將全面實施疾病診斷關係群( diagnosis related group; DRGs)支付制度後，不同特質醫院之因應表現。本研究係以1998年至2002年「住院醫療費用清單明細檔」申報資料共12，737，642筆進行長期資料分析，利用健保局提供之網路醫療資訊服務系統，轉出DRGs代碼，以1998年為基期年，計算各年度各醫院的平約編碼數、病例組合指標(case mix index; CMI)、平約住院日及14日同科再住院率，並利用廣義估計方程式(generalized estimating equation; GEE)，進行年度效應的統計檢定。研究結果發現相較於1998年，醫院年平約編碼數、年CMI值、及年14日同科再住院率有增加的情形，但年平約住院日自1999年開始有下降的情形；年平均編碼數自1999年開始逐年上升，以公立地區醫院及和立醫院增加最明顯；年CMI值自2000年開始逐年上升，以和立地區醫院增加最明顯；醫學中心及區域醫院年平約住院日自1999年開始持續有減少；年14日同科再住院率除公立地區教學醫院外，其他特質醫院有不同程度顯著的上升。即將全面實施DRGs支付制度已經使醫院行為有明顯的改變，不同特質醫院在研究期間，因應改變的程度亦有不同，而這些改變可能會對住院醫療照護品質產生影響。 To investigate the reaction of hospitals to the announcement of the coming diagnosis related groups (DRGs) payment system in 1999. The claimed data of 12, 737, 642 NHI inpatients from 1998 to 2002 was used for the longitudinal analyses. The DRG code was created by BNHI DRGs software. The annual average numbers of coded diagnoses, case-mix index (CMI), average length of stay (ALOS) and readmission rate (14-day) of each hospital were compared with the baseline data of 1998. The year effect was analyzed by the generalized estimating equation model. Comparing to the data in 1998, the annual average numbers of coded diagnoses, CMI, and readmission rate (14-day) was increased, but annual ALOS was decreased since 1999. The annual average numbers of coded diagnoses was increased since 1999. The annual average numbers of coded diagnoses of public district and private hospitals was increased more obvious than other type of hospitals. The annual CMI was increased since 2000 esp. in private district teaching hospitals. The ALOS of medical centers and regional hospitals was progressive decreased since 1999. The 14-day readmission rate was also increased since 1999. It is concluded that the coming DRGs payment system has changed hospital behavior. It also was found that different property of hospitals, during the study period, have different degree of impact on hospital reaction. This change of hospital behavior may influence the quality of health care.