[Using diagnosis relative groups mortality risk classification to assess medical quality].
OBJECTIVE
To introduce diagnosis related groups to assess the medical quality and try to establish an effective quality evaluation approach.


METHODS
Using Australia-Refined Diagnosis Related Groups, version 5.0 (AR-DRGs v5.0) to classify the 160 000 discharged cases from 7 large hospitals in Beijing in 2005. Based on this, mortality risk classification was established to adjust the whole-hospital risks. And then hospital mortality of all the risk groups from each hospital was calculated respectively, which was used as the basic quality assessment criterion. The differences between the assessment results from using the raw hospital mortality and from using Diagnosis Relative Groups Mortality Risk Classification (DRGs-MRC) were compared.


RESULTS
(1) The risk types were different among the discharged cases in different hospitals; (2) The assessment results from these two approaches about No.6 hospital were similar in that No.6 hospital had a good quality performance; (3) The raw hospital mortality was the lowest in No.2 hospital (0.98%), but the mortality of low risk group in this hospital was higher than the average level of the same risk group among these 7 hospitals; the status of No.5 hospital was much the same.


CONCLUSIONS
Compared with raw hospital mortality, DRGs-MRC improved the comparability of cases and the reliability of the assessment result.
Jian
Wei-yan
WY
Department of Health Policy and Management, Peking University School of Public Health, Beijing 100083, China.
Cui
Tao
T
Wang
Hong-yuan
HY
Hu
Mu
M
Huang
Yin-min
YM
Zhang
Xiu-mei
XM
Guo
Yan
Y
D002681:China; D003953:Diagnosis-Related Groups / Q000145:classification / Q000706:statistics & numerical data*; D005260:Female; D017052:Hospital Mortality; D006779:Hospitals, Public / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008499:Medical Records / Q000145:classification / Q000706:statistics & numerical data; D011785:Quality Assurance, Health Care / Q000379:methods / Q000706:statistics & numerical data