Describing Iranian hospital activity using Australian refined DRGs: A case study of the Iranian Social Security Organisation

Ghaffari, Shahram, Jackson, Terri J., Doran, Christopher M., Wilson, Andrew and Aisbett, Chris (2008) Describing Iranian hospital activity using Australian refined DRGs: A case study of the Iranian Social Security Organisation. Health Policy, 87 1: 63-71. doi:10.1016/j.healthpol.2007.09.014


Author Ghaffari, Shahram
Jackson, Terri J.
Doran, Christopher M.
Wilson, Andrew
Aisbett, Chris
Title Describing Iranian hospital activity using Australian refined DRGs: A case study of the Iranian Social Security Organisation
Journal name Health Policy   Check publisher's open access policy
ISSN 0168-8510
1872-6054
Publication date 2008-07-01
Sub-type Article (original research)
DOI 10.1016/j.healthpol.2007.09.014
Open Access Status
Volume 87
Issue 1
Start page 63
End page 71
Total pages 9
Editor Katrien Kesteloot
Mia Defever
Place of publication Shannon, Ireland
Publisher Elsevier Ireland
Language eng
Subject C1
920208 Health Policy Evaluation
111799 Public Health and Health Services not elsewhere classified
1605 Policy and Administration
1117 Public Health and Health Services
Abstract Objective: To describe Iran's hospital activity with Australian Refined Diagnosis Related Groups (AR-DRGs). Method: A total of 445,324 separations was grouped into discreet DRG classes using AR-DRGs. LH; IQR and 10th-95th percentile were used to exclude outlier cases. Reduction in variance (R) and coefficient of variation (CV) were applied to measure model fit and within group homogeneity. Results: Total hospital acute inpatients were grouped into 579 DRG groups in which 'surgical' cases represented 63% of the total separations and 40% of total DRGs. Approximately 12.5% of the total separations fell into DRGs O60C (vaginal delivery) and 28% of the total separations classified into major diagnostic category (MDC) 14 (pregnancy and childbirth). Although reduction in variance (R) for untrimmed data was low (R = 0.17) for LOS, trimming by LH, IQR, and 10th-95th percentile methods improved the value of R to 0.53, 0.48, and 0.51, respectively. Low value of R for AR-DRGs within several MDCs were identified, and found to reflect high variability in one or two DRGs. High within-DRG variation was identified for 23% of DRGs using untrimmed data. Conclusion: Low quality and incomplete data undermines the accuracy of casemix information. This may require improvement in coding quality or further classification refinement in Iran. Further study is also required to compare AR-DRG performance with other versions of DRGs and to determine whether the low value of R for several MDCs is due to the weakness of the AR-DRG algorithm or to Iranian specific factors.
Formatted abstract
Objective
To describe Iran's hospital activity with Australian Refined Diagnosis Related Groups (AR-DRGs).

Method
A total of 445,324 separations was grouped into discreet DRG classes using AR-DRGs. L3H3; IQR and 10th–95th percentile were used to exclude outlier cases. Reduction in variance (R2) and coefficient of variation (CV) were applied to measure model fit and within group homogeneity.

Results
Total hospital acute inpatients were grouped into 579 DRG groups in which ‘surgical’ cases represented 63% of the total separations and 40% of total DRGs. Approximately 12.5% of the total separations fell into DRGs O60C (vaginal delivery) and 28% of the total separations classified into major diagnostic category (MDC) 14 (pregnancy and childbirth). Although reduction in variance (R2) for untrimmed data was low (R2 = 0.17) for LOS, trimming by L3H3, IQR, and 10th–95th percentile methods improved the value of R2 to 0.53, 0.48, and 0.51, respectively. Low value of R2 for AR-DRGs within several MDCs were identified, and found to reflect high variability in one or two DRGs. High within-DRG variation was identified for 23% of DRGs using untrimmed data.

Conclusion
Low quality and incomplete data undermines the accuracy of casemix information. This may require improvement in coding quality or further classification refinement in Iran. Further study is also required to compare AR-DRG performance with other versions of DRGs and to determine whether the low value of R2 for several MDCs is due to the weakness of the AR-DRG algorithm or to Iranian specific factors.
© 2007 Elsevier Ireland Ltd. All rights reserved.

Keyword Casemix
DRG performance
Hospital
Iran
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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Created: Wed, 25 Mar 2009, 01:02:28 EST by Geraldine Fitzgerald on behalf of School of Public Health