Describing Serbian Hospital Activity Using Australian Refined Diagnosis Related Groups: A Case Study in Vojvodina Province
Article Category: Original scientific article
Published Online: Dec 13, 2019
Page range: 18 - 26
Received: Mar 21, 2019
Accepted: Oct 16, 2019
DOI: https://doi.org/10.2478/sjph-2020-0003
Keywords
© 2020 Aleksandar P Medarevic, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Introduction
AR-DRG system for classification hospital episodes was implemented in Serbia to improve efficiency and transparency in the health system.
Methods
L3H3, IQR, and 10th–95th percentile methods were used to identify outlier episodes in the classification. Classification efficiency and within-group homogeneity were measured by an adjusted reduction in variance (R2) and a coefficient of variation (CV).
Results
There were 246,131 hospital episodes with a total 1,651,913 bed days from 14 hospitals. All episodes were classified into 652 groups of which 441 had CV lower than 100%. “Medical groups” accounted for 51% of groups and for 72% of episodes. Chemotherapy and vaginal delivery were the highest volume groups, with 5% and 4% of total episodes. Major diagnostic category 6 (MDC 6, Diseases of the digestive system) was the highest volume MDC, accounting for 11% of episodes. “Day-cases” and “prolonged hospitalisation” accounted for 21% and 3% of episodes, respectively. The average length of stay varied from 5.6 to 8.2 days. Adjusted R2 was 0.3 for untrimmed data. Trimming by L3H3, IQR, and 10th–95th percentile method improved the value of adjusted R2 to 0.61, 0.49, and 0.51, identifying 24%, 7%, and 7% of total cases as outliers, respectively. Mental diseases (MDC 19) remained the lowest adjusted R2 in untrimmed and trimmed datasets.
Conclusion
A long length of stay and a small percentage of “day-cases” characterized hospital activity in Vojvodina. Trimming methods significantly improved DRG efficiency. Future studies should consider cost data.