<abstract xmlns="http://www.w3.org/1999/xhtml"><sec><h3>Introduction</h3><p>AR-DRG system for classification hospital episodes was implemented in Serbia to improve efficiency and transparency in the health system.</p></sec><sec><h3>Methods</h3><p>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).</p></sec><sec><h3>Results</h3><p>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.</p></sec><sec><h3>Conclusion</h3><p>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.</p></sec></abstract>

IntroductionAR-DRG system for classification hospital episodes was implemented in Serbia to improve efficiency and transparency in the health system.MethodsL3H3, 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).ResultsThere 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.ConclusionA 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.

Describing Serbian Hospital Activity Using Australian Refined Diagnosis Related Groups: A Case Study in Vojvodina Province

Slovenian Journal of Public Health

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Opis Srbske Bolnišnične Dejavnosti Z Uporabo Avstralskih Skupin Primerljivih Primerov Diagnoz: Prikaz za Vojvodino

IntroductionAR-DRG system for classification hospital episodes was implemented in Serbia to improve efficiency and transparency in the health...

Describing Serbian Hospital Activity Using Australian Refined Diagnosis Related Groups: A Case Study in Vojvodina Province

Article Category: Original scientific article

Data publikacji: 13 gru 2019

Zakres stron: 18 - 26

Otrzymano: 21 mar 2019

Przyjęty: 16 paź 2019

DOI: https://doi.org/10.2478/sjph-2020-0003

Słowa kluczowe
average length of stay, outliers, reduction of variance, AR-DRG, casemix, healthcare financing, clinical coding

© 2020 Aleksandar P Medarevic, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Describing Serbian Hospital Activity Using Australian Refined Diagnosis Related Groups: A Case Study in Vojvodina Province

Article Category: Original scientific article

Data publikacji: 13 gru 2019

Zakres stron: 18 - 26

Otrzymano: 21 mar 2019

Przyjęty: 16 paź 2019

DOI: https://doi.org/10.2478/sjph-2020-0003

Słowa kluczoweaverage length of stay, outliers, reduction of variance, AR-DRG, casemix, healthcare financing, clinical coding

© 2020 Aleksandar P Medarevic, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
average length of stay, outliers, reduction of variance, AR-DRG, casemix, healthcare financing, clinical coding