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A new clinical complexity model for the Australian Refined Diagnosis Related Groups myDRG Stellenmarkt Gesundheitswesen

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A new clinical complexity model for the Australian Refined Diagnosis Related Groups

A new clinical complexity model for the Australian Refined Diagnosis Related Groups (ScienceDirect).

Highlights • Australian Refined Diagnosis Related Groups (AR-DRG) V8.0 introduced a new complexity model. • It has a new way to statistically estimate the Diagnosis Complexity Level (DCL). • DCLs...

[...] The Australian Refined Diagnosis Related Groups (AR-DRG) underwent a major review in 2014 with changes implemented in Version 8.0 of the classification. The core to the changes was the development of a new methodology to estimate the Diagnosis Complexity Level (DCL) and to aggregate the complexity level of individual diagnoses to the complexity of an entire episode, resulting in an
Episode Clinical Complexity Score (ECCS). This paper provides an overview of
the new methodology and its application in Version 8.0.

Method
The AR-DRG V8.0 refinement project was overseen by a Classifications Clinical
Advisory Group and a Diagnosis Related Groups (DRG) Technical Group. Admitted
Patient Care National Minimum Dataset and the National Hospital Cost Data
Collection were used for complexity modelling and analysis.

Result
In total, Version 8.0 comprised 807 DRGs, including 3 error DRGs. Of the 321
Adjacent DRGs (ADRGs) that had a split, 315 ADRGs used ECCS as the only
splitting variable while the remaining 6 ADRGs used splitting variables other
than ECCS: 2 used age and 4 used transfer.

Discussion and conclusion
A new episode clinical complexity (ECC) model was developed and introduced in
AR-DRG V8.0, replacing the original model introduced in the 1990s. Clear AR-DRG
structure principles were established for revising the system. The new
complexity model is conceptually based and statistically derived, and results
in an improved relationship with actual variations in resource use due to
episode complexity.
[...]

Quelle: ScienceDirect, 13.09.2019

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erschienen am Freitag, 13.09.2019
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