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[Measuring case severity with a DRG-based reimbursement system].

Abstract

BACKGROUND: The Australian Refined Diagnosis-Related Groups (AR-DRGs) will be the model for the German DRGs (G-DRGs). Their system to measure severity of illness will be a major point of interest. METHOD: The most common systems for measuring severity of illness are presented and compared with the AR-DRGs based on criteria regarding applicability. RESULTS: None of the systems for measuring severity of illness fits all the criteria. They can be used for reimbursement of inpatient care or for quality assurance, but not for both at the same time. The designated areas for the use of the systems should not be exceeded. CONCLUSION: AR-DRGs are very complex in measuring the costs per case (severity of illness in terms of efficiency). They are not able to support quality assessment by risk adjustment (severity of illness in terms of medical complexity). A less complex system would have been easier to transfer to Germany with the same incentives for providing effective care.

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BibTeXRIS

Markus Lüngen, Karl W Lauterbach. 2002-02-15. [Measuring case severity with a DRG-based reimbursement system].. https://doi.org/10.1007/s00063-002-1128-x

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OBJECTIVE: Reliability of diagnoses coding is essential for the use of routine data in a national health care system. The present investigation compares reliability of diagnoses coding with ICD-10 between three groups of coding subjects. METHOD: One hundred and eighteen students coded 15 diagnoses lists, 27 medical managers from hospitals 34 discharge letters, and 13 coding specialists 12 discharge letters. Agreement in principal diagnosis was assessed using Cohen's Kappa and the fraction of coincidences over the number of pairs, agreement for the full set of diagnoses with a previously developed measure p(om). RESULTS: Kappa values were fair (managers) or moderate (coders) for terminal codes with 0.27 and 0.42 (agreement 29.2% versus 46.8%), substantial for the chapter level with 0.71 and 0.72 (agreement 78.3% versus 80.8%). p(om) was lower for the full set of diagnoses than for principal diagnoses, for example in case of managers with 0.21 versus 0.29 for terminal codes. Best results were achieved by students coding diagnoses lists. In summary, the results are remarkably lower than in earlier publications. CONCLUSION: The refinement of the ICD-10 accompanied by innumerous coding rules has established a complex environment that leads to significant uncertainties even for experts. Use of coded data for quality management, health care financing, and health care policy requires a remarkable simplification of ICD-10 to receive a valid image of health care reality.

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