Background: Hospital discharge records are widely classified by the Diagnosis Related Group (DRG) system; the version currently used in Italy counts 538 different codes, including thousands of diagnosis and procedures. These numbers reflect the considerable effort towards simplification, yet the current classification system is of little use to evaluate hospital production and performance.Methods: As the case-mix of a given Hospital Unit (HU) is driven by its physicians’ specializations, a grouping of DRG s into a specialization-driven classification system has been conceived through the analysis of HUs discharging and the ICD -9-CM codes. We shall propose a physicians’ competencecentred classification, based on the analysis of 1,670,755 Hospital Discharge Cards (HDC s) produced by Lombardy Hospitals in 2010; it consists of 32 specializations (e.g. Neurosurgery), 124 sub-specialization (e.g. skull surgery) and 337 sub-sub-specialization (e.g. craniotomy).Results: We shall offer a practical application of our classification, based on the production of a Neurosurgical HU; we shall observe synthetically the profile of production (1,305 hospital discharges for 79 different DRG codes of 16 different MDC are divided into few groups of homogeneous DRG codes), a more informative production comparison (through process-specific comparisons, rather than crude or case-mix standardized comparisons) and a potentially more adequate production planning (considering the Neurosurgical HUs of the same city, that produce a limited quote of the whole neurosurgical production, since the same activity can be realized by non-Neurosugical HUs).Conclusions: Our work may help evaluate the hospital production for a rational planning of available resources, blunting information asymmetries between physicians and managers.

Lanzarini, A., Lafranconi, A., Nonis, M., Madotto, F., Grillo, P., Olgiati, S., et al. (2014). Using DRG to analyze hospital production: A re-classification model based on a linear tree-network topology. EPIDEMIOLOGY BIOSTATISTICS AND PUBLIC HEALTH, 11(3), e9347-e9347-11 [10.2427/9347].

Using DRG to analyze hospital production: A re-classification model based on a linear tree-network topology

LAFRANCONI, ALESSANDRA
Secondo
;
MADOTTO, FABIANA;OLGIATI, STEFANO
Penultimo
;
CESANA, GIANCARLO
Ultimo
2014

Abstract

Background: Hospital discharge records are widely classified by the Diagnosis Related Group (DRG) system; the version currently used in Italy counts 538 different codes, including thousands of diagnosis and procedures. These numbers reflect the considerable effort towards simplification, yet the current classification system is of little use to evaluate hospital production and performance.Methods: As the case-mix of a given Hospital Unit (HU) is driven by its physicians’ specializations, a grouping of DRG s into a specialization-driven classification system has been conceived through the analysis of HUs discharging and the ICD -9-CM codes. We shall propose a physicians’ competencecentred classification, based on the analysis of 1,670,755 Hospital Discharge Cards (HDC s) produced by Lombardy Hospitals in 2010; it consists of 32 specializations (e.g. Neurosurgery), 124 sub-specialization (e.g. skull surgery) and 337 sub-sub-specialization (e.g. craniotomy).Results: We shall offer a practical application of our classification, based on the production of a Neurosurgical HU; we shall observe synthetically the profile of production (1,305 hospital discharges for 79 different DRG codes of 16 different MDC are divided into few groups of homogeneous DRG codes), a more informative production comparison (through process-specific comparisons, rather than crude or case-mix standardized comparisons) and a potentially more adequate production planning (considering the Neurosurgical HUs of the same city, that produce a limited quote of the whole neurosurgical production, since the same activity can be realized by non-Neurosugical HUs).Conclusions: Our work may help evaluate the hospital production for a rational planning of available resources, blunting information asymmetries between physicians and managers.
Articolo in rivista - Articolo scientifico
DRG; Hospital; Performance
English
e9347
e9347-11
Lanzarini, A., Lafranconi, A., Nonis, M., Madotto, F., Grillo, P., Olgiati, S., et al. (2014). Using DRG to analyze hospital production: A re-classification model based on a linear tree-network topology. EPIDEMIOLOGY BIOSTATISTICS AND PUBLIC HEALTH, 11(3), e9347-e9347-11 [10.2427/9347].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/62693
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