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首页> 外文期刊>Italian Journal of Public Health >Using DRG to analyze hospital production: a re-classification model based on a linear tree-network topology
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Using DRG to analyze hospital production: a re-classification model based on a linear tree-network topology

机译:使用DRG分析医院生产:基于线性树形网络拓扑的重新分类模型

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Background : Hospital discharge records are widely classified through 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 of 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 DRGs into a specialization-driven classification system has been conceived through the analysis of HUs discharging and the ICD-9-CM codes.?We propose a three-folded classification, based on the analysis of 1,670,755 Hospital Discharge Cards (HDCs) 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 give a practical application of the three-layered approach, based on the production of a Neurosurgical HU; we observe synthetically the profile of production (1,305 hospital discharges for 79 different DRG codes of 16 different MDC are grouped in 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, those produce a limited quote of the whole neurosurgical production, because the same activity can be realized by non-Neurosugical HUs). Conclusion : Our work may help to evaluate the hospital production for a rational planning of available resources, blunting information asymmetries between physicians and managers.
机译:背景:医院出院记录通过诊断相关组(DRG)系统被广泛分类;意大利目前使用的版本包含538种不同的代码,包括数千种诊断和程序。这些数字反映了简化工作的巨大努力,但是当前的分类系统对评估医院的生产和绩效几乎没有用。方法:由于给定医院单位(HU)的病例组合是由其医生的专业知识驱动的,因此通过对HUs出院和ICD-9-CM的分析,将DRG分为一个专业化分类系统代码。根据对伦巴第医院2010年生产的1,670,755张医院出院卡(HDC)的分析,我们提出了三类分类;它由32个专科(例如神经外科),124个专科(例如颅骨外科)和337个专科(例如颅骨切开术)组成。结果:基于神经外科HU的产生,我们给出了三层方法的实际应用。我们综合观察生产情况(将16种不同MDC的79种不同DRG代码的1,305例医院出院分为几组同质DRG代码),从而提供了更具信息量的生产比较(通过特定于工艺的比较,而不是原始或病例混合)标准化比较)和可能更充分的生产计划(考虑到同一城市的神经外科HU,由于非神经外科HU可以实现相同的活动,因此它们对整个神经外科生产的报价有限。)结论:我们的工作可能有助于评估医院的生产情况,以合理规划可用资源,减轻医生和管理人员之间的信息不对称。

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