Lamers L M
Erasmus University Rotterdam, The Netherlands.
Health Policy. 1998 Jul;45(1):15-32. doi: 10.1016/s0168-8510(98)00031-1.
In many countries market-oriented health care reforms are high on the political agenda. A common element of these reforms is that the consumers may choose among competing health insurers or health plans, which are largely financed through premium-replacing capitation payments. Since 1993, Dutch sickness funds receive risk-adjusted capitation payments based on demographic factors. It has been shown that the predictive accuracy of a demographic capitation model improves when it is extended with diagnostic information from prior hospitalizations, in the form of Diagnostic Costs Groups (DCGs). In this study a DCG classification is developed using Dutch cost data of sickness fund members of all ages. The study also dealt with the question of how to handle high discretion diagnoses. For the Dutch situation high discretion diagnoses may be defined as those diagnoses for which day case treatment is a possible alternative for a hospital admission. Grouping persons with a hospital admission for high discretion diagnoses together with people without an admission resulted in a slight reduction of the predictive accuracy of the DCG model. Adequate risk-adjustment is critical to the success of market-oriented health care reforms. The use of diagnostic information from prior hospitalizations seems a promising option for improving the capitation formula.
在许多国家，以市场为导向的医疗保健改革在政治议程中占据重要位置。这些改革的一个共同要素是，消费者可以在相互竞争的健康保险公司或健康计划中进行选择，这些保险公司或健康计划主要通过保费替代人头费来融资。自1993年以来，荷兰的疾病基金根据人口统计因素获得风险调整后的人头费支付。研究表明，当人口统计人头费模型通过先前住院的诊断信息（以诊断成本组（DCG）的形式）进行扩展时，其预测准确性会提高。在本研究中，利用荷兰所有年龄段疾病基金成员的成本数据开发了一种DCG分类。该研究还处理了如何处理高自由度诊断的问题。对于荷兰的情况，高自由度诊断可定义为那些日间病例治疗可替代住院治疗的诊断。将因高自由度诊断而住院的人与未住院的人归为一组，会导致DCG模型的预测准确性略有下降。充分的风险调整对于以市场为导向的医疗保健改革的成功至关重要。利用先前住院的诊断信息似乎是改进人头费公式的一个有前景的选择。
