论文标题
建模医疗保健中的数量结果关系
Modelling volume-outcome relationships in health care
论文作者
论文摘要
尽管对护理质量与医疗保健提供者量之间的关联有持续的浓厚兴趣，但缺少分析它们的统一统计框架，许多研究都遭受了统计建模的不良选择。我们提出了一个灵活的，添加的混合模型，用于研究医疗保健中的数量结果关联，该模型考虑了个人患者特征以及通过多级方法的特定效果。更具体地说，我们将体积视为连续变量，其对所考虑结果的影响被建模为平滑函数。我们通过包括特定于患者的危险因素和通过随机拦截在提供商级别的聚类来考虑不同的病例混合。该策略使我们能够提取平滑的音量效应以及独立的提供商效应。这两个数量可以直接根据其幅度进行比较，这可以深入了解护理质量的可变性。基于因果关系，我们得出了可以将体积效应解释为因果效应的条件。本文为每个效果和参数的关节估计提供了每个估计数量的置信集。通过模拟研究和对德国医疗保健数据的应用来说明我们的方法。 关键词：医疗保健质量测量，数量结果分析，最低提供商数量，添加剂回归模型，随机拦截
Despite the ongoing strong interest in associations between quality of care and the volume of health care providers, a unified statistical framework for analyzing them is missing, and many studies suffer from poor statistical modelling choices. We propose a flexible, additive mixed model for studying volume-outcome associations in health care that takes into account individual patient characteristics as well as provider-specific effects through a multi-level approach. More specifically, we treat volume as a continuous variable, and its effect on the considered outcome is modelled as a smooth function. We take account of different case-mixes by including patient-specific risk factors and of clustering on the provider level through random intercepts. This strategy enables us to extract a smooth volume effect as well as volume-independent provider effects. These two quantities can be compared directly in terms of their magnitude, which gives insight into the sources of variability of quality of care. Based on a causal DAG, we derive conditions under which the volume-effect can be interpreted as a causal effect. The paper provides confidence sets for each of the estimated quantities relying on joint estimation of all effects and parameters. Our approach is illustrated through simulation studies and an application to German health care data. Keywords: health care quality measurement, volume-outcome analysis, minimum provider volume, additive regression models, random intercept
