Onnela Jukka-Pekka, O'Malley A James, Keating Nancy L, Landon Bruce E
1Harvard T.H. Chan School of Public Health, Harvard University, 655 Huntington Avenue, Boston, MA USA.
2Department of Biomedical Data Science, The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Hanover, NH USA.
Appl Netw Sci. 2018;3(1):28. doi: 10.1007/s41109-018-0084-1. Epub 2018 Aug 13.
To compare standard methods for constructing physician networks from patient-physician encounter data with a new method based on clinical episodes of care.
We used data on 100% of traditional Medicare beneficiaries from 51 nationally representative geographical regions for the years 2005-2010.
We constructed networks of physicians based on their shared patients. In the fixed-threshold networks and adaptive-threshold networks, we included data on all patient-physician encounters to form the physician-physician ties, and then subsequently thresholded some proportion of the strongest ties. In contrast, in the episode-based approach, only those patient-physician encounters that occurred within shared clinical episodes treating specific conditions contributed towards physician-physician ties.
DATA COLLECTION/EXTRACTION METHODS: We extracted clinical episodes in the Medicare data and investigated structural properties of the patient-sharing networks of physicians, temporal dynamics of their ties, and temporal stability of network communities across the two approaches.
The episode-based networks accentuated ties between primary care physicians (PCPs) and medical specialists, had ties that were more likely to reappear in the future, and appeared to have more fluid community structure.
Constructing physician networks around shared episodes of care is a clinically sound alternative to previous approaches to network construction that does not require arbitrary decisions about thresholding. The resulting networks capture somewhat different aspects of patient-physician encounters.
比较从患者-医生诊疗数据构建医生网络的标准方法与基于临床护理事件的新方法。
我们使用了2005 - 2010年来自51个具有全国代表性地理区域的100%传统医疗保险受益人的数据。
我们基于医生共享的患者构建医生网络。在固定阈值网络和自适应阈值网络中，我们纳入了所有患者-医生诊疗数据以形成医生-医生联系，然后对一定比例的最强联系设置阈值。相比之下，在基于事件的方法中，只有那些在治疗特定疾病的共享临床事件中发生的患者-医生诊疗才构成医生-医生联系。
数据收集/提取方法：我们从医疗保险数据中提取临床事件，并研究医生的患者共享网络的结构特性、其联系的时间动态以及两种方法下网络社区的时间稳定性。
基于事件的网络突出了初级保健医生（PCP）与医学专家之间的联系，其联系在未来更有可能再次出现，并且似乎具有更灵活的社区结构。
围绕共享护理事件构建医生网络是一种临床上合理的替代先前网络构建方法的方式，无需对阈值进行任意决策。由此产生的网络捕捉了患者-医生诊疗的一些不同方面。
