An Chuankai, O'Malley A James, Rockmore Daniel N
1Department of Computer Science, Dartmouth College, Hanover, 03755 NH USA.
2Department of Biomedical Data Science and the Dartmouth Institute of Health Policy and Clinical Practice in the Geisel School of Medicine at Dartmouth College, Lebanon, 03784 NH USA.
Appl Netw Sci. 2018;3(1):20. doi: 10.1007/s41109-018-0081-4. Epub 2018 Jul 31.
In this paper, we analyze the millions of referral paths of patients' interactions with the healthcare system for each year in the 2006-2011 time period and relate them to U.S. cardiovascular treatment records. For a patient, a "referral path" records the chronological sequence of physicians encountered by a patient (subject to certain constraints on the times between encounters). It provides a basic unit of analysis in a broader that encodes the flow of patients and information between physicians in a healthcare system. We consider referral networks defined over a range of interactions as well as the characteristics of referral paths, producing a characterization of the various networks as well as the physicians they comprise. We further relate these metrics and findings to outcomes in the specific area of cardiovascular care. In particular, we match a referral path to occurrences of Acute Myocardial Infarction (AMI) and use the summary measures of the referral path to predict the treatment a patient receives and medical outcomes following treatment. Some referral path features are more significant with respect to their ability to boost a tree-based predictive model, and have stronger correlations with numerical treatment outcome variables. The patterns of referral paths and the derived informative features illustrate the potential for using network science to optimize patient referrals in healthcare systems for improved treatment outcomes and more efficient utilization of medical resources.
在本文中，我们分析了2006 - 2011年期间每年数百万患者与医疗系统互动的转诊路径，并将它们与美国心血管治疗记录相关联。对于一名患者，一条“转诊路径”记录了患者遇到的医生的时间顺序（在就诊时间间隔上有一定限制）。它在更广泛的层面上提供了一个分析基本单元，对医疗系统中患者和医生之间的信息流进行编码。我们考虑了在一系列互动中定义的转诊网络以及转诊路径的特征，对各种网络及其所包含的医生进行了特征描述。我们进一步将这些指标和发现与心血管护理特定领域的结果相关联。特别是，我们将一条转诊路径与急性心肌梗死（AMI）的发生情况相匹配，并使用转诊路径的汇总测量来预测患者接受的治疗以及治疗后的医疗结果。一些转诊路径特征在提升基于树的预测模型的能力方面更为显著，并且与数值治疗结果变量具有更强的相关性。转诊路径的模式以及派生的信息特征说明了利用网络科学优化医疗系统中的患者转诊以改善治疗结果和更有效地利用医疗资源的潜力。
