论文标题
一种系统的监视和检测分层医疗保健成本驱动因素和利用率的方法
A Systematic Approach to Surveillance and Detection of Hierarchical Healthcare Cost Drivers and Utilization Offsets
论文作者
论文摘要
医疗保健付款人中有浓厚的兴趣，以确定新兴的医疗保健成本驱动因素以支持早期干预。但是，在分析大型，高维和嘈杂的医疗保健数据方面出现了许多挑战。在本文中，我们提出了一种系统的方法，该方法利用层次搜索策略并增强统计过程控制（SPC）算法来表现出高影响力的成本驱动因素。我们的方法旨在提供归因于多种临床因素的可解释，详细和可行的见解。我们还提出了一种算法，以确定人群水平上的可比治疗偏移，并量化成本对其利用变化的影响。为了说明我们的方法，我们将其应用于IBM Watson Health MarketScan商业数据库，并将检测到的新兴驱动程序组织为5个类别以进行报告。我们还讨论了此分析中的一些发现以及减轻驾驶员影响的潜在行动。
There is strong interest among healthcare payers to identify emerging healthcare cost drivers to support early intervention. However, many challenges arise in analyzing large, high dimensional, and noisy healthcare data. In this paper, we propose a systematic approach that utilizes hierarchical search strategies and enhanced statistical process control (SPC) algorithms to surface high impact cost drivers. Our approach aims to provide interpretable, detailed, and actionable insights of detected change patterns attributing to multiple clinical factors. We also proposed an algorithm to identify comparable treatment offsets at the population level and quantify the cost impact on their utilization changes. To illustrate our approach, we apply it to the IBM Watson Health MarketScan Commercial Database and organized the detected emerging drivers into 5 categories for reporting. We also discuss some findings in this analysis and potential actions in mitigating the impact of the drivers.
