Epidemiology of Care Teams: Network Analysis of Providers and Shared Patients

护理团队的流行病学：提供者和共享患者的网络分析

基本信息

批准号：
8570303
负责人：
KENNETH D MANDL
金额：
$ 27.88万
依托单位：
BOSTON CHILDREN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-09-01 至 2015-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8570303
关键词：
Address Awareness Caring Characteristics Communication Computing Methodologies Congestive Heart Failure Cost Control Data Data Set Electronic Health Record Epidemiology Group Practice Health Health Maintenance Organizations Health Personnel Health Professional Health system Healthcare Healthcare Systems Individual Information Systems Information Technology Insurance Internist Link Marketing Measurement Measures Medical Medical Care Team Medicare Methods Metric Modeling Nature Nurses Operative Surgical Procedures Outcome Pathway Analysis Patient Care Patient Care Team Patients Pharmaceutical Preparations Physicians Policy Maker Population Population Study Primary Care Physician Protocols documentation Provider Quality of Care Regimen Research Research Infrastructure Services Side Single-Payer System Social Network Structure Surveys System Testing Variant Weight Work beneficiary care delivery cost design experience health care delivery health care model health care quality improved innovation member network models novel patient oriented public health relevance tool

项目摘要

DESCRIPTION (provided by applicant): In a survey of primary care physicians taking care of Medicare beneficiaries, an average physician coordinates care with 229 other physicians working in 117 practices. Normalized, this is equivalent to 99 physicians and 53 practices for every 100 Medicare beneficiaries. The sheer magnitude of the US Healthcare system, providing services to more than 350 million patients, makes this a "big data" problem. Each patient is at the center of a cluster of providers. We seek to measure interconnectedness among health care providers in a system where data tend to be siloed by payor, and therefore do not reflect many inter-provider connections. We construct a unique dataset of selected geographically-defined markets, ultra-penetrated by a single payor and with it, define the epidemiology of health care teams and team structure. Building on our experience in network modeling with insurance claims data, we adapt tools from social network analysis to characterize the nature of fragmented team care in the US health system. We develop computational methods to allow policy makers to understand the "big data" problem of the healthcare social network infrastructure of linked providers and patients. Beyond social network analysis of provider relationships and the flow of information and influence through large networks, we develop novel social networking methods for health system data using the patient-centered team (essentially a network of providers around a single patient) as the primary unit. A provider network is built where each node is an individual provider. Links between provider pairs are weighted by the number of patients they share. We introduce the network-derived concept of "team stability" and develop novel methods to quantify it. These innovative metrics allow elucidation of the baseline epidemiology of teams through the first broad-scale system measurements of team structure in the US Healthcare system. We hypothesize that that the national population of providers constantly assorts and re-assorts into a staggeringly large number of different care teams (perhaps millions). As an initial test of the validity of our team constructs, we conduct a formative study of the association between team characteristics and health care quality metrics.

描述（由申请人提供）：在一项针对照顾 Medicare 受益人的初级保健医生的调查中，平均有一名医生与 117 个诊所的 229 名其他医生协调护理工作。标准化后，这相当于每 100 名 Medicare 受益人拥有 99 名医生和 53 家诊所。美国医疗保健系统规模庞大，为超过 3.5 亿患者提供服务，这使得这成为一个“大数据”问题。每个患者都是一组提供者的中心。我们试图衡量系统中医疗保健提供者之间的相互联系，在该系统中，数据往往被付款人孤立，因此不能反映许多提供者之间的联系。我们构建了选定的地理定义市场的独特数据集，由单一付款人进行超渗透，并用它来定义医疗保健团队和团队结构的流行病学。基于我们在保险索赔数据网络建模方面的经验，我们采用社交网络分析工具来描述美国卫生系统中分散的团队护理的性质。我们开发计算方法，使政策制定者能够了解链接的提供者和患者的医疗保健社交网络基础设施的“大数据”问题。除了通过大型网络对提供者关系以及信息流和影响力进行社交网络分析之外，我们还使用以患者为中心的团队（本质上是围绕单个患者的提供者网络）作为主要单位，为卫生系统数据开发了新颖的社交网络方法。构建了一个提供商网络，其中每个节点都是一个单独的提供商。提供者对之间的链接根据他们共享的患者数量进行加权。我们引入了网络衍生的“团队稳定性”概念，并开发了新的方法来量化它。这些创新指标可以通过对美国医疗保健系统团队结构的首次大规模系统测量来阐明团队的基线流行病学。我们假设，全国提供者群体不断地组合并重新组合成数量惊人的不同护理团队（可能有数百万）。作为对我们团队结构有效性的初步测试，我们对团队特征与医疗保健质量指标之间的关联进行了形成性研究。