Social Networks in Medical Homes and Impact on Patient Care and Outcomes

医疗之家的社交网络及其对患者护理和结果的影响

• 批准号: 10548173
• 负责人: Lusine Poghosyan
• 金额: $ 35.95万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10548173
• 关键词: Social; Networks; Medical; Homes; Impact

The Patient-Centered Medical Home (PCMH) model aims to address primary care challenges such as poor access and quality and rising costs by delivering team-based care, particularly for chronic diseases. Yet little is known about the composition of effective teams to achieve best patient outcomes. Furthermore, how team members communicate, share advice, or help to deliver care or how the resulting social structures (i.e., social networks) affect quality and outcomes has not been studied. Our innovative mixed-methods study will fill this gap. We will combine analysis of team configurations and social networks in PCMH practices with assessment of quality of care and patient outcomes to identify team best practices. We will also collect qualitative data to assess the underlying teamwork dynamics not captured quantitatively. The specific aims are to: 1. Identify factors determining team configurations and the formation of social networks in primary care practices adopting the PCMH model. 2. Investigate how team configurations and social networks impact quality of care and patient outcomes for five chronic conditions. 3. Identify barriers, facilitators, and characteristics of teamwork for teams with different configurations, social networks, and performance. Practices (n=24) with the PCMH model at NewYork-Presbyterian Hospital/Columbia University and Weill Cornell Medical Centers and the University of Pittsburgh Medical Center will participate. We will recruit team members including clinicians and staff (n=1,437) through online surveys who will identify their team members from the clinic's roster and report with who they communicate, share advice and/or support, and trust or approach to solve problems. We expect an 80% response rate (n=1,150). We will obtain patient data on quality of care and outcomes for diabetes, asthma, hypertension, cardiovascular disease, and chronic obstructive pulmonary disease and merge it with survey data. ORA* and R software will be used for data analysis. We will map team configuration and social networks, visualize them, and compute network metrics. We will then build Exponential Random Graph Models to predict factors explaining the observed networks and multilevel models to assess the impact of network variables on quality of care and patient outcomes. Based on Aim 1 findings, we will recruit participants who are highly- (n=~20) and poorly- (n=~20) connected to their team members in social networks. Based on Aim 2 findings, we will recruit participants from high- (n=~20) and low- (n=~20) performing teams. We will conduct individual face- to-face interviews with them using an interview guide. Interviews will be audio-taped and transcribed, and data will undergo content analysis. Multiple researchers will code the data and identify themes. Quantitative and qualitative findings will be triangulated. This study has the potential to show how to facilitate teamwork and identify the most effective team attributes to assure best quality of care and outcomes particularly for patients with chronic diseases (AHRQ's priority population). This application is in response to the Special Emphasis Notice (SEN) NOT-HS-16-011 on AHRQ's interest in applications related to innovative primary care research.

以病人为中心的医疗之家（PCMH）模式旨在解决初级保健的挑战，如贫困 通过提供以团队为基础的护理，特别是对慢性病的护理，可获得性和质量以及不断上升的成本。但很少有人 了解有效团队的组成，以实现最佳的患者结果。此外，团队如何 成员沟通、分享建议或帮助提供护理，或者由此产生的社会结构（即，社会 网络）对质量和结果的影响尚未研究。我们创新的混合方法研究将填补这一空白 间隙我们将结合联合收割机的团队配置和社交网络的PCMH实践与评估分析 护理质量和患者结果，以确定团队最佳实践。我们还将收集定性数据， 评估未量化的潜在团队合作动力。具体目标是：1.识别 决定团队配置和初级保健实践中社交网络形成的因素 PCMH模型2.调查团队配置和社交网络如何影响护理质量， 五种慢性疾病的患者结局。3.确定团队合作的障碍、促进因素和特点， 具有不同配置、社交网络和性能的团队。使用PCMH模型的实践（n=24） 在纽约长老会医院/哥伦比亚大学和威尔康奈尔医学中心以及大学 匹兹堡医疗中心将参加。我们将招募包括临床医生和工作人员在内的团队成员（n= 1，437） 通过在线调查，他们将从诊所的名册中识别他们的团队成员，并报告他们与谁一起工作 沟通，分享建议和/或支持，信任或解决问题的方法。我们预计80% 应答率（n= 1，150）。我们将获得有关糖尿病、哮喘、 高血压、心血管疾病和慢性阻塞性肺疾病并与调查合并 数据将使用ORA* 和R软件进行数据分析。我们将绘制团队配置和社交网络， 可视化并计算网络指标。然后，我们将构建指数随机图模型来预测 解释观察到的网络和多层次模型的因素，以评估网络变量对 护理质量和患者结局。根据目标1的研究结果，我们将招募高度- 在社交网络中，与团队成员的联系较差（n =~20）。根据目标2的发现，我们 将从高绩效团队（n=~20）和低绩效团队（n=~20）中招募参与者。我们将进行个人面对面- 使用面试指南对他们进行面对面的面试。采访将录音和转录，数据 将进行内容分析。多名研究人员将对数据进行编码并确定主题。定量和 将对定性结果进行三角分析。这项研究有可能表明如何促进团队合作， 确定最有效的团队属性，以确保最佳的护理质量和结果，特别是对患者而言 慢性病患者（AHRQ的优先人群）。本申请是为了回应特别强调 通知（SEN）NOT-HS-16-011关于AHRQ对创新初级保健研究相关应用的兴趣。