Improving Population Health Through Enhanced Targeted Regional Decision Support

通过加强有针对性的区域决策支持改善人口健康

• 批准号: 8533932
• 负责人: Brian E. Dixon
• 金额: $ 42.81万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-30 至 2016-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8533932
• 关键词: Improving; Population; Health; Through; Enhanced

Project Summary/Abstract Comprehensive clinical information from a broad set of data sources is required for many healthcare tasks, including comparative effectiveness research, improving clinical care processes, and improving overall population health. Health information exchanges (HIEs) are an emerging source of healthcare data aggregation and comprehensive clinical data for these purposes. It is well-known that traditional clinical care processes underreport population level disease burden for a variety of reasons: reporters are overburdened or under resourced and they lack knowledge and/or willingness; and clinical data is scattered across different systems in different formats, which makes completing reports burdensome. Incomplete reporting can lead to inaccurate assessment of the disease burden in a community, which further hinders population health interventions and only partially informs preventive care delivered to individual patients. Our long-term goal is to improve population health through innovative informatics strategies that seamlessly integrate and effectively use practice-based population health tools in clinical care. The objective in this project is to improve the effectiveness of acute and preventative care processes by improving information sharing and data quality among healthcare providers and population health stakeholders using novel decision support tools. These tools will deliver reminders to clinical providers using pre-populated reportable condition forms that contain patient demographics and pertinent case management information. Further, this research will investigate the process and effects of deploying a framework to integrate HIE data captured from present and previous clinical encounters to improve the identification and reporting of conditions of population health significance. The central hypothesis of this proposal is that automated data capture and information enhancements will streamline provider-based population health reporting workflows, lower barriers to reporting and case follow-up, increase data completeness, capture a greater portion of communicable disease burden in the community, and improve population health. While this project focuses on the impact of novel population health decision support technology, the framework is applicable to a variety of use-cases. Thus, findings from this project will inform future large-scale clinical decision support initiatives in heterogeneous technical settings. We propose to employ both quantitative and qualitative research methods to determine the data elements and data characteristics vital for clinician case reporting, public health consumption of these reports and bidirectional transmission of case reporting information among population health stakeholders.

项目摘要/摘要 许多医疗保健任务需要一组广泛数据源的全面临床信息， 包括比较有效性研究，改善临床护理过程并改善整体 人口健康。健康信息交流（HIE）是医疗保健数据的新兴来源 用于这些目的的聚集和综合临床数据。众所周知，传统的临床护理 由于各种原因，流程不足的人口水平疾病负担负担：记者负担重大或 资源不足，他们缺乏知识和/或意愿；临床数据散布在不同的 以不同格式的系统，使报告完成了繁重的报告。不完整的报告可能导致 对社区中疾病负担的评估不准确，这进一步阻碍了人口健康 干预措施，仅部分告知提供给个别患者的预防保健。 我们的长期目标是通过创新的信息学策略来改善人口健康， 在临床护理中无缝整合并有效地使用基于实践的人群健康工具。目标 在这个项目中，是通过改善急性和预防性护理过程的有效性 使用医疗保健提供者和人口健康利益相关者之间的信息共享和数据质量 新颖的决策支持工具。这些工具将使用预先填充的临床提供商向临床提供者提供提醒 可报告的状况形式，其中包含患者人口统计和相关病例管理信息。 此外，这项研究将研究部署框架以整合HIE数据的过程和影响 从现在和以前的临床相遇中捕获，以改善条件的识别和报告 人口健康的重要性。该提案的中心假设是自动数据捕获和 信息增强功能将简化基于提供者的人口健康报告工作流程，较低的障碍 进行报告和案例随访，提高数据完整性，捕获更大的可传染性 社区中的疾病负担，改善人口健康。 尽管该项目着重于新的人口健康决策支持技术的影响，但 框架适用于各种用例。因此，该项目的发现将为未来的大规模提供信息 异质技术环境中的临床决策支持计划。我们建议使用两种定量 以及确定对临床医生至关重要的数据元素和数据特征的定性研究方法 案例报告，这些报告的公共卫生消费以及案例报告的双向传播 人口健康利益相关者之间的信息。