Discern Health , Baltimore, Maryland.
J Palliat Med. 2018 Mar;21(S2):S1-S6. doi: 10.1089/jpm.2017.0596.
Successful implementation of a comprehensive accountability system for community-based serious illness care will require a robust data infrastructure. Data will be needed to support care delivery, quality measurement, value-based payment, and evaluation and monitoring.
The specific data needs in these areas need to be identified and understood, so that gaps in currently available data may be addressed.
We developed a framework that includes the needed data and data infrastructure to support the features and characteristics of a serious illness care accountability system. Based on this framework, we analyze the current data landscape to identify gaps in available data resources and capacities. This analysis was informed by conducting Internet-based research, interviews with key informants, and a survey of key informants.
Based on the identified gaps, we present a series of priority recommendations for advancing the data infrastructure to support community-based serious illness care. These recommendations include additional measurement of patient-reported outcomes, increasing interoperability among various data sources, increasing development and exchange of patient care plans, leveraging newly standardized data on patient functional and cognitive status, and using patient-reported information for clinical decision support at the point of care.
There are significant unmet data needs for a comprehensive accountability system in serious illness care, but these gaps can be prioritized and addressed through alignment and collaboration across stakeholders.
成功实施社区重大疾病照护综合问责制需要有强大的数据基础设施。需要数据来支持护理服务、质量衡量、基于价值的支付以及评估和监测。
需要确定并了解这些领域的具体数据需求，以便解决当前可用数据中的差距。
我们开发了一个框架，其中包括支持重大疾病照护问责制的功能和特点所需的数据和数据基础设施。基于该框架，我们分析了当前的数据情况，以确定现有数据资源和能力中的差距。这项分析是通过进行基于互联网的研究、与关键信息提供者的访谈以及对关键信息提供者的调查得出的。
根据确定的差距，我们提出了一系列优先建议，以推进支持社区重大疾病照护的数据基础设施。这些建议包括增加患者报告结果的测量、增加各种数据源之间的互操作性、增加患者护理计划的开发和交流、利用新标准化的患者功能和认知状态数据以及在护理点使用患者报告信息进行临床决策支持。
重大疾病照护综合问责制存在重大的数据需求未得到满足，但通过利益相关者之间的协调和合作，可以确定并优先解决这些差距。
