Health systems seek data to understand where to focus investments in non-clinical supports and services—access to aggregated data from multiple sectors can assist health systems in targeting their efforts. Additionally, the ability to track individual patients across multiple social services areas (e.g., health, housing, employment) is seen as a critical in order to assess the overall needs of a community, identify high-need populations, understand the gaps in capacity, and evaluate the success of joint efforts.  In order to achieve these goals, health systems must overcome barriers including logistical (including having sufficient workforce with necessary expertise), financial, and legal challenges to integrating clinical and non-clinical data.  Integration often requires significant investments in internal health information technology (e.g., electronic health records) as well as linkages across systems (e.g., state or regional health information exchanges). Collaborating partners also must decide which metrics (existing or to be developed) are needed to track and use for evaluation and accountability. The lack of “real time” availability of both clinical and non-clinical information as well as data-sharing privacy and security concerns limit the speed and ease of access for community partners to use multiple data sources to inform patient care and larger system-wide decisions. Other, less tangible, but equally important barriers include the need for a shared vision, commitment to collaboration, and mutual trust in data sharing between health systems and their community partners.

For health systems interested in data integration across sectors, we pose the following questions:

  • Which population-level metrics are most useful to track investments in non-clinical services and supports? Are there certain “core” metrics that can be agreed upon between health systems and community partners?
  • How can health systems leverage electronic health records and other sources of clinical data to both identify complex patients and connect with outside data sources to gain a more complete perspective of overall population health?
  • Is a centralized data warehouse necessary to facilitate multi-sector data integration?
  • Which social services sectors integrate more easily with clinical data, and which ones could use additional attention and technical support to facilitate integration?

Other Organizations Exploring this Element

The data infrastructure foundational element was identified and informed by a multitude of interviews with key informants, thought leaders, health systems, and other community organizations immersed in these discussions. We recognize many other organizations and initiatives are exploring the multitude of issues related to shared data collection, analysis, and evaluation.

  • County Health Rankings & Roadmaps
  • America’s Essential Hospitals
  • Community Health Peer Learning Program
  • Data Across Sectors for Health (DASH)
  • Build Health Challenge
  • Build Healthy Places Network
  • State Health Value Strategies