Data is Alive!
What 68 Post-It Notes tell us about the challenges of sharing data
By Peter Eckart, Co-Director, Data Across Sectors for Health (DASH) at the Illinois Public Health Institute
Representatives from 19 community collaborations funded by the BUILD Health Challenge came together in September to meet each other, share experiences and begin to form the learning collaboration that will sustain their work as they embark on efforts to transform health locally over the next two years.As a co-founder of All In: Data for Community Health, I joined the two-day meeting, along with my fellow co-founder Alison Rein of AcademyHealth, to share the experiences of the existing All In communities and offer insights on the collaborative and technical aspects of sharing multi-sector data. We asked the assembled community representatives to share their answers to this question: what is the first or biggest data sharing issue your collaboration will face? There was no shortage of challenges--we received 98 answers on 68 Post-It Notes.
Not surprisingly, the top issues raised had to do with the technical elements of data: infrastructure, interoperability and how to access and use the data. When collaborations first consider sharing data within a community context, they anticipate these thorny dilemmas:
Connecting data points across systems and parameters so that they (1) make sense and (2) demonstrate new knowledge and insights
Getting all agencies involved to provide or contribute the data
Reconciling variables (timing, source, etc.) to arrive at something actionable
Identifying what data within the vast amount that is collected will be most meaningful
Turning data into information that is usable to effect meaningful change
Accessing data from sources outside our collaborative
All In members are no stranger to these issues, which persist across the variety of use cases addressed by community collaborations. The bad news may be that there is no common roadmap for addressing these widely-experienced challenges; the good news is that the projects within the All In network have dealt with many of these issues before and their solutions and lessons learned are available to communities so that they don’t have to start from scratch.
We regularly highlight these stories on the All In website in resources like the Community Health Peer Learning Program Learning Guide Series on Improved Use of EHRs for Population Health and the Data Across Sectors for Health brief on Coordinated Whole-Person Care that Addresses Social Determinants of Health. All In projects also share insights and lessons on integrating multi-sector data to improve health in our project showcase webinar series (our next webinar is November 9th).
The second set of issues centers on the softer science of conceiving and organizing work and relationships: broadly summarized as partnerships, data collection issues, legal and privacy issues and choosing the right data to collect:
Lack of trust that data can be shared without putting privacy at risk
Equitable partnership and relationship building
Getting all the right data people at the same table
Getting comprehensive data in time to make decisions
Building capacity to collect objective measures (staffing, funding, HIPPA)
Collecting pertinent data across systems and/or sectors that can be tracked at both individual and population-level
Again, All In communities continue to struggle with these same issues. Some of the difficulty reflects the technical issues above, but much of it reflects the challenges inherent to multi-sector collaboration. Many of us know our own organization’s work and data well, but when we step beyond our own experience, we are confronted with different values, different ways of describing and understanding the community, and wholly different ways of measuring and evaluating our impacts.
Fortunately, All In and our network partners are starting to catalogue responses to these challenges as well. Here is where the peer-to-peer networking really yields benefits: time and again, members of the different All In projects tell us now valuable it is to just talk with colleagues who have or are facing similar struggles. The connections are made via webinar, conference calls, in-person and virtual meetings—sometimes facilitated by partner staff with knowledge of a communities that can help each other and sometimes organically as a result of browsing similar projects the All In online community. All In partners are also working with colleagues across the country to understand the solutions that have already been discovered and how we can share the knowledge of those “bright spots.”
All In welcomes our new colleagues at BUILD into the learning collaborative and we look forward to following your amazing work as you make progress towards transforming health in your communities. We’re excited to learn along with you, and to help share your experience with communities across the country. As you embark on this journey, know that there are others out there who have been down the same road and have valuable insights to share. Alison Rein has summarized some of them in part two of this blog series, which shares questions and practical examples for data sharing collaborations just getting started.
Although the field of multi-sector data sharing for community health is relatively new, the knowledge base for this work is growing quickly. All In provides a vehicle to help early innovators galvanize their work as they gain new insights, make meaningful connections, and increase their collective momentum and impact towards improving health equity.
About the Author
Peter Eckart’s career spans over twenty-five years in which he has successfully spearheaded operations and project management in not-for-profit organizations. In addition to his role as Director of Health and Information Technology at the Illinois Public Health Institute (IPHI), he is currently leading the National Program Office at IPHI for a Robert Wood Johnson Foundation initiative, Data Across Sectors for Health (DASH). DASH identifies barriers, opportunities, promising practices and indicators of progress for multi-sector collaborations to connect information systems and share data for community health improvement.