Exploring the Intersection of Clinical Data, Claims and Social Determinants of Health
At a recent HealthDoers Peer-to-Peer Event, 75+ stakeholders met to discuss promising approaches for combining social determinants of health (SDOH) data with traditional health care data.Kelly Cronin, MPH, director of the Office of Care Transformation at the Office of the National Coordinator for Health Information Technology (ONC) and Niall Brennan, former chief data officer at the Center for Medicare & Medicaid Services (CMS), provided a national-level perspective on the role of SDOH data in health care transformation. These leaders were joined by practitioners from the Center for Improving Value in Health Care and the Cincinnati Children’s Hospital Medical Center, who helped illuminate successful local approaches to integrating multi-sector data for community health.Representatives from the DASH National Program Office attended the meeting and compiled a set of recommendations for organizations interested in supporting data sharing between health care and other sectors. The All In: Data for Community Health network is looking forward to working with HealthDoers to advance this work, which is vital to building a culture of health.
1. Build consensus on how to standardize SDOH measures
To achieve better outcomes at a lower cost, all stakeholders must be clear on what measures matter most. Metrics and indicators that incorporate a broad definition of health equity and SDOH need to be developed along with the clinical quality indicators. As Sanne Magnan, MD, PhD, former president and CEO of the Institute for Clinical Systems Improvement, stated: “We have got to raise the mean and close the gap. We will not achieve the Triple Aim unless we do both.”With the proliferation of SDOH assessment tools for clinical providers on the market, the field of multi-sector data sharing needs guidance, standards, and best practices about how to systematically capture, document, and prioritize the non-health needs of patients. Cronin explained that standardization can help serve both policymakers analyzing data at a population-level and providers in the field coordinating care at the patient-level. Some tools that have emerged for measuring SDOH include:
A report released by the National Academies of Science, Engineering, and Medicine (NASEM) recommends 11 SDOH domains that should be captured in electronic health records (EHRs)
NASEM released a conceptual framework for integrating SDOH into primary care practice
The National Association of Community Health Centers developed the PRAPARE assessment tool to help health centers and other providers collect SDOH data and respond to needs identified
2. Ensure incentives are in place to increase adoption
Standardizing how we measure SDOH is only the first step towards changing the health care landscape. Brennan explained: “You can have all the standards in the world, but if the incentives for adoption are not there, they just sit there.”The ability to act on SDOH in clinical settings has historically been constrained by payment models which incentivize treating disease rather than promoting health. Cronin and Brennan both stressed the need to implement payment and delivery system innovations that can help encourage systematic collection of SDOH data for community health improvement.In recent years, CMS has spearheaded several efforts to transition payments from volume to value-based care, and help providers to thrive in new models, including Accountable Health Communities, the State Innovation Models initiative, and numerous pilot tests supported by the Medicare Access and CHIP Reauthorization Act (MACRA). As a recent ONC blog stated, “Data is the lifeblood of value-based payment environment…That’s why the Department of Health and Human Services (HHS) envisions a future where clinicians in a multi-payer environment obtain actionable, reliable, and comprehensive feedback data regardless of who pays for their patients’ care.”
3. Help care teams use data purposefully in clinical care
Even were it possible or common, simply documenting SDOH in EHRs is not enough. Care teams need to adjust workflows to incorporate SDOH data into their current practice to meet their patients’ health and social needs. Cronin emphasized the importance of making the value case for data sharing to health care providers, demonstrating how SDOH data can make an impact on their existing goals.In fact, Brennan asked: Is the data really stopping you? He agreed that success of CMS’ value-based care initiatives will depend on lessening physician burden and ensuring seamless flow of data and information to providers and insurers. One tool that CMS is re-engineering as a patient-centered data home is Blue Button, a technological platform where Medicare patients can access data and share it back with their providers.
4. Before collecting new data, look at the data that already exists
Brennan’s advice to “start by focusing on the data you have, not the data you want” resonated with HealthDoers participants. Patient-level data collection can require considerable resources, so it’s important to start with a clear purpose for data collection and then search for data already available that can serve your needs.Insurance claims data on race, ethnicity, Medicaid eligibility (proxy for income), and zip code can be leveraged until patient-level data can be easily collected. CMS is working to make their system-level SDOH data free and widely available as possible with products like Medicare public use files and physician utilization files. Sharing visualizations of this data with providers can help them understand their patient panel and generate buy-in to collecting even more useful patient-level information.
5. Learn from community “bright spots” in multi-sector data integration
Meaningful progress towards incorporating SDOH data into health care will likely be accelerated if leaders from provider groups, social and community service organizations, and other stakeholders come together to share their lessons learned, enabling more informed decision-making. Two regional approaches for collecting SDOH data in a clinical setting were featured:
The Center for Improving Value in Health Care is integrating social services and health care data in Colorado through a statewide community resource directory.
Cincinnati Children’s Hospital Medical Center is identifying neighborhoods with poor child health using EHRs and geographic information systems. Overlaying information about housing code violations and other community data has led to a partnership with legal aid groups to ensure clients have access to public benefits and healthier housing.