Change is coming, yet again, to hospitals in the US. Starting next year, any hospitals that accept Medicare payments will be required to screen all adult patients for social determinants of health (SDOH) – not just those on Medicare.
However, doing so will be tricky as IMO Health’s Director of Government and Standards, Ann D. Phillips, describes in our new white paper. From unpacking policy, to examining the challenges of screening itself, to how natural language processing (NLP) could help maximize this data, she explains why SDOH data quality should be on your organization’s radar.
Keep scrolling for an excerpt from the paper on how CMS is approaching and addressing health disparities. There’s also an example of why it’s important to gather granular information about factors like homelessness to help provide more effective interventions.
Or, if you’re ready for the full white paper, click the button below.
WHITE PAPER
Realizing the potential of SDOH data: A look at policy, screening, and the role of NLP
Advancing policy for SDOH
The Centers for Medicare & Medicaid Services (CMS) has long recognized the connection between health disparities and healthcare spending, which is the focus of work by the CMS Office of Minority Health (OMH). The OMH published the 2015 CMS Equity Plan for Improving Quality in Medicare with specific recommendations to advance health equity by improving the quality of care for minority and other underserved Medicare beneficiaries. CMS officially adopted this plan as an agency-wide initiative in 2021, and the current version of the CMS Framework for Health Equity 2022–2032 was released in April 2023.
In the plan, CMS identifies five priority areas critical to achieving health equity. Each area identifies activities for an integrated approach to address health disparities throughout CMS programs. Collaboration with the Office of the National Coordinator for Health Information Technology (ONC) ensures the interoperability of SDOH data and alignment with the standards defined in the United States Core Data for Interoperability (USCDI).
While CMS is active in executing all five areas of the framework, with components of Priorities 2 through 5 represented in recent Medicare payment policy, Priority 1: to Expand the Collection, Reporting, and Analysis of Standardized Data is crucial.
More granular and specific data is needed to better understand the scope of SDOH, inform the five health-related social needs (HRSNs), and develop effective interventions. The homelessness example below provides a useful illustration.
Use case: SDOH and homelessness
JOIN, a Portland, Oregon nonprofit serving the needs of the homeless, identifies four general categories of homelessness: chronic, episodic, transitional, and hidden. Each of these categories consists of subcategories that require different solutions to address homelessness. Screening for SDOH that support differentiation is essential when analyzing the data in order to drive effective interventions. Afterall, the needs for an individual experiencing chronic homelessness with drug dependency may differ from those experiencing transitional homelessness due to a lack of affordable housing.
Quality data is key to informing Priority 1, since data for social risk factors, experience of care, and comprehensive patient demographic data – including race, ethnicity, language, gender identity, sex, sexual orientation, and disability status – drives all other activities in the framework. CMS quality programs reflect the incorporation of Priority 1 in Medicare payment policy by associating the collection of SDOH data with quality measurement.
It is worth noting that linking payment to reporting quality measures for SDOH screening signals a shift in Medicare policy that continues to reverberate throughout healthcare. The National Committee for Quality Assurance (NCQA) has implemented SDOH screening measures as part of the Healthcare Effectiveness Data and Information Set (HEDIS) for commercial health plans including Medicare Advantage, Managed Medicaid, and plans sold on the exchanges.
