Making Care Primary (MCP) Model. This 10.5-year, multi-payer model, with three tracks, is being tested in eight states slated for July 2024. Participation will come from across healthcare systems in each of the participating states including clinicians, community-based organizations (CBOs), and Medicaid agency payers, with plans to engage private payers soon.The Centers for Medicare & Medicaid Services (CMS) announced a new voluntary primary care model – the
With primary care as the focus, the Making Care Primary model aims to:
- Improve patient outcomes
- Increase access to healthcare
- Reduce costs
The key components to the success of the Making Care Primary model hinges on data, interoperability, integration, and technology. Let’s examine these topics and what health plans can do.
Interoperability vs. Data Integration for the Making Care Primary Model
At first glance, it’s easy to think that interoperability and data integration are interchangeable. However, they are nuanced in their definition.
The 21st Century Cures Act defines interoperability as health information technology that “(A) enables the secure exchange of electronic health information with, and use of electronic health information from, other health information technology without special effort on the part of the user; (B) allows for complete access, exchange, and use of all electronically accessible health information for authorized use under applicable State or Federal law; and (C) does not constitute information blocking as defined in section 3022(a).” Or, more simply put, healthcare organizations can send, receive, find, and integrate data from outside sources.
Some consider data integration the last mile of interoperability. HIMSS defines data integration as the mechanism for transforming and integrating data from multiple sources into a targeted destination environment. It ensures that the data reaches the intended recipient in a usable format.
One can see how both are needed for the Making Care Primary model. As a health plan, it’s imperative you ask others within your organization how they differentiate interoperability and data integration. There will likely be various answers ranging from low levels of integration to higher. To ensure your organizational priorities are successful, confirm early that everyone has the same understanding.
Data Integration to Support the Making Care Primary Model
With the objectives set for the Making Care Primary model participating Medicaid agencies and health plans can prepare by asking the following data-related questions.
- Where are data sources coming from (internal or external)?
- Where is the data stored? And who’s using the data?
- Does the enterprise have the technology and resources to implement things like predictive analytics?
- How will the organization integrate unstructured data (e.g., social determinants of health data)?
Collecting answers to these questions will:
- Break down internal silos
- Gain organizational alignment
- Create a culture of sharing
- Lead to better processes and workflows
Using Natural Language Processing (NLP) to Facilitate Data Integration for the Making Care Primary Model
Integrating external data can be challenging, but incorporating unstructured data like SDoH can pose an even bigger challenge. Executives at NorthShore – Edward-Elmhurst Health use NLP with artificial intelligence and machine learning concepts to extract unstructured SDoH information from patient records and convert it to a structured format.
While still relatively new, initial results are positive with approximately 30% of NorthShore’s population having at least one SDoH factor in unstructured text. NorthShore has also identified 56% more at-risk patients who are experiencing SDoH gaps. This according the the article linked above.
Much Has Been Done
However, there is still much to learn on how to best utilize clinical and SDoH data as it becomes more accessible and secure thanks to interoperability and integration. There are preliminary steps to take within your health plan:
- Agree on where all data resides
- Review resources (people, processes, and software) to identify gaps
- Look at technology like AI and NLP to incorporate unstructured data sets
- Determine if you can handle AI and NLP internally or need to establish a contract with an external vendor
Better patient outcomes, lower costs of care, and optimized encounters are just the tip of the iceberg for the potential that lies ahead as health data becomes fully digitized and compliantly accessible.
Ciox Health utilizes the Datavant Switchboard to supply compliant access to structured and unstructured clinical data electronically. This coupled with Ciox Data Utilities (data supplementation capabilities for SDoH member data) and the NLP AI powered coding engine Cross Check, offer the complete data solution for health plans participating in the Making Primary Care initiative, or planning to participate in the future.