How Health Information Exchanges Can Identify Medically Frail Work Requirement Exemptions

Overview

Recent federal legislation establishes work reporting requirements as a new condition of Medicaid eligibility for adults in states that have expanded Medicaid coverage. Under this law, adults subject to the requirement generally must complete a specified number of hours of qualifying activities such as work, education and community engagement each month to maintain coverage. Recognizing the unique health needs of certain populations, the statute explicitly exempts individuals who are medically frail—defined to include people with serious or complex medical conditions, physical, intellectual or developmental disabilities, substance use disorders and disabling mental disorders. To minimize administrative burden and preserve coverage for eligible individuals, the law directs states to identify medically frail individuals using ex parte processes, leveraging data already available to the Medicaid agency whenever possible rather than requiring additional documentation from beneficiaries.

For states, the challenge is not whether to exempt medically frail individuals but how to identify them accurately and efficiently without creating new administrative barriers or relying on enrollee-initiated information or documentation. While most state Medicaid agencies intend to rely on claims and encounter data housed in their Medicaid Management Information Systems (MMIS), the inherent lag in those systems raises concerns about timeliness in exemption identification. As states prepare to operationalize medical frailty exemptions at scale, health information exchanges (HIEs) present a critical opportunity to supplement traditional Medicaid data sources with more current clinical information.

Reliance on MMIS Claims and Encounter Data—and the Data Lag Problem

Most states intend to begin medical frailty identification by leveraging MMIS claims and encounter data, which contain diagnosis codes, procedure codes, service utilization histories and managed care encounters. These data allow states to create logic-based approaches—such as diagnosis groupings or utilization thresholds—that align with medical frailty criteria.

However, MMIS data are inherently retrospective. There is often a substantial lag between when a service is delivered or a diagnosis is made and when that information is fully processed and visible in MMIS, particularly in managed care environments. This lag can delay identification of medically frail individuals and increase the risk of disenrollment of eligible populations.

The Potential Role of Health Information Exchanges

HIEs have the potential to play a vital and complementary role in any state strategy to identify medically frail individuals for Medicaid work requirement exemptions. HIEs are increasingly not only facilitators of clinical information exchange among health care organizations but also aggregators and analyzers of this data, using it to derive new patient and population insights for exchange participants—including states.  

Clinical data, exchanged via HIEs to support informed clinical care delivery, are timelier than claims and encounter data, which can lag for 90 days or more. They can include information not available through administrative data, including more detailed information on diagnoses and procedures, inpatient admissions and discharges, lab results and pharmacy dispensing information. HIEs may also be able to provide states with clinical histories for Medicaid members who may not have long—or who may have interrupted—coverage histories with the program.

As states develop strategies to identify and exempt medically frail individuals from work reporting requirements, they should look beyond in-house administrative data resources to those stewarded by HIEs.  

Operational and Systems Considerations for Integrating HIEs

States can leverage existing Medicaid Management Information System (MMIS) and information management infrastructure and funding mechanisms to acquire and integrate external HIE data to support the identification of medically frail individuals. Steps that state Medicaid agencies can take include the following:

1. Engage With HIE Data Partners: Explore potential partnerships with state and regional HIEs that have the data access and analytic capabilities to identify Medicaid members who qualify for medical frailty exemptions based on clinical diagnosis and care histories. States will need to work with HIEs to establish data use agreements that describe what information is being requested and for what purpose. Contract specifications may extend beyond technical criteria to support medical frailty identification to include expectations for data transactions (e.g., flat file, API-based exchange), roster linkage, delivery timelines, data quality and data security.
2. Leverage Enhanced Federal Financing for Systems Builds: States can draw down federal matching funds to support necessary information technology (IT) investments for implementing work reporting requirements. States may apply for (FFP) support through planning and implementation Advanced Planning Documents (APDs) for eligible IT and data system investments, including the establishment of new data reporting relationships with HIEs. States may be able to leverage enhanced federal funding for new system designs and installations and maximize cost allocations to serve Medicaid members.     
3. Develop Actionable Technical Criteria: Consult with clinical physical and behavioral health, academic and community-based clinician experts to confirm the appropriate diagnoses and procedure codes that may be used to identify individuals who may meet —and troubleshoot data anomalies that arise. States can build from publicly available technical specifications to support this work.
4. Establish Strong Internal Data Governance: Develop data governance processes to efficiently normalize, clean and integrate new clinical data and information that may be delivered by new HIE partners. Medicaid staff may require training to understand clinical data—or how to apply aggregate indicators—so that it can be appropriately used for analytics and incorporated into medical frailty exemption-algorithms.

HIEs across the country are increasingly establishing relationships with state Medicaid agencies to support population health and operational functions and can be a valuable partner to identify individuals that may qualify for work reporting requirement exemptions. Large system integrator vendors are too; some have even to provide support to states to implement community engagement requirements.

Conclusion

As states implement Medicaid work reporting requirements, accurate identification of medically frail individuals is essential to protecting vulnerable populations and ensuring compliance with federal requirements. Integrating HIEs into Medicaid eligibility operations offers a promising pathway to improve timeliness, accuracy and administrative efficiency while safeguarding continuity of coverage for eligible individuals.

One Big Beautiful Bill Act, Pub. L. No. 119-21, 139 Stat. 72 (2025).

States that do not have access to an HIE may consider leveraging , where available, as a supplemental source to MMIS. APCDs capture claims and related clinical information across multiple payers (e.g., Medicaid, Medicare, and commercial coverage) and can help identify individuals whose coverage or utilization spans payer types. However, because APCD data are claims-based and subject to reporting lags, they generally do not provide the near-real-time data availability that HIEs can offer.