Health Centers Struggle to Turn EHR Tools into Social Care Referrals

Community health centers sit on the front lines of American primary care, serving some 52 million low-income people whose chronic diseases are shaped not only by medicine but by whether they can afford food, keep their housing, or get a ride to an appointment. A new formative evaluation published in the Journal of General Internal Medicine examines why the electronic tools designed to help these centers manage such social needs are falling short at the point of care. The study, led by Constance Owens-Jasey of OCHIN, Inc., and colleagues, finds that while screening tools embedded in the electronic health record are relatively mature, the referral and tracking functions that should carry patients from an identified need to an actual service remain fragmented, labor-intensive, and inconsistently used.

The research team interviewed eleven care management staff from four geographically diverse health centers and five subject matter experts in health information technology, all drawn from OCHIN, a nonprofit that hosts a shared instance of the Epic EHR for more than 2,000 community health center clinics across 37 states, the largest such network in the country. In 2022, OCHIN activated Epic’s care management module, called Compass Rose, which is designed to support care coordination activities including the tracking of contextual drivers such as food, housing, and transportation insecurity. Yet at the time of the study, fewer than 10 percent of OCHIN member clinics had ever used the module to make and track referrals for these needs, a striking adoption gap that motivated the investigation.

Methodologically, the study was a formative evaluation informed by human-centered design principles, conducted between September 2023 and July 2024. The researchers used semi-structured interviews paired with a virtual “guided tour” technique, in which participants shared their screens and demonstrated how they actually navigated the EHR to document screening, make referrals, and follow up, using a dummy patient record. Transcripts were analyzed with a rapid qualitative analytic approach organized around the Integrated Technology Implementation Model, and the findings were distilled into a care manager journey map that traces each step of addressing contextual drivers, the tasks involved, and the barriers that surface at each one. Preliminary findings were shared back with participants to verify accuracy.

Step one of the journey, screening, is the system’s relative bright spot. Health centers screen for contextual needs at check-in, rooming, or care management enrollment, and results are captured in EHR flowsheets that support longitudinal tracking. Some centers have configured alerts that prompt any staff member opening a chart to screen, and shortcuts allow quick insertion of relevant text into notes. Once documented, social risk data appear as color-coded icons in the EHR’s patient summary and within the care management module itself, giving care managers a consolidated view. One care manager described the appeal plainly: everything from screenings to disease-specific questions is “all right there,” eliminating the need to hunt across the chart for information relevant to care planning.

Step two, making referrals, is where the machinery begins to grind. For internal referrals to social workers or community health workers, care managers can use EHR messaging and referral ordering. For external referrals to community-based organizations such as food pantries or transportation services, some centers use community resource referral systems like Findhelp or Unite Us, platforms increasingly integrated with EHRs to enable closed-loop communication with registered organizations. But adoption of these platforms is hampered by two major challenges the participants identified: the effort and cost required for both clinics and community organizations to establish the referral model, and the fact that many community-based organizations lack the technological infrastructure to engage in the required data exchange at all. Relationships, participants stressed, matter as much as software; one expert recounted how a center’s referrals went unaccepted because the organizations it wanted to reach had never been onboarded to the platform.

Documentation of referrals proved equally problematic. Most EHR tools as configured at the participating centers offer no discrete field for referral documentation outside a specific referral work queue, and that work queue demands extensive manual entry and is not linked to care management care plans. Within the care management module, care plans include only pre-set, general referral options that must be customized by hand, a task one care manager called a “huge slowdown” that is “very, very time-consuming.” Worse, care plans built inside the module do not propagate to other views of the chart, forcing care managers to re-enter the same information elsewhere so that other care team members can see it. As one staff member explained, the care plan exists only in the module and “doesn’t cross over into any other part” of the record, so visibility elsewhere requires duplicative documentation. The practical result is that much referral information ends up in free-text notes, where it cannot be systematically tracked.

Step three, tracking whether patients actually connected with services, exposes the deepest gaps. Community resource referral systems could in principle close the loop by letting community providers report service receipt back into the EHR, but their limited adoption leaves most centers without that capability. Only referrals routed through the standard EHR referral work queue can be followed longitudinally, and even then, the lack of integration with care management care plans means outcome dispositions must be re-entered in multiple locations. Referrals documented in care plans through free text or shortcuts were not reliably trackable at all. One staff member admitted that after years of doing this work, the center had no formal referral pathway to community partners and could barely “fathom how that would work” given the scale of capturing and closing referrals. Notably, the care management module contains a “tasking” dashboard feature that could support referral tracking, but care managers reported they rarely use it for this purpose simply because they never received adequate training on how.

The study’s authors argue that these barriers can be sorted into three categories: technical, organizational, and those requiring implementation support rather than tool redesign. On the technical side, structured data fields for referrals, care plans customized to each center’s specific programs and reimbursement requirements, and alignment with emerging documentation standards such as those promoted by the Gravity Project could make referral data visible, actionable, and reportable. On the organizational side, the findings highlight a structural tension: health centers are investing heavily in EHR tools and workflows, but the community organizations receiving referrals are often under-resourced to participate in electronic exchange. Without investment in the infrastructure and readiness of those partners, even well-designed platforms will be underused, a problem likely to be most acute in communities with the fewest available services. The authors suggest implementation strategies that include assessing community organization readiness, mapping feasible referral pathways, and building backup workflows when electronic exchange is not possible.

Implementation support emerges as the study’s central prescription. Participants described their training on the care management module as something they “learned as we went,” with comments like “there wasn’t much training available” and wishes for “a much better training program.” Experts confirmed that hands-on, step-by-step guidance with demonstration and practice is the single biggest lever for improving uptake, and that support must be ongoing, since staff reported questions persisting even one or two years after adopting the tools. Leadership backing, workflow redesign coaching, and site-specific configuration assessments before training begins round out the recommended support package. These findings will now feed directly into a cluster-randomized trial, registered on ClinicalTrials.gov, that will test implementation strategies aimed at helping care management teams adopt EHR-based tools for social care coordination, an effort the researchers describe as the first of its kind. The study’s limitations are acknowledged: a small sample, a single EHR system, and the absence of community organization perspectives, though the authors note that Epic’s dominance in health centers and the breadth of roles interviewed strengthen the findings’ relevance.

The broader significance is hard to overstate. Federal and state programs, from Medicare’s Chronic Care Management codes to California’s CalAIM Enhanced Care Management, increasingly require the screening of social needs and linkage to services, and value-based payment models tie reimbursement to that documentation. If the electronic backbone meant to support this work remains siloed and untracked, centers risk both missed interventions for vulnerable patients and unfulfillable reporting obligations. This evaluation offers a precise map of where the technology works, where it breaks, and what a coordinated fix would require: better configuration, shared visibility across teams, genuine two-way infrastructure with community partners, and sustained, hands-on support for the people asked to use it.

Subject of Research: Adoption of electronic health record-based care management technologies for addressing social needs in community health centers

Article Title: Community Health Center Adoption of Enabling Technologies to Address Contextual Drivers of Health for Care-Managed Patients: Formative Evaluation

Article References: Owens-Jasey, C., Gunn, R., Cook, N., Fein, H. L., Pisciotta, M., Fee, C., Larson, Z., Templeton, A., & Gold, R. (2026). Community Health Center Adoption of Enabling Technologies to Address Contextual Drivers of Health for Care-Managed Patients: Formative Evaluation. Journal of General Internal Medicine. https://doi.org/10.1007/s11606-026-10735-6

Image Credits: AI Generated

DOI: 10.1007/s11606-026-10735-6

Keywords: community health centers, electronic health records, care management, social needs, care coordination, health information technology, referrals, implementation science, contextual drivers, social determinants of health, qualitative research, health informatics