A mid-sized ACO REACH entity in the mid-Atlantic region — 4,832 attributed Medicare beneficiaries across 14 primary care practices — engaged Integris Health Data Systems in early 2026 ahead of the ACO LEAD model launch. The organization had been successfully operating under REACH since 2023, but leadership recognized that the infrastructure built for a 4-year model cycle was not designed for a 10-year accountability commitment with monthly attribution reconciliation.
Their data team consisted of two part-time analysts managing CCLF files manually in Excel, a data warehouse that had not been updated since 2024, and a vendor-provided dashboard they could not customize or extend. They had no BCDA API integration, no dbt transformation layer, and no equity reporting capability — despite the LEAD model’s explicit equity reporting mandate.
Integris conducted a structured LEAD Readiness Assessment across six domains using the bcda-client library against the CMS sandbox and a CCLF file sample. The initial score was 38/100 — classified as Critical Gaps.
| Domain | Initial Score | Severity | Key Finding |
|---|---|---|---|
| Data Infrastructure | 20/100 | Critical | No BCDA API connection. CCLF files processed manually in Excel. No automated pipeline. |
| Attribution Accuracy | 35/100 | Critical | 6.2% of roster MBIs absent from BCDA Patient responses — 301 beneficiaries missing from care management programs. |
| Equity Reporting | 10/100 | Critical | No race/ethnicity stratification. No SDOH data. LEAD equity reporting mandate unaddressed. |
| Care Management Data | 30/100 | High | No care gap registry. No ADT feed. TCM workflow not connected to claims data. |
| FHIR Compliance | 60/100 | Moderate | Using BCDA v1 (FHIR STU3). LEAD requires FHIR R4. Migration path straightforward. |
| Analytics Maturity | 25/100 | High | Vendor dashboard not extensible. No gold-layer analytics. No reproducible transformation layer. |
The most operationally significant finding was a persistent attribution gap between the ACO’s CMS-issued roster and the BCDA Patient NDJSON data. Across six months of retrospective analysis, an average of 6.2% of attributed beneficiaries present in CCLF8 were absent from BCDA Patient responses — a documented CMS Beneficiary FHIR Data Server limitation many ACOs do not actively monitor.
Roster-only MBIs declining after reconciliation pipeline deployment
| Metric | Before | After | Status |
|---|---|---|---|
| Attribution match rate (BCDA vs. roster) | 93.8% | 98.2% | Resolved |
| Beneficiaries missing from care management | 301 | 87 | Resolved |
| CCLF processing time | 2–3 days (manual) | <4 hours (automated) | Resolved |
| Open care gaps identified | Unknown | 1,847 (prioritized) | New Capability |
| Equity reporting baseline | None | 6 stratification categories | LEAD Compliant |
| ADT feed integration | None | Scoped, in progress | In Progress |
“The attribution gap alone — 301 beneficiaries we weren’t tracking — justified the entire engagement. Those are real patients who were attributed to us but invisible in our care management system.”
Following the 8-week engagement, the ACO retained Integris on a monthly analytics retainer covering:
A methods paper documenting the BCDA field-mapping gap discovered during this engagement — with longitudinal attribution concordance data — is in preparation for submission to JAMIA or Applied Clinical Informatics in Q3 2026.
Virginia-based health AI research and data infrastructure firm founded by an MD-trained biomedical informatics scientist (PhD, FAMIA) with a decade of national health data program leadership. We build the data infrastructure that ACOs, FQHCs, and health systems need to operate in value-based care — with the domain knowledge to understand what the data means and the engineering execution to make it run reliably.
Our work is open-source first, equity-by-design, and grounded in peer-reviewed research. Every pipeline we build is also a contribution to the published literature on health data infrastructure.
All data in this case study is synthetic and representative of the types of outcomes achievable through Integris’s ACO data infrastructure engagements. No PHI was used. The BCDA field-mapping gap described reflects a documented limitation of the CMS Beneficiary FHIR Data Server acknowledged by CMS. This document illustrates Integris’s service delivery approach and methodology.