Empowering ACOs Through AI Data Acquisition

Accountable Care Organizations (ACOs) are under increasing pressure to improve performance, meet quality benchmarks, and optimize financial outcomes, all while managing data across disparate systems. Too often, the conversation centers on dashboards and reporting tools, yet overlooks a more fundamental capability: data acquisition.

Most organizations prioritize how data is displayed, not how it is ingested. However, performance visibility is meaningless if the underlying data is fragmented, outdated, or incomplete. 

Without the ability to acquire, normalize, and surface meaningful data from across the network in real time, quality measures, care quality, and revenue suffer. Healthcare organizations that rely on value-based care revenue from quality programs often scramble at the end of the year to report sub-optimal quality measures instead of proactively managing data and performance throughout the year.

Productive data acquisition is not just a technical process. It is a strategic function that enables ACOs to drive measurable outcomes at scale. With the right infrastructure, organizations can transform fragmented data streams into unified performance intelligence, gaining the control necessary to lead effectively.

Agentic AI transforms healthcare data acquisition by meeting data where it lives—across FHIR, CDA, QRDA, EHR connectors, APIs, CCLF, claims files, databases, and custom data feeds. The result is broader coverage, higher data fidelity, lower integration costs, and analytics that reflect real-world care delivery.

For organizations pursuing population health, value-based care, and regulatory reporting, agentic AI is not just an optimization; it is becoming essential infrastructure.

The Consequences of Insufficient Data Control

Why is data acquisition hard to get right?Many legacy solutions treat acquisition as a basic technical task, typically a one-time file transfer, without supporting real-time ingestion or ongoing integration. These approaches reduce acquisition to a passive function, creating blind spots, delays, and inefficiencies that undermine performance.

Disconnected EHRs, payer feeds, and ancillary systems produce incomplete records. Manual normalization or inconsistent formats further degrade the reliability of clinical and financial insights. When acquisition is not treated as a core capability, measure performance degrades, care gaps go unnoticed, and teams are left chasing compliance rather than driving improvement.

Mike Deyett states:

"Data acquisition isn’t just about pulling files. It’s about gaining command of your information so you can lead with it."

When acquisition is treated as a passive, technical necessity rather than a strategic capability, the downstream impact is significant. Measure performance degrades, care gaps go unnoticed, and teams are left chasing compliance instead of driving improvement.

From Strategic Acquisition to Actionable Intelligence

ReportingMD is built to solve this problem. It supports strategic acquisition by capturing data continuously across any number of EHRs, claims systems, and real-time feeds such as ADT. This includes structured and unstructured data, which is ingested, validated, and normalized into a clean, actionable patient record.

Acquisition is the starting point. Only after data is acquired can it be aggregated and aligned to regulatory standards like FHIR. ReportingMD transforms raw, fragmented data into unified patient records that support real-time visibility into quality scores, risk adjustment opportunities, and provider-level performance metrics.

Acquisition at this level enables:

• Unique Patient defined

•  Daily measure tracking

• On-demand HCC capture

• Targeted gap closure at the point of care

• Network-wide transparency down to the visit level

Real World Application

A large academic medical center ACO exemplifies what’s possible when data acquisition is treated as a strategic lever rather than a technical hurdle.

Facing the complex challenge of unifying data across 240+ practices, 80+ EHRs, and over 1,500 providers, the ACO needed more than dashboards; they needed a trusted data foundation to support eCQM, Medicare CQM, and CQM reporting and long-term value-based care success.

By partnering with ReportingMD, the ACO achieved full eCQM submission readiness within four months, established a single source of truth across its network, and uncovered care activities previously hidden in fragmented systems. In the past, the large academic medical center ACO achieved high-quality scores through manual chart reviews. One of the most striking outcomes: an increase in the hemoglobin A1c poor control performance rate by 69%, driven by previously missing and fragmented clinical data, not changes in care delivery.  

ReportingMD’s ability to ingest, normalize, and validate massive volumes of heterogeneous data gave the ACO real-time visibility into performance by practice, provider, and patient. The result was measurable improvements in quality scores, stronger confidence in reporting accuracy, and a scalable platform now positioned for CMS digital measure requirements and broader population health analytics.

“We’ve never had that view across all practices and payers and patients… I don’t think we’ve scratched the surface of how much this data set can help us.”

– Dawn Nee, Executive Director, Community Practice Management Services, Tufts Medicine

Digital Measures Are Not Optional

CMS will mandate digital quality measures (dQMs) by 2026. These measures rely on structured, FHIR-based data, a format that most legacy systems cannot support without significant retrofitting. While eCQM submission requires ONC-certified EHR technology like ReportingMD, our analytics platform aggregates and normalizes data from multiple sources and ingestion pathways. This broader data foundation consistently results in higher and more accurate scores than relying solely on an EHR system.

Without modern AI acquisition pipelines, organizations will be forced into costly retrofitting, manual abstraction, or vendor replacement just to meet baseline compliance. 

Delaying investment in acquisition capabilities will create resource-intensive remediation efforts just to meet baseline compliance.

ReportingMD clients are already operating with dQM-ready pipelines. No last-minute conversions. No disruption to workflows. Just scalable infrastructure that meets tomorrow’s requirements today.

Strategic Impact Across the Organization

Effective data acquisition creates measurable value in every part of the network:

• AI Ingestion collects your data where it lives today, not where your EHR company tells you to record it.

• Risk adjustment becomes more accurate with clinical data driving HCC coding.

• Care gap closure is embedded directly into daily workflows.

• Dashboards reflect the real-time state of the network, not outdated snapshots.

• Quality programs gain access to more than 1,600 clinical measures, with real-time feedback to guide improvement.

  
  

This isn’t just visibility, it’s performance control.

Earning Provider Trust Through Usable Data

Clinicians are expected to deliver better outcomes with limited time and increasing pressure. They need data they can trust. Stale, aggregated reports undermine credibility. Timely, measure-level insights, delivered directly within clinical workflows, restore confidence and drive action.

ReportingMD provides exactly that. Whether it’s identifying missed screenings or flagging uncoded chronic conditions, our tools deliver relevant, real-time insights that clinicians use to guide care decisions.

ReportingMD: Infrastructure for Leadership

ACO performance depends on more than reporting; it depends on ownership of data. ReportingMD delivers a unified data acquisition pipeline that supports MIPS, APMs, MVPs, and digital quality measures. Our team provides dedicated advisory support, ensuring organizations stay compliant, competitive, and prepared for what’s next.

Most importantly, ReportingMD gives ACOs the ability to use their data how they need and when they need it. That is the difference between reporting performance and improving it.

This approach is especially relevant for ACOs, CINs, and health systems operating across multiple EHRs, payer feeds, and delegated quality arrangements.

Conclusion

Data acquisition is not a support function. It is a strategic enabler of quality, risk, and financial performance. To scale, you need to consume data assets through agentic AI.  ACOs that invest in the infrastructure to control their data will outperform those that don’t because outcomes start with insight, and insight starts with acquisition.

Explore what full data control looks like.

• Schedule a Data Acquisition Assessment to identify hidden gaps across your network

• See how real-time acquisition changes ACO performance – not just reporting

• Talk to a ReportingMD Advisor about getting dQM-ready

• Request a demo of ReportingMD’s Data Platform and see the impact for yourself

  
  

Book Your Assessment