The 2025–2030 dQM regulatory timeline is already in motion. 2027 will be a critical CMS financial inflection point with expanded eCQM requirements and maximum payment penalties for plans that are not ready. 2030 is NCQA’s deadline for fully digital HEDIS reporting. For mid-size Medicare Advantage plans, the annual payment swing tied to dQM performance can exceed $8 million.
This guide walks through what dQM readiness actually requires, from FHIR data ingestion and CQL measure execution to compliant reporting outputs and provider data access, with a self-assessment checklist you can complete in under 15 minutes. It also breaks down the real cost of building in-house versus connecting to an existing platform, so you can make an informed decision before the window closes.
Table of Contents
- What Are Digital Quality Measures?
- Why It Matters
- The Regulatory Timeline
- Your dQM Readiness Checklist & Diagnostic
- What Happens If You Do Nothing
- What Payers Actually Need
- Build vs. Connect: What This Actually Costs
- The Infrastructure That Closes the Gap
What Are Digital Quality Measures?
Digital quality measures (dQMs) are the next generation of healthcare quality reporting. Traditional quality measurement relied on manual chart reviews, fragmented data abstraction, and submissions that arrived months after care was delivered. dQMs replace that process with standardized, interoperable digital data captured and exchanged in real time.
In practice, it means having FHIR-based data pipelines, Clinical Quality Language (CQL) logic engines, and measure outputs that do not require human abstraction to produce. The results are faster reporting, more complete data, and measure calculations that reflect what is actually happening in current care — not what was documented six months ago.
dQMs are not just a technology upgrade. They are the foundation on which Star Ratings performance, value-based care contracts, and population health management will be built going forward.
Why It Matters
The Compliance Clock is Running
Starting in 2025, a subset of HEDIS measures must be submitted digitally. That number grows every year through 2030, when all HEDIS measures will be fully digital and hybrid measures will be retired. CMS has simultaneously expanded eCQM requirements across Medicare Advantage, MSSP ACOs, Hospital IQR, and MIPS programs.
The Financial Stakes are Real
Plans face an up to 18% payment swing tied to dQM adoption — from minus 9% to plus 9% in Part B payments, with annual swings of up to $16K per provider. Organizations without enterprise-grade interoperability in place by 2027 face maximum penalties, and the decisions made in 2025 and 2026 will have million-dollar implications within two years — in either direction.
The Data Advantage Compounds
Plans building dQM infrastructure now are gaining real-time visibility into measure performance, making proactive care gap closure and earlier intervention possible. That precision compounds over time in Star Ratings, value-based contract performance, and clinical outcomes.
The Competition is Already Moving
The largest health plans in the country are not waiting. Plans that invest now will shape how their provider networks, quality programs, and value-based contracts perform for years. Plans that wait will comply with a standard others have built.
The Regulatory Timeline
Your dQM Readiness Action Plan
Before diving into what needs to be built, it helps to get a clear picture of where your plan stands today. The following checklist walks through the core infrastructure areas that define dQM readiness. Use it to identify what is already in place and where the work still lies ahead.
Step 1: Complete the Checklist
Check every item your plan can confirm today.
Data Infrastructure
- ☐ We ingest clinical data from provider EHRs via FHIR APIs.
- ☐ We normalize data to FHIR R4 across claims, clinical, lab, and pharmacy sources.
- ☐ We maintain a longitudinal health record for each member beyond claims data alone.
- ☐ We have bulk FHIR connections with our highest-volume provider relationships.
Data Quality
- ☐ We have visibility into the quality of our data through PIQI scoring and a performance scorecard.
- ☐ We capture and maintain provenance metadata for all clinical data sources.
- ☐ We are preparing to meet NCQA’s new Primary Source Verification requirements effective 2027.
Measure Execution
- ☐ We run CQL-compliant logic engines that execute measure specifications at scale.
- ☐ Our measure logic updates automatically with annual NCQA and CMS changes.
- ☐ We produce measure results without manual chart review or data abstraction.
- ☐ We can calculate measures at any point in the year, not just at submission time.
Comparative Analysis
- ☐ We have a measure comparative analysis plan and framework in place.
- ☐ We have operationalized data quality refinement to mitigate measure performance concerns.
- ☐ We have validated provenance and primary source verification across data sources.
Reporting and Submission
- ☐ We generate FHIR-formatted MeasureReport outputs.
- ☐ Our submissions are ECDS-compliant and delivery-ready for CMS and NCQA.
- ☐ Our submission infrastructure is certified and audit-ready.
- ☐ We do not manually assemble submissions at the end of each reporting cycle.
Provider Data Access
- ☐ We have active interoperable data-sharing agreements with our provider network.
- ☐ We can query provider systems for clinical data tied to claims in the prior 60 days.
- ☐ We capture specific data elements such as HbA1c values, mammogram completion, blood pressure, BMI, and depression screening results from provider sources.
- ☐ Provider data access gaps are identified and actively being remediated.
Step 2: Review Your Results
Step 3: Understand the Gaps and Cost
For every box left unchecked, here is what it is likely costing your plan:
Can’t ingest standardized clinical data from provider EHRs.
Your measure rates are calculated on administrative data alone. Plans relying on claims-only data systematically underperform peers with access to FHIR-enabled clinical data on key HEDIS measures. On a 50,000-member MA plan, that gap can represent millions in annual Star Rating bonus payments.
Measure execution isn’t CQL compliant.
Your quality team is consuming significant capacity on manual abstraction and chart review that automated engines handle automatically. That is not just an efficiency problem — it is a scalability problem as the digital measure set expands through 2030.
Reporting outputs aren’t ECDS-compliant.
Submission errors are unrecoverable mid-year. A failed or incomplete submission does not get a second chance. Plans that discover formatting or certification gaps at submission time lose points they cannot regain until the following measurement year — a 12-month penalty with no remedy.
No active provider data-sharing agreements.
NCQA identifies this as one of the top three implementation barriers. Plans without clinical data from provider partners systematically miss care gaps that were actually closed — they just were not documented in a format the plan could access. That is not a care problem. It is a data problem with a care gap price tag.
No real-time performance visibility.
You are managing quality retrospectively. By the time year-end data reveals a gap, the window to intervene has closed. Plans with live measure tracking can redirect outreach, adjust provider engagement, and close gaps while there is still time. Plans without it find out what went wrong after it is too late to fix.
The gaps add up. For a mid-size Medicare Advantage plan, each unchecked category above represents meaningful financial risk in payment adjustments, Star Rating performance, and value-based contract outcomes. This diagnostic is not designed to alarm. It is designed to make the cost of inaction specific enough to act on.
What Happens If You Do Nothing
Picture your plan in January 2027.
MSSP ACO reporting now requires nine digital measures with no MIPS CQMs accepted as a substitute. Hospital IQR has expanded to nine mandatory eCQMs. HOS measures carry full 3x weight. CMS has made clear that organizations without enterprise-grade interoperability face maximum payment penalties.
Your quality team is still running manual chart reviews. Your measure calculations are still drawing on administrative data because the clinical pipelines were never built. Your submissions are incomplete, your rates are understated, and your Star Rating reflects a data problem more than a care problem.
Your competitors — the plans that started building in 2025 and 2026 — are submitting clean, complete, automated MeasureReports. Their rates are higher not because their care is better, but because their data is better. They are capturing credit for care that was actually delivered. You are not.
The gap that opens in 2027 does not close quickly. Star Ratings operate on a lag. Value-based contract performance compounds over years. Provider network relationships are influenced by the administrative burden your plan creates. The plans that fall behind in the first fully digital payment year will spend the following two to three years recovering — if they recover at all.
By 2030, when NCQA’s fully digital mandate takes effect, plans without mature infrastructure will have no compliant path to HEDIS reporting. The window to build is now. Time-constrained decisions produce legacy debt. Every workaround built to meet this year’s requirement becomes next year’s retrofit project. Organizations that treat digital quality infrastructure as a strategic architecture decision — not a compliance checkbox — are the ones that will not be rebuilding in 2029 and 2030.
This is not a scenario that requires pessimism to construct. It is the straightforward consequence of the regulatory timeline already in motion.
What Payers Actually Need
Meeting dQM requirements is not a documentation exercise. It requires genuine infrastructure across four areas.
1. Data Ingestion
What it requires: Payers must ingest clinical data from provider EHRs via FHIR APIs and normalize it against the FHIR R4 specification. dQMs draw on EHR encounters, pharmacy records, lab results, device data, and patient-reported health information — not claims data alone.
Why it matters: Plans without richer clinical pipelines will systematically underperform on digital measures. What you get out will only be as good as what you put in. The most precise measure calculation starts with the most complete longitudinal data.
2. Measure Execution
What it requires: Payers need CQL-compliant logic engines that execute measure specifications at scale, stay current with annual NCQA and CMS technical specification updates, and produce results without manual abstraction.
Why it matters: Manual chart review and retrospective data abstraction are not scalable. The volume of measures and the pace of specification changes will overwhelm any team that has not automated. As hybrid measures retire through 2029 and digital measures expand toward 2030, the gap between plans that have automated and those that have not will widen every measurement year.
3. Reporting Outputs
What it requires: Submissions must be in FHIR-formatted MeasureReport outputs ready for delivery to CMS and NCQA via ECDS-compliant reporting channels.
Why it matters: Generating compliant outputs is not just a formatting task. It requires the full data pipeline to be standardized, the measure logic to be current, and the submission infrastructure to be certified. Errors in output format are errors in the submission — and submissions that fail cost plans points they cannot recover mid-year.
4. Provider Data Access
What it requires: Payers must establish interoperable data-sharing agreements with their provider networks and maintain the technical connections to execute them. NCQA has identified data access as one of the top three barriers to successful dQM implementation.
Why it matters: Without clinical data from provider partners, measure calculations will be incomplete. Administrative-only data produces lower rates, missed care gaps, and weaker performance across every program tied to quality — Star Ratings, value-based contracts, and CMS reporting alike.
Build vs. Connect: What This Actually Costs
The decision to build dQM infrastructure in-house versus connecting to an existing platform is not just a technology decision. It is a financial one.
Health plans attempting to internally build FHIR-native dQM infrastructure face significant time and resource commitments, spanning multiple years of engineering work, ongoing maintenance, annual measure specification updates, and the organizational burden of keeping pace with evolving NCQA and CMS requirements. That investment does not include the cost of failed or delayed submissions along the way.
By contrast, plans that connect to an existing CMS-aligned platform typically reach operational readiness in months, with implementation costs at a fraction of the build alternative and without the ongoing burden of keeping pace with annual NCQA and CMS specification changes.
The stakes become more clear when you consider what is at stake financially. A mid-size Medicare Advantage plan with 500 participating providers faces a meaningful performance swing based on dQM results alone. Every month of infrastructure delay is a month closer to the 2027 penalty cliff, with less runway to course-correct.
There is no question whether dQM infrastructure is worth the investment. The real question is whether your plan should build it from scratch or connect to what already exists.
The Infrastructure That Closes the Gap
The essential dQM capabilities reviewed in this document are not theoretical. They describe exactly what b.well’s health.quality platform was built to deliver — a complete, FHIR-native dQM stack that meets every infrastructure requirement without requiring plans to build from scratch.
health.quality is the industry’s most complete dQM and analytics solution, built natively on FHIR and CQL standards. It maps directly to what payers need:
| Infrastructure Requirement | How health.quality Delivers |
|---|---|
| Data Ingestion | Ingests clinical, claims, pharmacy, lab, and consumer data and normalizes everything to FHIR R4, building a complete longitudinal health record for every member. |
| Measure Execution | Advanced CQL engine processes quality logic in real time across the full measure set, updated automatically with every NCQA and CMS specification cycle — no manual rebuilds required. The same CQL clinical reasoning engine also supports downstream CMS mandates including clinical decision support, AI analytics, and prior authorization logic — one engine, multiple use cases. |
| Reporting Outputs | Generates FHIR-formatted MeasureReports and ECDS-compliant submission packages automatically — no manual assembly at the end of each reporting cycle. |
| Provider Data Access | Connects to provider systems via bulk FHIR and standard FHIR APIs, enabling the data-sharing agreements and technical connections that make clinical data accessible at scale. |
health.quality goes beyond these four core requirements:
Automation and Scale
Manual chart review and data abstraction are eliminated. Measure calculation and aggregation happen automatically across systems, freeing your quality team to focus on interventions rather than retrieval.
Near Real-Time Visibility
Performance is accessible at any point in the year, not months after submission. Proactive care gap closure becomes possible when you can see where you stand today.
Regulatory and Future-Ready
health.quality meets current CMS and NCQA dQM mandates and is built to support the digital-first, AI-assisted quality environment emerging through 2030 and beyond.
Data Foundation for What Comes Next
Every measure, every gap, and every intervention runs on b.well’s FHIR-native infrastructure — the same clean, normalized data that supports AI-driven analytics and value-based care programs across the enterprise.
What payers get with health.quality:
- Certified NCQA HEDIS measure library and configurable CMS dQM measure development
- FHIR-based architecture with advanced CQL processing engine and event-based tracking
- HITRUST-certified infrastructure with scalable cloud FHIR and secure API integration
- Progressive quality measure tracking with live data and intelligent data exchange
- Architecture built on FHIR/CQL standards aligned with every upcoming regulatory timeline
- Flexible implementation tiers from basic FHIR integration and analytics dashboards to a full consumer experience platform
The output is a live intelligence layer — MeasureReports, supporting evidence, consumer-facing care needs, next-best actions, and FHIR Task services that turn measure performance into care delivery.
Plans that will be operational by 2030 are making platform decisions now. Implementation timelines are real — a build started today lands after the inflection point, not before it. The organizations that get this infrastructure in place will not just be compliant. They will be ahead: on Star Ratings, on value-based contracts, and on the populations they are actually able to improve. One connection to health.quality delivers the full dQM stack in 3 to 6 months.
Ready to see what health.quality can do for your plan? Connect with our team here.