By Chad Tillman, Vice President and General Manager of Release of Information and Care Coordination Solutions at Verisma

May 13, 2026

Clinical teams in practices nationwide work hard to provide excellent, coordinated care daily. And yet, quietly, silently – referrals fall through the cracks. Patients don’t show up. Results never make it back to the ordering provider. Revenue disappears. This isn’t intent failure, it’s infrastructure failure.

Fictional instance, Emily’s story

To see how these issues play out in real life, let’s look at a day-to-day example highlighting the consequences of a broken referral workflow.

Consider Emily, a fictional patient with a very real story.

Emily never made it to her specialist appointment. She left her primary care visit with a referral. However, no one followed up, confirmed scheduling, or tracked the outcome. The specialist never saw Emily, results never came back, and no one in the practice knew. Six months later she showed up in the emergency department with a condition that could’ve been caught early. This isn’t an isolated failure. It’s happening daily inside referral workflows nationwide.

Referral management is one of the most administratively demanding workflows in ambulatory care, and one of the most underestimated sources of clinical and financial risk. When it breaks down, consequences are real: delayed diagnoses, care gaps, reduced quality scores, and significant revenue loss never appearing on a single line in your P&L.

Impact: significant to exponential

Up to one-third of patients never complete specialist referrals, leading to missed diagnoses, delayed treatment, and potential revenue losses nearing $900,000 per physician. For a single physician, the impact is significant. For a 10-provider practice it’s exponential, with up to $9 million in downstream revenue at risk annually, and:

• Missed downstream services and procedures
• Gaps in care impacting quality scores
• Lost performance incentives in value-based care models
• Increased patient referral gaps to competing systems
• Potential malpractice exposure tied to missed follow-up

Referral breakdowns delay care and erode the entire economic model of the practice.

Why referral management is so hard to get right

The referral workflow touches nearly every part of your practice. It’s a chain of handoffs, each of which must be executed correctly for the referral to reach a successful conclusion.

Consider what your team must do for a single outgoing referral: verify the patient’s insurance, identify an in-network specialist, obtain authorization, prepare and send the referral packet, coordinate scheduling with the patient and the specialist, then follow up until results are returned to the ordering provider. That’s before accounting for urgent referrals, authorization denials, patients who can’t be reached, and specialists who don’t return consult notes.

A referral is nine coordinated actions across staff, systems, and external providers:

 

1. Insurance verification
2. In-network specialist identification
3. Prior authorization
4. Clinical documentation assembly
5. Referral transmission
6. Patient scheduling
7. Appointment completion
8. Consult note retrieval
9. Provider follow-up

Where the process typically breaks down

• Patient follow-through: Even when a referral is sent correctly, patients may not schedule or attend the appointment, often because no one is following up to make sure they do.
• Administrative overload: Staff responsible for referrals are often also handling scheduling, phones and billing – making it nearly impossible to track dozens of open referrals simultaneously.
• Results never arriving: Half of referring physicians report they don’t know if the patient saw the specialist, much less received the consult notes they need to update the care plan.
• Inconsistent processes: Without a standardized workflow, referrals are handled differently by different staff members – creating unpredictability, errors, and compliance risk.
• Lack of visibility: Most practices can’t tell you, at any given moment, how many referrals are open, which are aging, or what percentage were never completed.

If you can’t see your referral pipeline, you can’t manage it. And if you can’t manage it – you’re losing patients, outcomes and revenue daily.

What “closing the loop” means

The phrase is used often in healthcare but rarely put into practice. A closed-loop referral system means every incoming or outgoing referral is initiated, tracked, completed and confirmed. The ordering provider receives the consult result. The patient was seen. The record is updated.

This isn’t aspirational. It’s achievable. However, it requires the right combination of standardized process, dedicated resources, and real-time visibility most practices don’t have in place today.

Before vs. after: what changes when referrals are managed intentionally

After implementing a managed approach, every referral is tracked in real time, with dedicated ownership and accountability. Patient and specialist follow-up becomes proactive, and workflows are standardized throughout the organization. Referral completion rates are measurable, enabling continuous improvement and greater transparency.

How Verisma Closes the Loop

Verisma operates directly within your existing electronic health record (EHR), no new platform or disruption. We bring tech-enabled structure, visibility and accountability to every step:

1. Receive and triage: We receive the referral or order from the provider, identify the payer type, and determine the appropriate specialist based on network, availability, and patient proximity.
2. Gather, authorize and send: Our team pulls necessary clinical information from the chart, obtains authorization, prepares the referral packet, and sends it to the specialist – standard referrals within five business days, urgent within one.
3. Coordinate with the patient: We notify the patient and assist with scheduling, working within whatever protocol your practice prefers – from full scheduling coordination to readiness-only support.
4. Track and follow up: We monitor every open referral and follow-up proactively on pending appointments, missed visits, and aging consults so nothing falls through the cracks.
5. Retrieve and route results: After the appointment, we obtain consult notes via health information exchange (HIE) access, fax or phone – and route promptly to the ordering provider so care plans can be updated without delay.

This isn’t about outsourcing, it’s about gaining control. The most common concern we hear is, “Referral management is too important to hand off.” We agree, and that’s exactly the point. The goal isn’t to give up control. It’s to finally have it. With Verisma:

• You maintain full oversight
• We operate inside your systems
• You gain visibility you likely don’t have today
• Your staff is freed to focus on patient-facing and clinical work

Most organizations are live within four-six weeks, and the most consistent outcome is clarity, control and capacity.

Who benefits most, and why it matters now

Referral management challenges are most acute in ambulatory care settings: primary care practices, specialty clinics, federally qualified health centers (FQHC), and multi-site physician groups. These organizations carry high referral volumes with limited dedicated staff and face the most direct consequences when referrals are incomplete or results go missing.

For FQHCs and community health centers (CHC), referral completion rates are tied to Health Resources & Services Administration (HRSA) reporting and organizational funding. For value-based care (VBC) models, they connect to quality scores and payer performance metrics affecting revenue across the patient panel.

The question is no longer whether referral management matters to organizational performance because it does. The question is how your practice is managing it today, and whether you’re absorbing costs and risks you don’t need to. When referral management is done well, it increases care completion rates, improves patient satisfaction, boosts quality scores, and safeguards revenue.

3 simple questions to ask yourself today

Ask yourself:

1. Do you know how many referrals are currently open?
2. Can you identify which referrals are more than 10 days old?
3. Are you aware of your referral completion rate?

If the answer to any of these questions is no, you’re not alone – but you’re likely absorbing unnecessary costs and risks.

When referral management works, everything improves. Care is delivered faster, patients stay within your network, providers have complete information, quality scores improve, and revenue is protected. Referral management isn’t just an operational function. It’s financial and clinical control point hiding in plain sight.

What’s inside your referral workflow?

Most organizations don’t know where their referrals break down. Let’s find out and show you how to fix it. Connect with a Verisma care coordination specialist today.

By Jeannie Hennum, General Manager of Value-Based Care at Verisma

May 7, 2026

Healthcare is in the middle of a seismic shift. The old fee-for-service model – where providers are paid for every test, visit and procedure – is giving way to something more intentional: value-based care (VBC). While much of the conversation around VBC focuses on clinical outcomes and payment models, there’s a critical operational challenge that doesn’t get enough attention: how we retrieve and manage medical records.

Getting the right chart, from the right place, at the right time isn’t just an administrative task – it’s mission-critical for the financial health and clinical accuracy of every organization operating under a value-based model.

VBC record retrieval is a revenue integrity and risk-control function. Strong retrieval and documentation support can:

• Protect risk-adjusted payments tied to risk adjustment factor (RAF)/hierarchical condition categories (HCC) capture
• Improve quality program payouts by ensuring evidence is found and submitted on time
• Reduce recoupment and audit exposure from unsupported diagnoses or missing information

Put simply: better records = fewer dollars left on the table and fewer dollars clawed back.

What Is VBC, Really?

At its core, VBC is the evolution of how care is delivered and who takes on the risk. It’s a move away from treating conditions in isolation and toward whole-person health. Instead of standardized care plans, the goal is personalized prevention. Instead of volume, the focus is on quality – ensuring services lead to positive health outcomes, improved patient experience, and reduced costs.

Chief financial officers (CFO) can evaluate every VBC program by focusing on these variables:

• Revenue (risk-adjusted payments, shared savings, incentives)
• Cost (labor and vendor cost to retrieve/validate charts)
• Risk (recoupments, audit failures, penalties)
• Cash (how fast you can close the loop before submission deadlines)

Record retrieval touches all four.

Under VBC, providers are rewarded through incentive-based programs for meeting specific quality measures. That means reduced readmissions, better care transitions, and higher patient satisfaction aren’t just nice-to-haves – they translate into performance dollars (bonuses, shared savings, and risk-adjusted payments) only if the supporting documentation is retrieved, validated and submitted on time.

ACO LEAD: The Next Chapter in VBC

While accountable care organization (ACO) realizing equity, access, and community health (REACH) has been a proving ground for provider organizations with VBC expertise, the Centers for Medicare & Medicaid Services (CMS) is looking ahead. The long-term enhanced ACO design (LEAD) model is set to launch January 1, 2027, and represents a significant evolution in how ACOs will operate over the next decade.

What Makes LEAD Different?

ACO LEAD is designed as a 10-year model from 2027–2036, a sharp departure from the shorter program cycles characterizing previous CMS initiatives. That long horizon isn’t just symbolic, it’s structural. Here’s what sets it apart:

• Fixed 10-year benchmark with no rebasing. One of the biggest pain points in existing models is benchmark volatility. When benchmarks reset, organizations that have driven down costs can be penalized for their own success. LEAD eliminates that problem by locking in benchmarks for the full model term, giving ACOs predictability and long-term financial clarity.
• Lower participant alignment minimums. REACH required a scale many smaller and rural practices couldn’t meet. LEAD lowers the bar, making the model accessible to a broader range of provider organizations – including those in underserved and rural populations standing to benefit most from coordinated VBC.
• CMS-administered specialty risk arrangements (CARA). Under REACH, managing specialty care coordination was a significant burden on participating ACOs. LEAD introduces CARA, where CMS takes on the administration of specialty risk arrangements, easing the operational complexity for participants and allowing them to focus on primary care coordination and quality improvement.

Why LEAD Matters for Chart Retrieval

For organizations involved in medical record retrieval and risk adjustment, LEAD’s 10-year stability changes the calculus. With fixed benchmarks, the accuracy and completeness of documentation become even more critical financially. Every RAF score, care gap closure, and quality measure submission compounds over a much longer timeline – meaning small misses can become recurring revenue leakage, and small improvements can create recurring upside.

Organizations investing in scalable, accurate retrieval infrastructure are positioned to protect risk-adjusted revenue (PMPM), strengthen quality program performance dollars, and reduce avoidable recoupment exposure across the full decade of the model. Those treating retrieval as a short-term compliance exercise may find themselves locked into a 10-year program without the operational foundation to sustain financial performance.

Preparing for 2027

The January 2027 launch may feel distant, but the contracting, technology deployment, and workflow redesign required to participate effectively take time. Organizations considering LEAD should be asking themselves:

• Is our record retrieval centralized and scalable enough to support a 10-year commitment?
• Do we have the provider relationships and re-engagement processes to ensure documentation completeness?
• Are we shifting toward prospective retrieval strategies aligning with how LEAD will measure and reward performance?
• Do we know our current cost-to-collect a compliant chart (internal labor + vendor fees), and have we modeled the ROI of improving retrieval speed and completeness against expected incentive revenue and avoided recoupments?

The transition from REACH to LEAD isn’t just a program change. It’s a signal CMS is betting on long-term, stable partnerships with provider organizations. The organizations preparing early will be the ones best positioned to thrive.

ACO REACH vs. ACO LEAD

Key Comparison Takeaways

• Stability vs. agility: REACH rewards organizations performing in shorter cycles. LEAD rewards sustaining performance over a decade, a fundamentally different operational challenge.
• Accessibility is expanding: By lowering alignment minimums, LEAD opens the door to community health centers, rural practices, and smaller provider groups effectively excluded from REACH.
• Administrative burden is shifting: With CMS taking on specialty risk arrangements through CARA, participating ACOs can redirect resources from coordination overhead toward quality improvement and documentation accuracy.
• Retrieval stakes are higher: A fixed 10-year benchmark means early documentation gaps echo across the model term. Organizations need retrieval processes that are accurate and continuously improving.

Why RAF Scores and Care Gaps Matter

RAF scores are the engine behind VBC payment accuracy. Here’s how they work:

• Diagnoses (ICD codes), along with demographic and enrollment data, feed into HCCs.
• Conditions are grouped by cost severity, and hierarchical logic ensures the most severe condition is counted.
• Each HCC carries a relative risk weight, and the final RAF score combines demographic factors with those weights.

If the documentation supporting those diagnoses is incomplete, inaccurate or missing, the RAF score doesn’t reflect reality – or the payments. In simple terms, risk adjustment is a math problem: base rate × RAF. When RAF is understated, revenue is understated; when diagnoses are unsupported, the organization is exposed to audits and repayment. Care gaps go unidentified. Quality measures like MIPS and HEDIS fall short. The downstream effects ripple through the entire care model.

One useful way to size the opportunity is to model RAF sensitivity: even a 0.01 shift in average RAF, multiplied across thousands of covered lives, can become material annual revenue – especially in capitated arrangements.

Finding the Right Data: Retrospective, Prospective and Concurrent

Record retrieval in VBC isn’t one-size-fits-all. Organizations need to understand three distinct approaches:

• Retrospective Risk Adjustment: looks backward at diagnoses and costs from the same period. Often identifies missed capture too late to influence current-year cash flow and can increase fire-drill labor cost near deadlines.
• Prospective Risk Adjustment: uses past data to predict future costs (e.g., a 2025 diabetes diagnosis increases the 2026 payment rate). Protects next-year PMPM by ensuring complete, compliant diagnosis support is retrieved and submitted within the measurement window.
• Concurrent Risk Adjustment: uses current-year diagnoses to adjust current-year payments real-time (e.g., a new cancer diagnosis in March raises the risk score for that same year). Speeds cash realization but raises the bar on operational cycle time, retrieval delays can directly delay or reduce payment.

A shift toward prospective record requests is already happening. Organizations relying solely on retrospective retrieval are leaving money, and clinical accuracy, on the table.

Becoming a Forensic Medical Record Retrieval Expert

Medical charts live in a surprising number of places: archival storage, filing cabinets, multiple electronic medical record (EMR) systems, third-party platforms, and more. The distribution methods are equally varied – health information exchanges (HIE), portals, email, fax, mail, and on-site retrieval play a role.

Effective retrieval requires understanding:

• Where records are stored and how to access them across fragmented systems
• Plan, provider, and third-party relationships affecting availability
• Privacy and security requirements, including minimum necessary standards and patient self-pay protections
• Recoupment risk and the resources needed to manage it

Data fragmentation is real, and it’s one of the biggest obstacles to accurate VBC reporting.

Strategic Best Practices

So how do organizations get ahead of these challenges? A few key strategies:

• Centralize record storage and retrieval: to enable timely, complete submissions.
• Consider outsourcing, but plan: Contracting takes time, and policies may require a request for proposal (RFP) process.
• Embrace workflow automation but be realistic about deployment timelines: New technology is powerful, but it can take time.
• Don’t forget vendor management: Even the best tools and partners need collaboration.

Watch out for Pitfalls

Even with strong processes in place, retrieval comes with inherent financial risks: incomplete charts (lost measure credit and revenue), misplaced pages and missing signatures (denials), PHI mishandling (incident cost), excessive retrieval fees (higher cost-to-collect), purged records (permanent revenue leakage), and provider hardships delaying turnaround time.

Validation is essential. Provider re-engagement is critical when records come back incomplete. Share the “why” with your teams and partners. Missing information can lead to unsupported diagnoses, inaccurate coding, audits, and recoupments – real dollars, not abstractions. Time is of the essence, and collaboration makes the difference.

Leverage AI and QA

Integrating artificial intelligence (AI) into record retrieval and chart validation accelerates processes, flags inconsistencies, and streamlines data management. Maintaining a human-in-the-loop is essential for ensuring nuanced quality assurance (QA), especially when reviewing complex medical documentation or resolving ambiguous cases. Combining AI-powered automation with experienced human oversight creates a robust, reliable workflow maximizing efficiency and safeguarding accuracy.

Prioritize Archival for Compliance and Continuity

Establishing a secure, organized archival system for medical records is crucial. Proper archival supports audit readiness and regulatory compliance and preserves historical data for future analysis and ongoing patient care. Pairing advanced archival tools with thoughtful procedures, ensures records are accessible, protected and available when needed most.

The Bottom Line

VBC continues to evolve, and with it, the demands on how we collect, manage and use medical records. The organizations thriving will be those treating chart retrieval not as a back-office function, but as a CFO-visible lever for revenue (risk adjustment and incentives), cost (lower cost-to-collect), risk (fewer recoupments and audit findings), and cash (faster submission cycles).

The shift from retrospective to prospective record retrieval is happening now. Continuity of care through referrals and provider-based retrieval is expected to grow. And record retrieval? It’s not as easy as you might think. But this mission-critical capability is one of the clearest ways to reduce revenue leakage, strengthen quality payouts, and avoidable clawbacks – one record at a time.

Ready to strengthen your VBC performance? Contact Verisma to learn how our solutions improve record retrieval, support accurate coding, and drive aligned incentives for better outcomes. Let’s discuss your goals and how we can help, today.

By Elizabeth McElhiney, Director of Government Affairs and Policy at Verisma

April 30, 2026

If you work in healthcare, you’ve heard the word “AI” more times in the past two years than in the previous decade combined. But behind the buzz, something substantive is happening. Federal regulators are rewriting the rules for health IT, and major healthcare organizations are issuing guidance to help institutions navigate the shift. For health information (HI) professionals, now’s the time to cut through the noise and understand what’s changing – and what it means for your organization.

Two developments deserve your full attention: the proposed HTI-5 rule from the Office of the National Coordinator for Health IT (ONC), and recent guidance from the American Hospital Association (AHA) on responsible AI adoption. Together, they paint a clear picture of where health IT is heading – and what leaders need to do to stay ahead.

Not All AI Is the Same: A Plain-Language Guide

Before diving into regulation, it helps to understand what we’re talking about when we say “AI.” The term gets applied to everything from simple automated workflows to genuinely sophisticated machine learning systems. Here’s a practical breakdown:

• Machine Learning (ML): Algorithms learning from large datasets to identify patterns and make predictions. In health IT, ML powers case prioritization in clinical documentation integrity (CDI), predictive analytics in revenue cycle management, and security anomaly detection. Example: a system flagging high-risk records for review based on historical billing patterns.
• Natural Language Processing (NLP): A subset of ML enabling computers to read and interpret human language. In practice, NLP drives coding assistance tools parsing clinical notes and suggesting diagnosis codes – reducing manual effort and error.
• Robotic Process Automation (RPA): Often mistaken for AI, RPA is rule-based automation – software following fixed instructions to complete repetitive tasks like data entry or form routing. It doesn’t learn or adapt, but it does save significant staff time.
• Generative AI: The newest category to enter mainstream healthcare. These models can draft clinical summaries, respond to patient inquiries, or generate documentation. They carry significant promise, and substantial governance responsibility.

Understanding these distinctions matters because the regulatory and ethical obligations differ across each type. A rules-based RPA tool carries very different risks than a generative AI model influencing a clinical recommendation.

HTI-5: Less Prescription, More Responsibility

The proposed HTI-5 rule represents one of the most significant updates to the ONC Health IT Certification Program in years. Its intent is largely deregulatory: reduce certification burden, modernize interoperability standards, and streamline the path for health IT developers to bring innovative tools to market.

For healthcare organizations, that sounds like welcome news – and in many ways it is. But here’s the catch: fewer federal certification requirements don’t mean less risks. When the regulatory floor lowers, responsibility shifts to organizations themselves. Under HTI-5, your team will need to independently evaluate AI tools for safety and potential bias, ensure algorithms are explainable and auditable, and maintain strong internal governance over any AI or automated system in use.

Information blocking compliance is particularly urgent. AI systems can inadvertently create violations. For instance, if an automated workflow restricts access to electronic health information (EHI) in unintended ways. Enforcement is active and penalties are real. Leaders must ask vendors tough questions: Does your AI learn from our patient data? How is access to EHI logged and audited? Who governs how our data is used? Transparency isn’t optional, it’s a compliance requirement.

AHA Guidance: Governance Isn’t Optional

The AHA has been clear and consistent: responsible AI adoption is a governance challenge, not just a technology challenge. Hospitals and health systems are urged to ensure any AI deployment is strategically aligned with organizational goals, ethically evaluated with bias assessments conducted locally rather than relying solely on vendor testing, validated in the specific deployment environment, and continuously monitored after go-live.

The AHA’s emphasis on keeping humans-in-the-loop is especially important for HI professionals. When AI influences decisions about clinical documentation, revenue cycle, or patient access to records, human oversight isn’t just best practice, it’s an ethical and increasingly a legal requirement. Responsible AI isn’t a one-time project. It’s an ongoing governance model.

What HI Leaders Should Do Now

The convergence of HTI-5 and AHA guidance points to a clear action agenda:

1. Develop a clear AI strategy. Know what tools you have, how they work, and what decisions they influence.
2. Ask vendors better questions. Go beyond marketing claims. Demand transparency on data governance, model explainability, and audit trails.
3. Build multidisciplinary governance. AI oversight should include HI professionals, clinicians, IT, compliance and legal – not a single team working in isolation.
4. Embed information blocking compliance. Audit automated workflows ensuring no AI-driven process unintentionally restricts patient access to EHI.
5. Stay curious. Terminology and capabilities will keep evolving. Leaders committed to ongoing learning will be best positioned to guide their organizations.

The Bottom Line

The future of health information management isn’t about choosing between humans and machines. It’s about combining human judgment with machine efficiency – responsibly, transparently, and always in service of patients.

HTI-5 and AHA guidance aren’t obstacles to innovation. They’re a framework for doing it right. AI is already embedded in the tools we use every day. The only real question is whether we deploy it intentionally or let it shape us by default.