How'd you fix Cedar's revenue issues in 2026?

What's Actually Broken

1. Uninsured patient volume spike — 40% of patient out-of-pocket dollars now originate from uninsured patients (up 11% YoY), with 10M more losing coverage through 2034. Uninsured = 60-70% lower collection rates vs. insured. Cedar's revenue per patient crashes.

1. Waystar Patientco consolidation gravity — Waystar acquired Patientco ($2B annual payments volume, 30M patient accounts), creating a single RCM mega-stack with claims adjudication + price-transparency + patient payments on one payer graph. Cedar loses distribution leverage with hospital procurement.

1. Difficult-to-collect pool bloat — 77% of patient out-of-pocket dollars fall into hard-to-reach cohorts (uninsured, underinsured, digitally dark, complex bills). Cedar's aging propensity-score logic (built for stable-coverage cohorts) can't segment or suppress low-value accounts.

1. No-Surprises Act (NSA) compliance friction — Good-faith estimate, Advanced Explanation of Benefits, and 90-day provider-directory verification are now table stakes. Cedar's OODA integration doesn't auto-hydrate payer price cards into patient-facing estimates fast enough. Competitors (Phreesia, Athena Patient Pay) ship this faster.

1. OODA payer-channel undercapitalized — $425M acquisition was supposed to unlock payer-side revenue (insurance eligibility, claims prediction, denial mgmt). But payer sales cycles are 18+ months, and existing hospital buyers don't want to add payer dependency. OODA remains a cost center.

1. Staffing & automation gap — 63% of hospitals report billing-staffing shortages. Inbox Health, athenahealth Patient Pay, and Phreesia now offer agentic AI (call deflection, auto-follow-up, eligibility verification). Cedar shipped Agentic AI in April 2025 but lacks industry-specific workflow templates (radiology billing, surgery follow-up). Manual work still bleeds margin.

The 2026 Fix Playbook

1. Propensity-Pay Segmentation Overhaul — Use OODA payer claims data + third-party affordability/income data to build cohort-specific collection strategies. Segment patients into (A) collectible-self-pay, (B) charity-care candidates, (C) skip (too expensive to chase). Drop bottom 10-15% entirely; invest collections spend on A & B. Target: +400bp collection rate lift on difficult-to-collect pool.

1. Payer-Bundled Pricing Layer — Flip the sales motion: pitch Cedar + payer eligibility + claims-paid prediction as a 3-party contract. Partner with 2-3 major regional insurers (Aetna, Humana, United) to co-market step-down patient payments (reduce copay friction if claim-paid probability > 85%). Cedar gets recurring data-licensing revenue from payers; hospitals get higher net patient payments. Target: 5-8 new payer partnerships by Q4 2026.

1. NSA Automation Fast-Track — Bundle OODA payer fee schedules + CMS price transparency data into auto-refreshed good-faith estimates (GFE). Spin up templates by specialty (surgery, radiology, urgent care) with pre-filled cost ranges. Reduce manual estimate-writing from 2 hours → 15 minutes per patient. Sell as "NSA compliance audit + template pack" to hospital CFOs (bonus revenue line).

1. Agentic AI Workflow Library — Expand April 2025 Agentic AI launch with pre-built escalation trees: (A) eligibility verification → payment-plan offer → card-on-file, (B) denial-letter parsing + appeals, (C) post-discharge follow-up sequences by diagnosis (orthopedic surgery = higher patient responsibility). Target: 30% reduction in patient billing calls (benchmark: Phreesia's 88% copay-at-intake vs. Cedar's implied 60-65%).

1. Waystar Competitive Moat — Stop chasing RCM mega-vendors (Waystar, athenahealth). Become the *uninsured/self-pay specialist* instead. Build 1-2 case studies: "Hospital A reduced self-pay collection-time-to-cash by 40% with Cedar propensity-pay targeting." Position as David vs. Waystar Goliath. Sponsor Pavilion Revenue Events with CFO + Controller roundtables on Medicaid mix-shift strategy. Target: 15-20 "self-pay focused" hospital wins (vs. 55+ broad-platform hospitals today).

Table: 2026 Cedar Competitor Playbook

Mermaid: Cedar 2026 Turnaround Loop

Bottom line: Cedar's 2026 revenue fix is a ruthless remodel: pivot from "broad platform" to "uninsured specialist," weaponize OODA payer data for bundled-pricing deals with insurers, automate NSA compliance, and ship industry-specific Agentic AI workflows by Q2. Don't compete on RCM breadth (Waystar already won); own the margin-recovery niche nobody else is chasing.

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Revenue Cycle Orchestration: Turning Denial Data Into Predictable Cash

Cedar’s 2026 revenue issues are amplified by a fragmented denial management loop. Most health systems treat denials as isolated events, reacting after cash is already stuck. The fix requires shifting from denial management to denial *prediction* by layering payer contract intelligence directly onto Cedar’s existing patient payment workflows.

Start by mapping your top 10 commercial payers’ denial patterns over the past 18 months. You’ll likely find that 60-70% of denials stem from just 3-4 recurring reasons—authorization gaps, coding mismatches, or timely filing misses. Cedar’s platform can surface these patterns in near real-time if you configure its analytics to flag claims that deviate from historical payer behavior. For example, if a payer suddenly starts denying a previously accepted CPT code combination, Cedar should trigger an automated pre-claim scrub rather than waiting for the EOB.

The real leverage comes from integrating Cedar with your existing RCM stack (Epic, Cerner, or Meditech) to create a closed-loop feedback system. When a denial hits, Cedar’s patient-facing interface can simultaneously update the patient’s estimated responsibility while your back-end team works the appeal. This prevents the common scenario where a patient receives a bill for a denied service before the system has corrected the error—a major source of patient abrasion and bad debt.

For 2026, target a 15-20% reduction in first-pass denials by implementing automated prior authorization checks within Cedar’s pre-visit workflow. Health systems that have done this report recovering 2-4% of net revenue that was previously written off as contractual adjustments or timely filing misses.

Patient Financial Experience Redesign: Removing Friction From High-Deductible Populations

High-deductible health plan (HDHP) enrollment continues to climb, and Cedar’s revenue recovery depends on how well you serve these patients. The core issue: HDHP patients often delay or avoid care because they don’t understand their financial exposure until after the service is rendered. This creates a self-fulfilling cycle of higher bad debt and lower patient satisfaction.

The fix involves redesigning Cedar’s pre-service financial experience to give HDHP patients actionable cost estimates before they step foot in a clinic. This isn’t about showing a generic “estimated responsibility” number—it’s about integrating real-time eligibility and benefit data with Cedar’s existing price transparency tools. For instance, when a patient schedules a colonoscopy, Cedar should pull their specific deductible remaining, coinsurance percentage, and out-of-pocket maximum, then display a range: “Your cost will be between $450 and $1,200 depending on facility fees and anesthesia.”

More importantly, Cedar should offer structured payment options at this pre-service moment. Currently, many systems wait until after the claim adjudicates to offer payment plans, which is too late. By embedding a “pay now or set up a plan” option during scheduling, you convert uncertain future receivables into confirmed cash. Health systems using this approach report capturing 25-35% of patient responsibility before the date of service, compared to the industry average of 10-15%.

For 2026, target a 30% increase in pre-service collections from HDHP populations by implementing this pre-visit cost transparency workflow. The downstream effect is a measurable reduction in accounts receivable days for self-pay balances and fewer accounts moving to collections.

Payer Contract Optimization Using Cedar’s Data Lake

Cedar sits on a goldmine of payer-specific payment data that most health systems underutilize. Every transaction processed through Cedar contains implicit information about how each payer adjudicates claims, what they reimburse, and where they systematically underpay. In 2026, the revenue fix requires turning this data into ammunition for contract renegotiations.

Start by running a “payer performance scorecard” using Cedar’s historical transaction data. For each of your top 5 commercial payers, calculate:

• Average days to payment (from claim submission to cash)
• Denial rate by service category (e.g., radiology vs. cardiology)
• Percentage of claims paid at or above contracted rates
• Frequency of “downcoding” or payment bundling that reduces reimbursement

You’ll likely discover that one payer is consistently 10-15% below contracted rates on high-volume procedures like MRIs or colonoscopies. This isn’t a coding error—it’s systematic underpayment that Cedar’s data can quantify with precision. Armed with this evidence, your contracting team can demand a rate review or threaten to carve out that service line from the payer’s network.

The second layer involves using Cedar’s data to identify “leaky” payer contracts where your system is leaving money on the table due to outdated fee schedules. For example, if Cedar shows that a payer has been reimbursing you at 2019 rates for a procedure that Medicare increased in 2023, you have a clear case for a retroactive adjustment. Health systems that have done this recovered an average of $0.50-$1.50 per member per month (PMPM) in underpaid claims.

For 2026, target a 3-5% improvement in net payer yield by implementing a quarterly payer performance review using Cedar’s data lake. This isn’t a one-time fix—it’s an ongoing process that compounds as you build a track record of data-driven negotiations.

Sources

• Harvard Business Review — case studies and frameworks on revenue turnaround strategies in healthcare tech
• McKinsey & Company — industry reports on healthcare revenue cycle management and digital transformation
• Gartner — market analysis and vendor assessments for healthcare IT and revenue optimization
• U.S. Centers for Medicare & Medicaid Services (CMS) — official data on reimbursement policies and regulatory changes affecting healthcare revenue
• Deloitte — reports on healthcare financial trends and operational efficiency improvements
• Cedar’s official product website — company-specific solutions, case studies, and revenue cycle management features

FAQ

Does Cedar's revenue problem come from its product? No, the product itself is not the issue. The core problem is margin erosion caused by a shift in patient mix toward more uninsured or hard-to-collect accounts, which drags down overall revenue performance.

How does propensity-pay targeting fix revenue leakage? By using data to identify which patients are most likely to pay, Cedar can focus collection efforts on those cohorts and avoid wasting resources on accounts with near-zero recovery probability. This approach typically improves collection rates by a meaningful double-digit percentage while reducing operational cost.

What is OODA payer data and why does it matter? OODA stands for Observe, Orient, Decide, Act—a framework applied to payer data to rapidly analyze reimbursement patterns and denial reasons. Bundling this data helps Cedar negotiate better step-down rates with enterprise insurance partners by showing exactly where payment gaps occur.

How does owning Waystar's pricing table improve revenue? Waystar is a major revenue cycle platform, and controlling its pricing table means Cedar can set competitive rates for faster collections and compliance automation. This can reduce days in accounts receivable by a significant margin and lower the cost to collect.

Is this fix applicable to other healthcare revenue cycle companies? Yes, the principles of propensity modeling, payer data analysis, and pricing table ownership are transferable to any organization facing margin compression from payer mix shifts. However, the specific execution depends on each company's data infrastructure and partner relationships.

What are the expected results from these changes? Typical outcomes include a 15–30% improvement in net collection rates, a 20–40% reduction in days in accounts receivable, and lower operational costs per claim. Actual results vary based on starting patient mix and payer contract terms.