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

📖 2,158 words🗓️ Published Oct 30, 2026

Direct Answer

Fixing Cedar's 2026 revenue issues means pivoting from broad RCM platform to self-pay specialist: overhaul propensity-pay segmentation to drop uncollectible cohorts, bundle OODA payer data into co-marketed step-down payment deals with regional insurers, automate No-Surprises Act estimates, and ship specialty-specific agentic AI workflows. Target 400bp collection lift, 5-8 payer partnerships, and 15-20 focused hospital wins.

The two options compared: platform breadth versus self-pay depth

Cedar faces a genuine strategic fork in 2026, and the choice drives every downstream decision about product, sales, and capital allocation. The first option is to keep chasing platform breadth — matching Waystar after its Patientco acquisition, athenahealth Patient Pay, and Phreesia feature-for-feature across eligibility, claims, price transparency, and patient payments. The appeal is obvious: hospital procurement teams prefer consolidated vendors, and a broader stack theoretically raises average contract value. The problem is that Cedar would be fighting a well-capitalized incumbent on its home turf, where Waystar already processes enormous claims volume and bundles payer pricing directly into patient payment flows. Cedar's revenue would stay exposed to procurement gravity, and every renewal becomes a price negotiation against a mega-stack.

The second option is to go deep on self-pay and the difficult-to-collect pool — uninsured, underinsured, digitally dark, and complex-bill patients. This is where the margin actually bleeds: a large share of patient out-of-pocket dollars now sits in cohorts with dramatically lower collection rates than insured, stable-coverage populations. Cedar's existing propensity logic was built for stable-coverage cohorts and cannot reliably segment or suppress low-value accounts, so collections spend gets spread across accounts with near-zero recovery probability. Going deep means rebuilding segmentation, suppressing the bottom 10-15% of accounts entirely, and reinvesting that spend into collectible-self-pay and charity-care candidates. The trade-off is narrower total addressable market and a smaller average deal — but higher win rates, stickier deployments, and a defensible niche that Waystar and Phreesia are not optimized to serve.

How'd you fix Cedar's revenue issues in 2026 — figure 1

The comparison matters because the two options imply opposite sales motions. Breadth requires enterprise RCM selling against incumbents with 18-month cycles and heavy proof-of-concept demands. Depth requires CFO and controller-level selling on margin recovery, faster pilots, and case-study-driven expansion. For a company with a $425M acquisition (OODA) still functioning as a cost center, the depth path converts existing assets into revenue faster. The breadth path requires new capital and a multi-year feature race. In practice the winning answer is a sequenced hybrid: lead with depth to stabilize revenue and generate referenceable wins, then selectively broaden once payer partnerships and agentic automation create pull. But the primary identity for 2026 should be self-pay specialist, not RCM generalist.

How to decide between them

The decision framework hinges on three measurable inputs: current win rate against Waystar and athenahealth, collection-rate performance on the difficult-to-collect pool versus insured cohorts, and payer partnership pipeline velocity. If win rates against mega-vendors are declining while difficult-to-collect collection rates lag insured rates by 60-70%, depth wins decisively. If payer sales cycles are stretching past 18 months with no signed deals, the OODA bundling thesis needs a co-marketing partner rather than direct payer sales.

The diagram makes the sequencing explicit: depth decisions feed directly into segmentation, payer bundling, and compliance automation workstreams, all converging on a focused hospital win target. Breadth decisions, by contrast, funnel into feature parity investment and enterprise selling with structurally higher customer acquisition cost and longer cycles. A RevOps leader evaluating this should score each branch against cash-conversion timeline — depth workstreams can show collection-rate movement within two quarters, while breadth investments typically take four or more quarters to influence win rates.

Concrete numbers behind each option

How'd you fix Cedar's revenue issues in 2026 — figure 2

The depth path has quantifiable targets. On segmentation, suppressing the bottom 10-15% of accounts and concentrating collections spend on collectible-self-pay and charity-care cohorts targets a 400 basis point collection-rate lift on the difficult-to-collect pool. On payer bundling, co-marketing step-down patient payment programs with 2-3 major regional insurers — where copay friction drops when claim-paid probability exceeds roughly 85% — targets 5-8 new payer partnerships by Q4 2026, each generating recurring data-licensing revenue. On compliance automation, auto-refreshed good-faith estimates built from OODA payer fee schedules plus CMS price transparency data cut manual estimate-writing from about 2 hours to roughly 15 minutes per patient. On agentic AI, expanding the April 2025 launch with pre-built escalation trees targets a 30% reduction in patient billing calls, benchmarked against Phreesia's reported 88% copay-at-intake capture versus Cedar's implied 60-65%.

The breadth path's numbers are less favorable. Matching Waystar's consolidated claims-plus-pricing-plus-payments stack requires multi-quarter engineering investment with no guaranteed differentiation, since the incumbent already holds distribution through hospital procurement. Enterprise RCM sales cycles commonly run 12-18 months, and proof-of-concept demands consume solutions engineering capacity. Payer sales cycles for OODA's payer-side revenue — eligibility, claims prediction, denial management — run 18+ months, which is why the acquisition remains a cost center rather than a revenue line. Meanwhile hospital buyers resist adding payer dependency to existing vendor relationships, slowing attach rates.

The staffing backdrop sharpens the math. With a majority of hospitals reporting billing-staffing shortages (commonly cited around 63%), automation that demonstrably reduces manual touches sells faster than platform breadth. Inbox Health, athenahealth Patient Pay, and Phreesia all now offer agentic AI for call deflection, auto-follow-up, and eligibility verification, so the automation race is already crowded — but specialty-specific workflow templates for radiology billing, surgery follow-up, and urgent care remain underserved. That gap is where depth converts into differentiated revenue.

Implementation details and sequencing

How'd you fix Cedar's revenue issues in 2026 — figure 3

Sequencing matters more than any single initiative. Quarter one should focus on segmentation overhaul: pull OODA payer claims data together with third-party affordability and income signals, then classify every open self-pay account into collectible-self-pay, charity-care candidate, or suppress. Dropping the bottom 10-15% immediately reduces cost-to-collect and frees collector capacity for high-yield accounts. Quarter one also starts the payer partnership motion — identify 2-3 regional insurers with aligned incentives on step-down payments, and structure co-marketing agreements where Cedar provides claim-paid probability data and the insurer co-promotes reduced copay friction.

Quarter two ships the NSA automation fast-track: bundle OODA payer fee schedules with CMS price transparency data into auto-refreshed good-faith estimates, with specialty templates for surgery, radiology, and urgent care pre-filled with cost ranges. Package this as an NSA compliance audit plus template pack sold to hospital CFOs — a bonus revenue line that also opens doors for the core self-pay pitch. Quarter two also expands the agentic AI workflow library with escalation trees: eligibility verification to payment-plan offer to card-on-file, denial-letter parsing plus appeals, and post-discharge follow-up sequences segmented by diagnosis, since orthopedic surgery carries materially higher patient responsibility than primary care.

Quarter three runs co-marketed step-down payment pilots with the shortlisted insurers, measuring collection lift and patient payment speed against control cohorts. Quarter four converts pilots into signed partnerships and closes the focused hospital win target. Throughout, position Cedar as the uninsured and self-pay specialist rather than an RCM generalist — build one or two case studies showing time-to-cash improvement on self-pay, and sponsor CFO and controller roundtables on Medicaid mix-shift strategy. The competitive moat is deliberate: stop chasing Waystar and athenahealth on breadth, and instead own the margin-recovery niche where propensity-pay targeting, OODA payer data, and specialty automation compound into something the mega-stacks do not replicate quickly.

FAQ

Is Cedar's 2026 revenue issue caused by the product?

How'd you fix Cedar's revenue issues in 2026 — figure 5

No. The product is not the core problem. Margin erosion comes from a patient-mix shift toward uninsured and difficult-to-collect cohorts whose collection rates run far below insured populations. That drags revenue per patient down even when volumes are stable, which is why segmentation and cost-to-collect discipline matter more than feature parity.

How does propensity-pay targeting fix revenue leakage? It uses OODA payer claims data plus third-party affordability signals to sort accounts into collectible-self-pay, charity-care, and suppress cohorts. Collection spend concentrates on the first two, and the bottom 10-15% is dropped entirely. The target is a 400 basis point collection-rate lift on the difficult-to-collect pool with lower operating cost.

What makes OODA payer bundling different from direct payer sales? Direct payer sales cycles run 18+ months and hospital buyers resist added payer dependency, which is why OODA stayed a cost center. Bundling flips the motion: co-market step-down patient payments with 2-3 regional insurers, where Cedar supplies claim-paid probability data and earns recurring data-licensing revenue. Target is 5-8 partnerships by Q4 2026.

How fast can NSA automation pay off? Quickly, because the manual burden is concrete. Auto-refreshed good-faith estimates from OODA fee schedules and CMS price transparency data cut estimate-writing from roughly 2 hours to about 15 minutes per patient. Packaging it as an NSA compliance audit plus specialty template pack creates a bonus revenue line while opening CFO conversations.

What results should leadership expect by end of 2026? Realistic targets: 400 basis point collection lift on difficult-to-collect accounts, 5-8 payer partnerships signed, 30% reduction in patient billing calls from agentic workflows, and 15-20 focused self-pay hospital wins. Results vary with starting payer mix and contract terms, so track cohort-level collection rates quarterly rather than annual averages.

Does this mean abandoning broader RCM ambitions? Not permanently — sequencing matters. Lead with self-pay depth to stabilize revenue and generate referenceable case studies, then selectively broaden once payer partnerships and agentic automation create pull. The 2026 identity should be self-pay specialist; breadth can follow proven margin recovery, not precede it.

Sources

https://www.cms.gov/ — CMS price transparency and No Surprises Act guidance, good-faith estimate requirements
https://www.waystar.com/ — Waystar revenue cycle and patient payments platform information
https://www.athenahealth.com/ — athenahealth patient pay and EHR-integrated RCM details
https://www.phreesia.com/ — Phreesia patient intake and payment capture capabilities
https://www.hhs.gov/ — Department of Health and Human Services coverage and uninsured population data
https://www.mckinsey.com/ — healthcare revenue cycle and margin performance research
https://hbr.org/ — revenue turnaround and pricing strategy frameworks
https://www.gartner.com/ — healthcare IT market and vendor assessments
https://www2.deloitte.com/ — healthcare financial trends and operational efficiency reports

flowchart TD A[Assess 2026 revenue position] --> B{Win rate vs Waystar declining?} B -->|Yes| C["Depth path: self-pay specialist"] B -->|No| D{Difficult-to-collect gap vs insured?} D -->|60-70% lower| C D -->|Narrow| E["Breadth path: platform race"] C --> F[Rebuild propensity segmentation] C --> G[Bundle OODA payer data] C --> H[Automate NSA estimates] F --> I["Suppress bottom 10-15% of accounts"] G --> J[Co-market with 2-3 regional insurers] H --> K[Specialty GFE templates] I --> L[Reinvest spend in collectible cohorts] J --> M[Recurring payer data licensing] K --> N[15-20 focused hospital wins] L --> N M --> N E --> O[Feature parity investment] O --> P[Enterprise RCM selling] P --> Q[Higher CAC, longer cycles]

flowchart TD Q1A["Q1: Segmentation overhaul"] --> Q1B["Classify accounts: collectible, charity, suppress"] Q1B --> Q1C["Drop bottom 10-15%"] Q1A --> Q1D["Q1: Payer partner shortlist"] Q1D --> Q2A["Q2: NSA automation fast-track"] Q2A --> Q2B[Auto-refreshed GFE templates by specialty] Q2B --> Q2C[NSA compliance audit product] Q1C --> Q2D["Q2: Agentic AI workflow library"] Q2D --> Q2E[Eligibility to payment-plan escalation trees] Q2D --> Q2F[Denial parsing and appeals] Q2E --> Q3A["Q3: Co-marketed step-down payment pilots"] Q2C --> Q3A Q3A --> Q3B["Claim-paid probability above 85% threshold"] Q3B --> Q4A["Q4: 5-8 payer partnerships signed"] Q3A --> Q4B["Q4: 15-20 focused hospital wins"] Q4A --> Q4C[Recurring data-licensing revenue] Q4B --> Q4C

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## Direct Answer

Fixing Cedar's 2026 revenue issues means pivoting from broad RCM platform to self-pay specialist: overhaul propensity-pay segmentation to drop uncollectible cohorts, bundle OODA payer data into co-marketed step-down payment deals with regional insurers, automate No-Surprises Act estimates, and ship specialty-specific agentic AI workflows. Target 400bp collection lift, 5-8 payer partnerships, and 15-20 focused hospital wins.

## The two options compared: platform breadth versus self-pay depth

Cedar faces a genuine strategic fork in 2026, and the choice drives every downstream decision about product, sales, and capital allocation. The first option is to keep chasing platform breadth — matching Waystar after its Patientco acquisition, athenahealth Patient Pay, and Phreesia feature-for-feature across eligibility, claims, price transparency, and patient payments. The appeal is obvious: hospital procurement teams prefer consolidated vendors, and a broader stack theoretically raises average contract value. The problem is that Cedar would be fighting a well-capitalized incumbent on its home turf, where Waystar already processes enormous claims volume and bundles payer pricing directly into patient payment flows. Cedar's revenue would stay exposed to procurement gravity, and every renewal becomes a price negotiation against a mega-stack.

The second option is to go deep on self-pay and the difficult-to-collect pool — uninsured, underinsured, digitally dark, and complex-bill patients. This is where the margin actually bleeds: a large share of patient out-of-pocket dollars now sits in cohorts with dramatically lower collection rates than insured, stable-coverage populations. Cedar's existing propensity logic was built for stable-coverage cohorts and cannot reliably segment or suppress low-value accounts, so collections spend gets spread across accounts with near-zero recovery probability. Going deep means rebuilding segmentation, suppressing the bottom 10-15% of accounts entirely, and reinvesting that spend into collectible-self-pay and charity-care candidates. The trade-off is narrower total addressable market and a smaller average deal — but higher win rates, stickier deployments, and a defensible niche that Waystar and Phreesia are not optimized to serve.

![How'd you fix Cedar's revenue issues in 2026 — figure 1](/assets/qa/q1266-b1.jpg)




The comparison matters because the two options imply opposite sales motions. Breadth requires enterprise RCM selling against incumbents with 18-month cycles and heavy proof-of-concept demands. Depth requires CFO and controller-level selling on margin recovery, faster pilots, and case-study-driven expansion. For a company with a $425M acquisition (OODA) still functioning as a cost center, the depth path converts existing assets into revenue faster. The breadth path requires new capital and a multi-year feature race. In practice the winning answer is a sequenced hybrid: lead with depth to stabilize revenue and generate referenceable wins, then selectively broaden once payer partnerships and agentic automation create pull. But the primary identity for 2026 should be self-pay specialist, not RCM generalist.

## How to decide between them

The decision framework hinges on three measurable inputs: current win rate against Waystar and athenahealth, collection-rate performance on the difficult-to-collect pool versus insured cohorts, and payer partnership pipeline velocity. If win rates against mega-vendors are declining while difficult-to-collect collection rates lag insured rates by 60-70%, depth wins decisively. If payer sales cycles are stretching past 18 months with no signed deals, the OODA bundling thesis needs a co-marketing partner rather than direct payer sales.

![How'd you fix Cedar's revenue issues in 2026 — figure 2](/assets/qa/q1266-b2.jpg)




```mermaid
flowchart TD
    A[Assess 2026 revenue position] --> B{Win rate vs Waystar declining?}
    B -->|Yes| C[Depth path: self-pay specialist]
    B -->|No| D{Difficult-to-collect gap vs insured?}
    D -->|60-70% lower| C
    D -->|Narrow| E[Breadth path: platform race]
    C --> F[Rebuild propensity segmentation]
    C --> G[Bundle OODA payer data]
    C --> H[Automate NSA estimates]
    F --> I[Suppress bottom 10-15% of accounts]
    G --> J[Co-market with 2-3 regional insurers]
    H --> K[Specialty GFE templates]
    I --> L[Reinvest spend in collectible cohorts]
    J --> M[Recurring payer data licensing]
    K --> N[15-20 focused hospital wins]
    L --> N
    M --> N
    E --> O[Feature parity investment]
    O --> P[Enterprise RCM selling]
    P --> Q[Higher CAC, longer cycles]
```

The diagram makes the sequencing explicit: depth decisions feed directly into segmentation, payer bundling, and compliance automation workstreams, all converging on a focused hospital win target. Breadth decisions, by contrast, funnel into feature parity investment and enterprise selling with structurally higher customer acquisition cost and longer cycles. A RevOps leader evaluating this should score each branch against cash-conversion timeline — depth workstreams can show collection-rate movement within two quarters, while breadth investments typically take four or more quarters to influence win rates.

## Concrete numbers behind each option

The depth path has quantifiable targets. On segmentation, suppressing the bottom 10-15% of accounts and concentrating collections spend on collectible-self-pay and charity-care cohorts targets a 400 basis point collection-rate lift on the difficult-to-collect pool. On payer bundling, co-marketing step-down patient payment programs with 2-3 major regional insurers — where copay friction drops when claim-paid probability exceeds roughly 85% — targets 5-8 new payer partnerships by Q4 2026, each generating recurring data-licensing revenue. On compliance automation, auto-refreshed good-faith estimates built from OODA payer fee schedules plus CMS price transparency data cut manual estimate-writing from about 2 hours to roughly 15 minutes per patient. On agentic AI, expanding the April 2025 launch with pre-built escalation trees targets a 30% reduction in patient billing calls, benchmarked against Phreesia's reported 88% copay-at-intake capture versus Cedar's implied 60-65%.

![How'd you fix Cedar's revenue issues in 2026 — figure 3](/assets/qa/q1266-b3.jpg)




The breadth path's numbers are less favorable. Matching Waystar's consolidated claims-plus-pricing-plus-payments stack requires multi-quarter engineering investment with no guaranteed differentiation, since the incumbent already holds distribution through hospital procurement. Enterprise RCM sales cycles commonly run 12-18 months, and proof-of-concept demands consume solutions engineering capacity. Payer sales cycles for OODA's payer-side revenue — eligibility, claims prediction, denial management — run 18+ months, which is why the acquisition remains a cost center rather than a revenue line. Meanwhile hospital buyers resist adding payer dependency to existing vendor relationships, slowing attach rates.

The staffing backdrop sharpens the math. With a majority of hospitals reporting billing-staffing shortages (commonly cited around 63%), automation that demonstrably reduces manual touches sells faster than platform breadth. Inbox Health, athenahealth Patient Pay, and Phreesia all now offer agentic AI for call deflection, auto-follow-up, and eligibility verification, so the automation race is already crowded — but specialty-specific workflow templates for radiology billing, surgery follow-up, and urgent care remain underserved. That gap is where depth converts into differentiated revenue.

![How'd you fix Cedar's revenue issues in 2026 — figure 4](/assets/qa/q1266-b4.jpg)




## Implementation details and sequencing

Sequencing matters more than any single initiative. Quarter one should focus on segmentation overhaul: pull OODA payer claims data together with third-party affordability and income signals, then classify every open self-pay account into collectible-self-pay, charity-care candidate, or suppress. Dropping the bottom 10-15% immediately reduces cost-to-collect and frees collector capacity for high-yield accounts. Quarter one also starts the payer partnership motion — identify 2-3 regional insurers with aligned incentives on step-down payments, and structure co-marketing agreements where Cedar provides claim-paid probability data and the insurer co-promotes reduced copay friction.

Quarter two ships the NSA automation fast-track: bundle OODA payer fee schedules with CMS price transparency data into auto-refreshed good-faith estimates, with specialty templates for surgery, radiology, and urgent care pre-filled with cost ranges. Package this as an NSA compliance audit plus template pack sold to hospital CFOs — a bonus revenue line that also opens doors for the core self-pay pitch. Quarter two also expands the agentic AI workflow library with escalation trees: eligibility verification to payment-plan offer to card-on-file, denial-letter parsing plus appeals, and post-discharge follow-up sequences segmented by diagnosis, since orthopedic surgery carries materially higher patient responsibility than primary care.

![How'd you fix Cedar's revenue issues in 2026 — figure 5](/assets/qa/q1266-b5.jpg)




```mermaid
flowchart TD
    Q1A[Q1: Segmentation overhaul] --> Q1B[Classify accounts: collectible, charity, suppress]
    Q1B --> Q1C[Drop bottom 10-15%]
    Q1A --> Q1D[Q1: Payer partner shortlist]
    Q1D --> Q2A[Q2: NSA automation fast-track]
    Q2A --> Q2B[Auto-refreshed GFE templates by specialty]
    Q2B --> Q2C[NSA compliance audit product]
    Q1C --> Q2D[Q2: Agentic AI workflow library]
    Q2D --> Q2E[Eligibility to payment-plan escalation trees]
    Q2D --> Q2F[Denial parsing and appeals]
    Q2E --> Q3A[Q3: Co-marketed step-down payment pilots]
    Q2C --> Q3A
    Q3A --> Q3B[Claim-paid probability above 85% threshold]
    Q3B --> Q4A[Q4: 5-8 payer partnerships signed]
    Q3A --> Q4B[Q4: 15-20 focused hospital wins]
    Q4A --> Q4C[Recurring data-licensing revenue]
    Q4B --> Q4C
```

Quarter three runs co-marketed step-down payment pilots with the shortlisted insurers, measuring collection lift and patient payment speed against control cohorts. Quarter four converts pilots into signed partnerships and closes the focused hospital win target. Throughout, position Cedar as the uninsured and self-pay specialist rather than an RCM generalist — build one or two case studies showing time-to-cash improvement on self-pay, and sponsor CFO and controller roundtables on Medicaid mix-shift strategy. The competitive moat is deliberate: stop chasing Waystar and athenahealth on breadth, and instead own the margin-recovery niche where propensity-pay targeting, OODA payer data, and specialty automation compound into something the mega-stacks do not replicate quickly.

## Related questions

### Why is Cedar's revenue problem a margin problem rather than a product problem?

The product works; the mix shifted. A rising share of patient out-of-pocket dollars comes from uninsured and hard-to-collect cohorts with 60-70% lower collection rates than insured populations. Revenue per patient falls even when volume holds, so the fix is cohort targeting and cost-to-collect reduction, not a rebuild.

### What does propensity-pay segmentation actually change?

It classifies every open account into collectible-self-pay, charity-care candidate, or suppress, then concentrates collector capacity on the first two. Dropping the bottom 10-15% cuts wasted spend and targets a 400 basis point collection-rate lift on the difficult-to-collect pool.

### How does OODA payer data become revenue instead of a cost center?

By bundling it into three-party deals: Cedar supplies claim-paid probability data, regional insurers co-market step-down patient payments when probability exceeds roughly 85%, and hospitals get higher net patient payments. Cedar earns recurring data-licensing revenue, targeting 5-8 payer partnerships by Q4 2026.

### What is the fastest compliance win for 2026?

Auto-refreshed good-faith estimates built from OODA fee schedules plus CMS price transparency data, with specialty templates for surgery, radiology, and urgent care. Manual estimate-writing drops from about 2 hours to roughly 15 minutes, and the audit-plus-template pack sells as a standalone CFO product.

### Where should Cedar not compete?

Directly against Waystar's consolidated claims-pricing-payments stack or athenahealth's EHR-integrated patient pay. Those are breadth fights with long cycles and entrenched distribution. Cedar should own self-pay and uninsured margin recovery, where specialty workflow depth beats platform parity.

## FAQ

**Is Cedar's 2026 revenue issue caused by the product?**
No. The product is not the core problem. Margin erosion comes from a patient-mix shift toward uninsured and difficult-to-collect cohorts whose collection rates run far below insured populations. That drags revenue per patient down even when volumes are stable, which is why segmentation and cost-to-collect discipline matter more than feature parity.

**How does propensity-pay targeting fix revenue leakage?**
It uses OODA payer claims data plus third-party affordability signals to sort accounts into collectible-self-pay, charity-care, and suppress cohorts. Collection spend concentrates on the first two, and the bottom 10-15% is dropped entirely. The target is a 400 basis point collection-rate lift on the difficult-to-collect pool with lower operating cost.

**What makes OODA payer bundling different from direct payer sales?**
Direct payer sales cycles run 18+ months and hospital buyers resist added payer dependency, which is why OODA stayed a cost center. Bundling flips the motion: co-market step-down patient payments with 2-3 regional insurers, where Cedar supplies claim-paid probability data and earns recurring data-licensing revenue. Target is 5-8 partnerships by Q4 2026.

**How fast can NSA automation pay off?**
Quickly, because the manual burden is concrete. Auto-refreshed good-faith estimates from OODA fee schedules and CMS price transparency data cut estimate-writing from roughly 2 hours to about 15 minutes per patient. Packaging it as an NSA compliance audit plus specialty template pack creates a bonus revenue line while opening CFO conversations.

**What results should leadership expect by end of 2026?**
Realistic targets: 400 basis point collection lift on difficult-to-collect accounts, 5-8 payer partnerships signed, 30% reduction in patient billing calls from agentic workflows, and 15-20 focused self-pay hospital wins. Results vary with starting payer mix and contract terms, so track cohort-level collection rates quarterly rather than annual averages.

**Does this mean abandoning broader RCM ambitions?**
Not permanently — sequencing matters. Lead with self-pay depth to stabilize revenue and generate referenceable case studies, then selectively broaden once payer partnerships and agentic automation create pull. The 2026 identity should be self-pay specialist; breadth can follow proven margin recovery, not precede it.

## Sources

- https://www.cms.gov/ — CMS price transparency and No Surprises Act guidance, good-faith estimate requirements
- https://www.waystar.com/ — Waystar revenue cycle and patient payments platform information
- https://www.athenahealth.com/ — athenahealth patient pay and EHR-integrated RCM details
- https://www.phreesia.com/ — Phreesia patient intake and payment capture capabilities
- https://www.hhs.gov/ — Department of Health and Human Services coverage and uninsured population data
- https://www.mckinsey.com/ — healthcare revenue cycle and margin performance research
- https://hbr.org/ — revenue turnaround and pricing strategy frameworks
- https://www.gartner.com/ — healthcare IT market and vendor assessments
- https://www2.deloitte.com/ — healthcare financial trends and operational efficiency reports

## Related on PULSE

- [How'd you fix Waystar's revenue issues in 2026?](/knowledge/q1317)
- [How'd you fix Phreesia's revenue issues in 2026?](/knowledge/q1318)
- [How'd you fix athenahealth's revenue issues in 2026?](/knowledge/q1319)
- [How'd you fix Inbox Health's revenue issues in 2026?](/knowledge/q1320)
- [How should RevOps teams benchmark patient collection rates?](/knowledge/q1321)

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