Healthcare Billing Needs Consistency and AI That Actually Helps
Value-based and risk-based contracts changed what gets reimbursed. It's no longer just procedures. Payers want proof of what providers actually did for patients, and each payer asks for that proof differently. Without clear rules, documentation varies by clinician and claims bounce back.
What providers are feeling on the ground
Tiffany Waltos, Director of Revenue and Analytics at Community Health Care in Northern Ohio, summed it up well: inconsistent coding doesn't just frustrate payers-it shows up on patient bills. One specialist's visit can cost more than another's for the same condition. That erodes trust and slows cash.
Community Health Care runs 19 offices with 65 primary care providers. To get first-pass approvals, they set explicit coding and billing rules and aligned clinician documentation to those rules across the organization.
Leaning on your EHR vendor-strategically
They engaged their EHR vendor's revenue cycle consulting team to tackle their thorniest gaps. The work focused on the rules engine, eligibility checks, and claim edits before submission. The approach was collaborative: their internal team prioritized needs; the vendor brought additional recommendations and execution support.
If you're on eClinicalWorks, consider the same path. If you're on another platform, ask your vendor for a targeted RCM program with clear deliverables, test plans, and timelines.
Where AI actually adds value today
AI can speed up denial research-pinpointing why a claim failed and drafting a rule to prevent repeat errors. That shortens feedback loops from weeks to hours. Ambient voice tools can also suggest diagnosis and PT assessment codes inline, reducing missed specificity and rework.
None of this replaces policy. AI fits best on top of strong rules, standard templates, and disciplined auditing.
Your practical playbook for cleaner, faster reimbursement
- Map payer-by-payer requirements for value-based and risk contracts. Turn them into standardized documentation and coding checklists.
- Build (or refine) a rules engine that enforces those checklists at charge capture and before claim submission.
- Run eligibility and benefits checks up front. Flag plan nuances that affect documentation or prior auth.
- Give clinicians smart templates and real-time coding prompts, including ambient suggestions where appropriate.
- Use denial analytics to auto-create preventive edits. Review weekly. Promote high-impact edits into your core rules.
- Hold short, recurring coder-clinician huddles to align on patterns, not one-off fixes.
- Track first-pass yield, days in A/R, denial rate by reason code, and variance in patient responsibility by condition.
- Publish patient-facing billing FAQs so costs feel predictable across providers.
Resources and next steps
Community Health Care's experience shows the path: align documentation, standardize coding, partner closely with your EHR, and let AI handle the repetitive, error-prone steps. If you want to see how a peer organization approached it, visit Community Health Care. For vendor-side support, explore eClinicalWorks services.
For broader policy context on value-based programs, see CMS Value-Based Programs. If your team is building skills around AI for operations and RCM, here's a curated catalog of AI courses by job.
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