CPT Billing Explorer FAQ
1) What data are benchmarks based on?
Benchmarks come from CMS Medicare Physician/Supplier utilization data file
MUP_PHY_R25_P05_V20_D23_Prov_Svc.csv, representing calendar year 2023 claims (January-December 2023).
2) Why use Medicare benchmarks if our payer mix includes commercial plans?
Medicare is used as a large, nationally consistent reference point for coding-pattern comparisons. Results should be interpreted as directional for private payors, not a literal contract-specific reimbursement forecast.
3) Does this tool adjust for case mix, acuity, or referral complexity?
Not directly. The model compares coding mix distributions within specialty and category. Clinical acuity and documentation quality still need local chart-review context before operational conclusions.
4) What does “Potential $ Difference” mean?
It is a 12-month estimate of allowed-amount impact if your entered within-category CPT mix matched the selected benchmark, while holding your total entered category counts fixed.
5) Is this a compliance recommendation to code at higher levels?
No. The tool is an analytic benchmark aid, not coding advice. Documentation standards and medical necessity remain the governing criteria for all level selection.
6) How should leaders interpret benchmark vs baseline controls?
“Benchmark” selects the target Medicare distribution. “Your Estimated Baseline” is used to prepopulate counts for scenario setup before manual edits.
7) Why do some categories show “n/a” or incomplete benchmark behavior?
This typically means benchmark detail is incomplete for that category or required payment data is missing. Low usable volume can also reduce benchmark stability in certain specialty-category combinations.
8) Are pseudo-codes like “ABSENCE OF 99291” included?
Yes. Some pseudo-codes are derived from defined CPT combinations to represent opportunities where specific codes are absent. These are modeled explicitly and shown in the explorer.
9) Can we upload our own claims file directly?
Not in the current UI. Today the workflow is scenario-based: prepopulated estimates plus manual count edits.
10) What is the recommended governance use?
Use this tool to prioritize where to review documentation workflows, education needs, and coding variance. Final decisions should pair this output with compliance review, chart audits, and local payer-contract realities.
CASE STUDIES / TESTIMONIALS
Reducing clinical variation and clinician frustration
A process improvement manager at a regional health system identified inappropriate lab orders during a data-driven order set review process. The downstream removal of inpatient bacterial antigen testing saved over $700,000 annually on low-yield testing, while streamlining the order set design.
OUTCOMES
$700K annual savings by reducing bacterial antigen orders 57%
10X efficiency gains in order set review processes
Streamlined workflows by retiring redundant order sets
Cutting non-essential orders and IT time
A regional health system reduced non-essential IV fluid usage by 40% within weeks of a nationwide shortage. With Phrase Health, they implemented targeted interventions 5× faster than traditional analytics methods would allow, bypassing IT bottlenecks despite competing strategic priorities.
"The great thing about Phrase Health is that it makes it very easy to get the data you want. Most other vendors make retrieving any sort of data cumbersome.
Medical director,
Academic health system
ROI
$1M+
saved in lab costs
3,000+ hrs
saved in EHR clicks
10x
operational efficiences
50%
more care gaps closed
Get started with your personalized demo
Explore our platform that identifies ordering patterns and clinical variation opportunities. Start now to cut clinical waste and boost efficiency.
Sign up to our newsletter