Why Dental Claims Kept Rising: How a Pet Insurance Provider Used Consulting and Analytics to Diagnose Unexplained Claims Inflation in Companion Animal Dental Treatment

Executive Snapshot

Client

Pet Insurance Provider, United States

Situation/Challenge

The client had seen dental treatment claims grow faster than any other companion animal health category over three years, at a rate that exceeded both the growth in dental-covered policy count and the general veterinary fee inflation the actuarial team had modelled. The claims team had begun querying whether the inflation reflected genuine dental disease prevalence growth, fee schedule changes at veterinary practices, or a shift in how dental procedures were being coded on claims submissions. Without a structured diagnosis, the actuarial team could not calibrate the reserve correctly for the next policy year.

Objective

Engage consulting to design a dental claims inflation diagnostic framework, then apply analytics to the client's three-year dental claims dataset to identify whether the inflation was driven by prevalence, fee, coding, or a combination of factors.

Constancy Researchers Solution

Consulting Services combined with Data Analytics & Business Intelligence, a consulting-designed dental claims inflation diagnostic framework, paired with an analytics workstream examining claims volume, procedure code distribution, average claim value, and practice-level billing patterns across three years of dental treatment claims.

Impact

Analytics confirmed the dental claims inflation was driven by two distinct factors in roughly equal measure: genuine average fee increases at a specific segment of high-volume dental practices, and a shift in procedure coding toward higher-value codes on procedures that had historically been submitted under lower-value codes. The prevalence of actual dental disease claims was stable after adjusting for policy count growth. Consulting analysis identified the coding shift as partially addressable through updated claims adjudication logic.

Client Outcome

The client updated its dental claims adjudication rules to reflect the coding shift finding, reducing the unexplained coding-driven claims inflation, and the actuarial team recalibrated its dental reserve using the analytically separated prevalence, fee, and coding components.

The Situation / Challenge

Claims inflation in a specific treatment category is not always what it appears to be. An aggregate dental claims cost that grows faster than policy count and faster than general fee inflation could mean pets are genuinely developing more dental disease, that veterinary practices are charging more for the same procedures, that insurers are paying more for the same procedures because of how they are being coded, or some combination of all three.

The client’s actuarial team was carrying a dental reserve built on a model that had not separated these components, and the reserve was beginning to look inadequate. The claims team had flagged the coding shift hypothesis internally but had no analytical backing for it.

Running the next policy year’s reserve and pricing on the wrong diagnosis of the inflation driver was a risk neither the actuarial nor the commercial team wanted to take, but they had not yet built the analytics to distinguish between the competing hypotheses.

Key Challenges

  • No diagnostic framework separating dental claims inflation into its component drivers: disease prevalence, veterinary fee schedule changes, and procedure coding shifts.
  • An actuarial reserve model that had not separated the three inflation drivers, creating uncertainty about whether the reserve was adequately calibrated.
  • A claims team hypothesis about coding shift without analytical data to confirm or quantify it.
  • No practice-level billing pattern analysis identifying whether specific veterinary practices were driving a disproportionate share of the high-value coding shift.
  • A policy pricing and reserve decision for the next year that required a separated inflation diagnosis rather than an aggregate trend line.
  • Growing dental claims inflation that was moving faster than either policy count growth or modelled general veterinary fee inflation could explain.

Dental claims inflation in pet insurance is structurally similar to the same problem in human health insurance: the aggregate cost trend conceals several distinct drivers that require different management responses. Treating a coding shift as a prevalence increase and reserving accordingly overestimates future liability. Treating a genuine fee inflation as a coding artefact and not reserving accordingly underestimates it. Separating the components is not optional when the policy year reserve depends on getting the diagnosis right.

Constancy Researchers Solution

Constancy Researchers designed a diagnostic framework that separated dental claims inflation into its three component drivers, then applied analytics to the full three-year claims dataset to quantify each driver’s contribution and identify where the coding shift was concentrated.

Dental Claims Inflation Diagnostic Framework Design
  • Designed a consulting-led diagnostic framework separating three distinct dental claims inflation drivers: claims volume growth attributable to genuine dental disease prevalence increase net of policy count growth, average claim value growth attributable to veterinary fee schedule changes for established procedure codes, and average claim value growth attributable to migration toward higher-value procedure codes for procedures that had historically submitted under lower codes.
  • Established baseline expectations for each component using industry dental disease prevalence data, published veterinary fee surveys.
Claims Volume & Prevalence Analytics
  • Analysed three years of dental claims volume normalised by policy count growth.
  • Found that dental disease prevalence, measured as claims per hundred covered policies, was stable across the three-year period after normalisation.
Veterinary Fee Schedule Analytics
  • Analysed average claim values by procedure code over three years.
  • Found that a segment of high-volume dental practices had implemented fee schedule increases materially above the surveyed regional average.
Adjudication Rule Recommendation & Reserve Recalibration
  • Analysed the distribution of dental procedure codes submitted across the three-year period.
  • Found a clear shift over three years toward higher-value dental procedure codes.
Rural Market Access & Communication Plan
  • Delivered an adjudication rule update recommendation for the coding-shift component, specifying the procedure code combinations and practice billing pattern flags that should trigger enhanced review before settlement.
  • Provided the actuarial team with a separated three-component inflation decomposition for reserve recalibration.

The engagement gave the actuarial team a separated, quantified diagnosis they could model from rather than an aggregate trend line, and gave the claims team an evidence-based adjudication update rather than a general watchlist.

Impact

  • Prevalence analytics confirmed dental disease incidence was stable per covered policy after normalisation for policy count growth.
  • Fee analytics identified a segment of high-volume practices with fee increases materially above the regional average.
  • Code distribution analytics confirmed a three-year shift toward higher-value codes accounting for approximately half the unexplained inflation.
  • The coding shift was concentrated in a specific practice subset identifiable through billing pattern flags.
  • Adjudication rule updates were designed to address the coding-shift component through enhanced review triggers.
  • The actuarial team received a three-component inflation decomposition for reserve recalibration.
  • The dental reserve was recalibrated separately for the prevalence, fee, and coding components.
  • Coding-shift-driven claims inflation reduced following the adjudication rule update.

Client Outcome

Reserve Recalibration

The actuarial team recalibrated the dental reserve using a three-component inflation decomposition rather than an undifferentiated aggregate trend.

Coding Inflation Addressed

Adjudication rule updates reduced the coding-shift component of dental claims inflation by triggering enhanced review on flagged billing patterns.

Prevalence Clarity

Dental disease prevalence was confirmed as stable per covered policy, eliminating genuine disease incidence growth as a reserve driver.

Fee Inflation Quantified

High-volume practice fee increases were separated from coding artefacts, giving the actuarial team a precise fee inflation input for pricing.

Claims Team Intelligence

Practice-level billing pattern analysis gave the claims team an evidence-based adjudication update rather than a general fraud watch directive.

Pricing Accuracy

Next policy year dental pricing was built on a separated component model rather than an aggregate trend extrapolation.

Diagnosis Speed

The three-component separation was produced analytically from existing claims data, avoiding the delay of an external audit or regulatory referral.

Actuarial Confidence

The reserve entered the next policy year with a quantified, component-level justification the actuarial team could defend to the board.

Market Positioning

The insurer was repositioned as a data-disciplined underwriter that separates claims inflation components analytically rather than reserving against undifferentiated trend lines.

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