Pre-op IOL selection counseling. Earlier in the journey, structurally familiar to the post-op work above, commercially different.
There is no single correct lens. The right choice depends on the patient's visual priorities (spectacle independence vs. night-driving glare tolerance vs. out-of-pocket cost) and ocular candidacy [braga-mele-2014]. This tool surfaces trade-offs. It does not steer toward premium IOLs. Monofocal-plus-glasses is presented as a valid choice where it fits the patient's stated values.
A 2026 fee-schedule cut that resets the math for premium-IOL counseling.
CMS's CY 2026 Physician Fee Schedule final rule (CMS-1832-F, released Oct 31, 2025; effective Jan 1, 2026) cuts the surgeon's professional fee for CPT 66984 by ~11%, from $521.75 to $462.94 [cms-mpfs-2026]. Review of Ophthalmology calls it the largest single-year reduction to the code in three decades.
The 11% is composite, not a single conversion-factor cut. It is the net of three stacked moves: a +3.77% conversion-factor update (qualifying APM participants), a -2.5% efficiency adjustment on work RVUs (66984 work RVU 7.35 → 7.17), and a CMS policy change that halves indirect-PE allocation for facility services (66984 facility PE-RVU 8.23 → 6.15) [cms-mpfs-2026].
The cut hits the surgeon's professional fee. It does not hit the ASC facility payment for the same procedure. The separate CY 2026 OPPS/ASC final rule (CMS-1834-FC) raised the ASC facility line for 66984 by ~3.4% ($1,214.31 → $1,255.73), after ASCRS-led advocacy got CMS to correct an IOL-cost calculation error [cms-opps-asc-2026]. Office-based services rose modestly. "Cataract reimbursement down 11%" is directionally inaccurate either way.
The implication: surgeon professional-fee compression on a routine cataract case makes the cash-pay premium-IOL channel a revenue-defense lever, not a growth play. Premium IOLs (toric, EDOF, multifocal) are elective, non-covered, and require materially more pre-op counseling than monofocal: dysphotopsia risk, contrast loss, neuroadaptation, spectacle-independence trade-offs [aao-ppp-2021] [rampat-gatinel-2021] [braga-mele-2014]. That counseling time is unbundled, chair-time-constrained, and not separately billable. An AI-assisted counseling layer that improves completeness without consuming surgeon chair time changes the math.
This tool has no CPT or reimbursement code of its own. It works by improving the economics of a procedure that does.
Headline metric: counseling completeness
The headline form is fixed before the number is measured, so the number cannot move the goalposts: covered M of M elements relevant to the archetype's stated values across K hand-curated archetypes, with zero fabricated citations and N% of claims resolving against the locked source list. The element checklist anchors to the ASCRS Cataract Clinical Committee's patient-selection criteria [braga-mele-2014] and the AAO Preferred Practice Pattern's informed-consent enumeration [aao-ppp-2021].
Three secondary metrics sit in the integrity strip beneath the headline: cite-resolution rate (share of clinical claims resolving against the locked IOL source list), gap-flag completeness (share of out-of-list claims explicitly gap-flagged rather than fabricated), and a readability sub-metric (Flesch-Kincaid grade-level target around 8th grade, anchored to the surgeon-vs-chatbot 10.64 vs. 12.54 finding [ophthal-epi-2025-surgeon-vs-chatbot]). Eval wiring lands in a separate chunk; the framing is locked here.
Eval methodology, named limits up front
We adopt Trojacka 2025's persona-cohort and stateless re-instantiation scaffold, and build a domain-specific rubric for counseling output quality. The rubric is not inherited from Trojacka [trojacka-2025]. Trojacka pre-validates a Patient-Reported Outcome Measure, not a conversational AI; its psychometric battery (CFA, DIF, Cronbach α, ICC, Spearman vs. NEI-VFQ-25) is built for instrument validation, not counseling-output evaluation.
Synthetic patient archetypes compress between-group variance compared to real cohorts (a documented limitation of LLM-persona pre-validation [trojacka-2025]). We mitigate by hand-curating archetypes with pre-specified divergent value-weights, and we treat the eval as a construct demonstration, not an effect-size estimate. A real-cohort validation study is the next step beyond this artifact.
The strongest IOL decision-aid evidence is from Chinese single-center studies [ye-qu-2021] [iol-pda-2026-chen]. US-population transferability is uncertain; this artifact treats those studies as proof-of-concept evidence that structured IOL decision support is feasible, not as portable effect-size benchmarks.
Two scope rules on those two citations. Ye/Qu 2021 is cited only for the validity claim that structured IOL decision aids improve informed choice, which is the actual outcome the RCT measured [ye-qu-2021]. Chen et al. 2026 is cited only for instrument-in-domain provenance: PrepDM [prepdm], SDM-Q-9 [sdm-q-9], and Satisfaction With Decision have been applied to IOL-PDA evaluation, in a quasi-experimental Chinese-cohort study with abstract-only verification [iol-pda-2026-chen]. The eval scores against hand-curated archetype answer keys, not against either paper's measurand.
Cost-willingness vs ABN mechanics: a deliberate split
Whether the counseling conversation surfaced out-of-pocket cost for the premium lens is a counseling element. It belongs in the completeness headline and cites the OOP-disclosure discipline that ASCs operate under [asc-bundle-markup-cap-ellis-2019]. Whether the tool quoted or collected a premium-lens payment is a compliance element. It belongs in a separate pass/fail check and does not count toward the counseling-completeness headline. The tool must surface that the premium lens carries an out-of-pocket cost. The tool must not quote or collect that payment; the ASC collects directly from the patient under CMS Ruling 05-01 [asc-bundle-markup-cap-ellis-2019]. The reviewer agent enforces the split in its rubric.