OPTN eGFR Waiting-Time Correction

What this models

This example runs on the OPTN race-neutral eGFR requirement and waiting-time modification network: 12 components and 25 pathways between them. Every context in the Lab is a stylized model, never a reconstruction of any actual deployment, and each assumption behind it carries a provenance label.

Evidence base: 2 assumed · 15 published baseline. In the Lab, the shaded evidence band behind each headline readout draws its width from the least-established class below.

• baseline

  The algorithmic object here is a clinical equation, not a learned system. The 2009 CKD-EPI creatinine equation is a published formula with fixed coefficients, one of which multiplied the estimated kidney function of any patient recorded as Black by 1.159 (95 percent confidence interval 1.144 to 1.170); the peer-reviewed measurement is that the race-including equation overestimated measured GFR in Black patients by a median of 3.7 mL/min per 1.73 square metres, and the equation's authors concluded that race in these equations is a social and not a biologic construct. The schema's model NodeKind is the only home for a computational component, so it carries the equation here — but nothing on this diagram was trained, fitted or shipped by a vendor, and no machine-learning vocabulary appears in any label or copy above.

• baseline

  Two model nodes are drawn because the record documents two distinct computations. The laboratory calculation runs on every fresh specimen and its output set qualifying dates; the paired recomputation runs retrospectively on retrieved historical results, is performed by a transplant program rather than a laboratory, and produces an eligibility determination rather than a lab report. The eligibility rule is what makes the second a component and not a rephrasing of the first: documentation must show the candidate's eGFR was over 20 mL/min under the race-inclusive calculation and 20 or lower under a race-neutral one.

• baseline

  The corrected value's write path into the registry is drawn at zero, and this is the honest shape of a remedy that ran by hand. Nothing recomputed the registry centrally: each program had to identify its own affected candidates, retrieve historical laboratory documentation from its own chart and from outside institutions, run both calculations, and file a modification form that OPTN then accepted. That is why the network's remedy strength sits on the coordinator's write rather than on the equation's, and it is the structural source of the variation the peer-reviewed evaluation later measured between centers.

• baseline

  The reconciliation of the offer sequence against the registry is drawn at zero because the documented arc runs the other way. A backdated qualifying date re-ranks a candidate in the deceased-donor offer sequence directly, and the trade guidance for the audit records candidates receiving a lot of time back, moving to the top of the list and beginning to receive offers, with a significant operational impact on many centers in ensuring that a candidate had been re-evaluated recently. The safeguard the record documents is a clinical re-evaluation of the person, carried here on the physician pathways — the re-ranked candidate surfacing to the clinical team, the coordinator's handoff, and the result of the re-evaluation recorded against the candidate — not a reconciliation of the record before it actions.

• baseline

  The enforcement node is the deceased-donor offer sequence, drawn because the record is explicit that the correction is not advisory: accrued waiting time is a term in the ranking donor kidneys are offered down, so a change to a qualifying date is a change to allocation. The measured allocation effect — modified candidates showing an adjusted hazard ratio of 2.85 for deceased-donor transplantation — is a recorded external observation about served people in the case file, and is never computed from anything drawn here.

• baseline

  The equation's self-loop is drawn at the top rung because this deployment is the monoculture case in its purest form. One published formula was the standard in thousands of independent laboratories for more than a decade, so its coefficient produced the same adjustment, in the same direction, for every patient it touched, everywhere, at once. That is also why the remedy had to be a standards-and-policy action rather than a local fix: no single laboratory's quality process could see a bias that lived inside the formula every laboratory trusted.

• baseline

  The one check that can see this defect is drawn present at the middle rung: the same stored result, computed again under a formula without the coefficient, set beside the figure that was reported. It ran at national scale — 44,912 Black candidate kidney registrations assessed, 14,419 of them modified, about 32 percent — and it is drawn at 2 rather than 3 because what it reaches is bounded by which candidates a program's roster returns and how far its record retrieval goes.

• baseline

  Three reviewer nodes are drawn because the record documents three review functions with different authority, and each is wired in through its own inbound read rather than dangling. The policy committees and board read the monitoring record and hold approval authority; the compliance and attestation function reads what programs filed and holds a deadline, a documentation review and a referral; the independent evaluation team reads the national registry and holds no authority at all. Two findings travelled between them and both are carried: the compliance function's observation that programs were implementing the requirements in various ways, which the policy requirement pathway records as the reason for the 2025 update, and the independent team's measurement, drawn as its own check edge at the low rung because it is one study with no standing cadence.

• baseline

  Demand reads 3 and capacity 2, both from the documented record rather than a default. Demand is 3 because roughly 230 active kidney programs each ran a full waiting-list audit — candidate identification, cross-institution laboratory retrieval, two notifications to every kidney candidate regardless of race, a documented filing per qualifying candidate and an attestation — against a hard deadline, with 12 of 232 programs attested at the six-month snapshot and all 230 by the deadline. Capacity is 2 rather than 1 because the work was completed under a non-discretionary rule by human staff, and 2 rather than 3 because the peer-reviewed evaluation measured significant variation between centers in how it was executed.

• baseline

  The compliance check is drawn at the middle rung with universal coverage, deliberately below the top. Every active kidney program attested by the deadline, which is a completion rate no other board in this catalogue documents — and the independent measurement published afterwards found that modification rates varied significantly by transplant center, with the investigators noting that the variability suggested mixed use of the policies and that the requirement was not articulated clearly at the beginning. A self-attestation confirms that a program says it did the work; it does not show how the work was done.

• baseline

  The candidate assessment roster is drawn as an edgeless mediator per the corpus idiom: a program's list of candidates to assess, produced by the registry's own custom reporting tool. Its scope changed with the policy — the 2023 obligation covered Black candidates registered before 27 July 2022, while the 2025 update requires every registered kidney candidate to be assessed for eligibility — and which candidates the query returns is what decides whom the assessment reaches.

• baseline

  The outside laboratory and dialysis-center results are carried inside the historical record store and on the retrieval pathway, at the same granularity the PAN org uses, rather than as a feed of their own. The eligibility rule turns on documentation of a historical creatinine value, and the trade guidance written for the audit names where programs had to go for it: the electronic medical record, external and reference laboratories, dialysis centers, and record-retrieval and health-information-exchange systems. A candidate's kidney history is spread across institutions, so the figure that decides eligibility is often held by someone other than the transplant program, and reaching it is its own problem rather than a look in the chart. That is why how far a program's retrieval reached is drawn as a pathway rather than asserted as prose, why that pathway and the feed into the paired comparison both carry the identifiable-records marking, and why the 2025 requirements make each program write down which record sources it will review.

• assumed

  The privacy reading of 3 comes from the sensitivity of what actually moves on these pathways, not from any documented data-protection failure — none appears in this record. Special-category health data runs the length of the network: serum creatinine values and kidney-function estimates, a recorded race field that is the selector the whole assessment keys on, and identifiable clinical history requested across institutional boundaries from reference laboratories, dialysis centers and other hospitals. National registration data is also supplied for independent research. It reads above the commercial health boards because those flows run inside a federally contracted national registry with a published policy record, a governed research supply, and a written-protocol requirement — effective 10 September 2025 — covering how a program confirms a candidate's recorded race and which documentation sources it seeks. It reads below the top because the working method of the audit is broad retrieval of identifiable clinical history from wherever it was held.

• baseline

  This record contains no litigation and no enforcement action. It is affirmative governance: a 2022 prohibition, a 2023 retroactive modification programme, published monitoring, an independent peer-reviewed evaluation, and a 2025 tightening in response to measured variance. That absence is a finding rather than a gap — no regulator or court node is drawn, because none acted — and it must not be narrated in a litigation or enforcement register anywhere this network is presented.

• assumed

  Served people are not in the dynamics. Transplant candidates are the subjects of this correction and appear nowhere on this diagram: no waiting time, eligibility date, offer, transplant or clinical outcome for any person is computed from anything drawn here. The published figures about candidates — 14,701 modifications at a median 1.7 years, 14,419 of 44,912 assessed registrations, an adjusted hazard ratio of 2.85 for deceased-donor transplantation among modified candidates — are recorded external observations from OPTN monitoring reports and one peer-reviewed evaluation, each carrying its own denominator and data-snapshot date, and they live in the case file.

• baseline

  The counts are modifications and registrations, not distinct persons, and each carries its snapshot. More than 6,100 modifications is the six-month figure (report published 4 December 2023, data through 5 July 2023); 14,701 modifications processed is the one-year figure (published 8 May 2024, data through 4 January 2024); 14,419 of 44,912 is the peer-reviewed count of listings. The published counts are drawn from the registry and printed in the monitoring reports, which is why each one travels with the date its data was cut. The overestimation magnitudes come from different registers and are never conflated: a median 3.7 mL/min per 1.73 square metres is the peer-reviewed measurement, while up to 16 percent is OPTN's patient-education framing.

• baseline

  The equity framing in this record belongs to the sources that used it, not to this network's own voice. Restitution and restorative justice are the words of the peer-reviewed commentary and the OPTN materials, and the same commentary records the critique that the policy has been called both unfairly too broad and too narrow, addressing one input and one population while leaving open the broader question of whether all patients should accrue predialysis waiting time. Both the framing and the critique are carried with their attribution.

What this example does not show

• No candidate outcome is modeled. The Lab reads institutional propagation only; transplant candidates are boundary-only, and the modification counts, the median time credited, the transplant subtotals and the adjusted hazard ratio for deceased-donor transplantation among modified candidates live in the case file as recorded external observations with their own denominators, never computed on this diagram.
• Every count carries a data-snapshot date because the figures are cumulative and grew. More than 6,100 modifications is the six-month figure (report published 4 December 2023, data through 5 July 2023); 14,701 modifications processed at a median of 1.7 years is the one-year figure (published 8 May 2024, data through 4 January 2024); 14,419 of 44,912 assessed registrations is the peer-reviewed national count. These are counts of modifications and of listings, not of distinct people.
• The two magnitudes for the coefficient's effect come from different registers and are not interchangeable. The peer-reviewed measurement is that the race-including equation overestimated measured GFR in Black patients by a median of 3.7 mL/min per 1.73 square metres; the statement that the race variable could overestimate kidney function by as much as 16 percent is OPTN patient-education framing. Both are cited to their own source.
• There is no litigation and no enforcement action in this record, and it must not be presented in that register. The record is affirmative governance: a prohibition, a retroactive modification programme, published monitoring, an independent evaluation, and a tightening in response to measured variance.
• What the correction reached is bounded, and the record is clearer about its scope than about its completeness. It applies to registered kidney candidates on programs' waiting lists, and it can only advance a qualifying date, never delay one. The peer-reviewed evaluation found modification rates varying significantly by candidate characteristics and by transplant center, with the investigators describing mixed use of the policies and a requirement that was not clearly articulated at the beginning. The 2025 strengthening is in force but its program-completion deadline of 11 September 2026 has not passed. And the peer-reviewed commentary records the standing critique that the policy has been called both unfairly too broad and too narrow, addressing one input and one population while leaving open the question of whether all patients should accrue predialysis waiting time.
• The independent national evaluation's primary record was behind a paywall and a consent wall at verification time; its figures — 32 percent of 44,912, about 610 median priority days, an adjusted hazard ratio of 2.85 with a 95 percent confidence interval of 2.7 to 3.02, and the center-level variation — are carried here as verified by corroboration through a trade report of the same study rather than by direct retrieval of the primary.

Sources and evidence

What this example rests on, claim by claim. Every entry resolves to the same ledger the Evidence Registry publishes.

• The object corrected here is a clinical equation, not a learned system. The standard formulas for estimating glomerular filtration rate from a serum creatinine result — the 1999 MDRD equation and then the 2009 CKD-EPI creatinine equation — applied a coefficient that raised the estimated kidney function of any patient identified as Black; in the 2009 equation that coefficient was 1.159 (95 percent CI 1.144 to 1.170). The stated biological rationale, higher average muscle mass, treated race as a biological rather than a social category, and the MDRD equation behind it was derived from roughly 1,400 White and fewer than 200 Black patients. Inker and colleagues reported in the New England Journal of Medicine on 23 September 2021 that the race-including equation overestimated measured GFR in Black patients by a median of 3.7 mL/min/1.73m2, and concluded that race in eGFR equations is a social and not a biologic construct; OPTN's own patient materials state in a different register that the race variable automatically increased all Black patients' eGFR values, by as much as 16 percent. A kidney transplant candidate begins accruing waiting time when the estimate reaches 20 mL/min/1.73m2 or lower, so an estimate raised above that line delayed the clock; two studies cited in the nephrology commentary put the lost time at 1.3 and 1.9 years for affected Black candidates.

  empirical
  • Academic Inker, L. A., Eneanya, N. D., Coresh, J., et al. (2021). New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race. New England Journal of Medicine, 385(19), 1737-1749 https://pmc.ncbi.nlm.nih.gov/articles/PMC8822996/
  • Academic Pavlakis, M. (2023). A Restorative Justice Project in Kidney Allocation: The Wait Time Modification for Black and African American Candidates Affected by the Race-Based eGFR Equation. Journal of the American Society of Nephrology, 34(10), 1618-1620 https://pmc.ncbi.nlm.nih.gov/articles/PMC10561813/
  • Government HRSA / OPTN. Understanding Race & eGFR (patient resources) https://www.hrsa.gov/optn/patients/resources/kidney/understanding-race-egfr

• The correction arrived in two board actions. After a public comment period running 27 January to 23 March 2022, the OPTN Board of Directors unanimously approved 'Establish OPTN Requirement for Race-Neutral eGFR Calculations' on 27 June 2022, requiring every kidney transplant program to use an eGFR formula without a Black-race variable from 27 July 2022; the National Kidney Foundation, whose joint task force with the American Society of Nephrology had recommended a race-free equation, called the vote an important first step and said there is no place for race-based variables in evaluating organs offered through the allocation system. Because a prohibition runs only forward, the Board then unanimously approved the retroactive remedy on 5 December 2022, effective 5 January 2023: each kidney program had to assess its waiting list, identify Black candidates disadvantaged by race-inclusive eGFR, establish whether a race-neutral calculation would have qualified them sooner, and apply to OPTN to backdate the qualifying date. Eligibility required documentation that the candidate's eGFR was over 20 mL/min under the race-inclusive calculation and 20 mL/min or lower without it. Programs had until 3 January 2024 to complete assessments, submit every qualifying modification, notify all kidney candidates before and after assessment regardless of race, and file an attestation; programs that did not comply would be referred to the Membership and Professional Standards Committee.

  empirical
  • Government HRSA / OPTN. Understanding Race & eGFR (patient resources) https://www.hrsa.gov/optn/patients/resources/kidney/understanding-race-egfr
  • Advocacy National Kidney Foundation (2022, June 30). OPTN Unanimous Approval of eGFR Guidelines is Important Next Step https://www.kidney.org/press-room/optn-unanimous-approval-egfr-guidelines-important-next-step
  • Government UNOS (2023). Waiting time adjustment approved for kidney transplant candidates affected by race-based calculation https://unos.org/news/waiting-time-adjustment-approved-for-kidney-transplant-candidates-affected-by-race-based-calculation/
  • Government HRSA / OPTN. Waiting Time Modifications for Candidates Affected by Race-Inclusive eGFR Calculations (policy page) https://www.hrsa.gov/optn/policies-bylaws/policy-issues/waiting-time-modifications-race-inclusive-egfr-calculations
  • Academic Pavlakis, M. (2023). A Restorative Justice Project in Kidney Allocation: The Wait Time Modification for Black and African American Candidates Affected by the Race-Based eGFR Equation. Journal of the American Society of Nephrology, 34(10), 1618-1620 https://pmc.ncbi.nlm.nih.gov/articles/PMC10561813/

• OPTN published its own counts twice, and each figure carries the date its data was cut. The early monitoring report (published 4 December 2023, data through 5 July 2023) recorded more than 6,100 Black candidates with modified waiting times at a median of 1.7 years, of whom 491 had received a deceased-donor transplant and 15 a living-donor transplant; at that date 12 of 232 active kidney programs had submitted attestations. The one-year report (published 8 May 2024, data through 4 January 2024) recorded 14,701 waiting-time modifications processed at a median of 1.7 years, with roughly half of modified registrations receiving between one and three years, 2,709 modified candidates transplanted from deceased donors and 158 from living donors, and all 230 active kidney programs having submitted attestations confirming that lists were reviewed, candidates notified, and required modifications submitted. These are counts of modifications and of registrations at specific snapshot dates rather than counts of distinct people, and they are cumulative figures that grew between the two reports.

  empirical
  • Government HRSA / OPTN (2023, December 4). Early monitoring report shows Black kidney candidates are receiving waiting time modifications after implementation of new policies https://www.hrsa.gov/es/node/30440
  • Government HRSA / OPTN (2024, May 8). Over 14,700 waiting time modifications completed for Black kidney patients one year after policy implementation https://www.hrsa.gov/optn/news-events/news/over-14700-waiting-time-modifications-completed-black-kidney-patients-one-year-after-policy-implementation

• An independent national evaluation measured what the programme's own counts could not. Schold and colleagues, publishing in the Journal of the American Society of Nephrology on 6 May 2025, assessed 44,912 Black candidate kidney waitlist registrations nationally and found that 32 percent (14,419) received an eGFR waiting-time modification worth a median of about 610 priority days, and that modified candidates had an adjusted hazard ratio of 2.85 (95 percent CI 2.7 to 3.02) for deceased-donor transplantation against candidates who were not modified. The same study found modification rates varying significantly by candidate characteristics and by transplant center; the investigators read that variability as indicating there was still mixed use of the policies and that the requirement was not articulated clearly at the beginning. The study's primary record was behind a paywall and a consent wall at verification time on 28 August 2026, and these figures are carried as corroborated through the trade report of the same study rather than as directly retrieved from the primary.

  empirical
  • Academic Schold, J. D., Arrigain, S., Husain, S. A., et al. (2025). Variation of eGFR Wait Time Modifications for Black Kidney Transplant Candidates in the United States. Journal of the American Society of Nephrology (published online 6 May 2025) https://pubmed.ncbi.nlm.nih.gov/40327843/
  • Trade press Healio Nephrology (2025, November 3). Race-neutral eGFR equation affects wait times, increasing transplants for Black patients https://www.healio.com/news/nephrology/20251103/raceneutral-egfr-equation-affects-wait-times-increasing-transplants-for-black-patients

• The measured unevenness produced a further governance action rather than a closed file. The Membership and Professional Standards Committee, having observed programs implementing the requirements in various ways, referred a follow-on project to the OPTN Minority Affairs Committee; after public comment from 21 January to 19 March 2025 the OPTN Board approved 'Monitor Ongoing eGFR Modification Policy Requirements' at its June 2025 meeting, effective 10 September 2025. The update converts the one-time legacy audit into a standing per-candidate obligation: every registered kidney candidate must be assessed for eligibility, and each program must maintain written protocols and document compliance in three areas — confirming a candidate's race, fulfilling the notification requirements, and seeking supporting documentation, naming at minimum which sources will be reviewed. The notification requirements (education, eligibility, and outcome) apply to candidates registered on or after 4 January 2024, and the update removes the superseded 3 January 2024 attestation language. Programs must complete the strengthened requirements by 11 September 2026, a date that had not passed as of 28 August 2026.

  empirical
  • Government HRSA / OPTN, Minority Affairs Committee (2025). Monitor Ongoing eGFR Modification Policy Requirements (policy notice, update to OPTN Policy 3.7.D) https://www.hrsa.gov/sites/default/files/hrsa/optn/optn-website_monitor-ongoing-egfr-modification-policy-requirementsupdated.pdf
  • Government HRSA / OPTN. Waiting Time Modifications for Candidates Affected by Race-Inclusive eGFR Calculations (policy page) https://www.hrsa.gov/optn/policies-bylaws/policy-issues/waiting-time-modifications-race-inclusive-egfr-calculations

• The undo ran by hand, program by program. Trade guidance written for transplant programs describes the working method: identify candidates through the OPTN custom reporting tool's 'Current waitlisted African American Candidates' query, pull historical laboratory results from the electronic medical record, from external and reference laboratories, from dialysis centers, and through record-retrieval and health-information-exchange systems, compare the race-inclusive and race-neutral figures against the 20 mL/min threshold, submit an eGFR Waiting Time Modification Form in UNet with supporting documentation, and send two notifications — before and after assessment — to every kidney candidate regardless of race. The same guidance records the correction's own second wave as a documented operational pressure: some patients were getting a lot of time back, bouncing them to the top of the list to start receiving offers, which it describes as a significant operational impact on many transplant centers, especially in ensuring that a patient had been re-evaluated recently. Accrued waiting time is a term in the ranking donor kidneys are offered down, so a backdated qualifying date changes a candidate's position in the live deceased-donor offer sequence directly rather than serving as a note on a file.

  empirical
  • Trade press The Alliance (Organ Donation Alliance) (2023). Insights: eGFR OPTN Implementation (Quality Corner) https://www.organdonationalliance.org/insights/quality-corner/insights-egfr-optn-implementation/
  • Government HRSA / OPTN. Waiting Time Modifications for Candidates Affected by Race-Inclusive eGFR Calculations (policy page) https://www.hrsa.gov/optn/policies-bylaws/policy-issues/waiting-time-modifications-race-inclusive-egfr-calculations
  • Government HRSA / OPTN. Understanding Race & eGFR (patient resources) https://www.hrsa.gov/optn/patients/resources/kidney/understanding-race-egfr

• The equity framing around this programme belongs to the commentary and policy materials that used it, and the same commentary records the critique. Pavlakis, writing in the Journal of the American Society of Nephrology in 2023, describes the waiting-time modification as a restorative justice project in kidney allocation and also records that the policy has been criticised as being unfair to people suffering under other inequities besides Black or African American race, and as both unfairly too broad and too narrow, leaving open the broader question of whether all patients should accrue predialysis waiting time. The remedy's scope is bounded on the face of the policy: it reaches registered kidney candidates whose documentation meets the eligibility rule, it addresses the eGFR-driven delay and no other source of delay, and it can only advance a qualifying date, never delay one. No litigation and no enforcement action appears anywhere in this record as of 28 August 2026; the record is affirmative governance — a prohibition, a retroactive modification programme, published monitoring, an independent peer-reviewed evaluation, and a tightening in response to measured variance.

  empirical
  • Academic Pavlakis, M. (2023). A Restorative Justice Project in Kidney Allocation: The Wait Time Modification for Black and African American Candidates Affected by the Race-Based eGFR Equation. Journal of the American Society of Nephrology, 34(10), 1618-1620 https://pmc.ncbi.nlm.nih.gov/articles/PMC10561813/
  • Government HRSA / OPTN. Waiting Time Modifications for Candidates Affected by Race-Inclusive eGFR Calculations (policy page) https://www.hrsa.gov/optn/policies-bylaws/policy-issues/waiting-time-modifications-race-inclusive-egfr-calculations
  • Government HRSA / OPTN, Minority Affairs Committee (2025). Monitor Ongoing eGFR Modification Policy Requirements (policy notice, update to OPTN Policy 3.7.D) https://www.hrsa.gov/sites/default/files/hrsa/optn/optn-website_monitor-ongoing-egfr-modification-policy-requirementsupdated.pdf

Where this connects

Institutional pressures in this domain

• Workload surge — Demand outruns staffing; per-case attention shrinks and review becomes triage.
• Reviewer bottleneck — One fixed-capacity checking stage sits between AI output and consequence; everything queues behind it.
• Vendor opacity — The deploying institution cannot inspect the model, data, or update pipeline it is accountable for.
• Data & policy drift — The world, the intake process, and the rules change under a system trained on how things used to be — two mechanisms with different remedies: the statistical properties of what the system processes move (concept drift), or the mixture of inputs arriving in deployment differs from the mixture it was trained on (covariate shift).
• Deadline pressure — Statutory or managerial timeliness rules reward fast approval of machine output over slow disagreement.

All of them in context on the Clinical decision support & deterioration alerting domain page.

Levers available here and the patterns behind them

• Upgrade model — Improve the model
• Check with a second model — Cross-model verification
• Understand the system — Understand the system
• Review on schedule — Oversight cadence & retrospectives
• Escalate checks — State-feedback vigilance
• Mark AI-written records — Provenance labeling
• Gate record entries — Human-in-the-loop write gating
• Check copied records — Reconcile copied records

Documented case histories

• OPTN eGFR Waiting-Time Correction
• TREWS sepsis early-warning system
• Advance Alert Monitor (AAM) deterioration model
• Sepsis Watch deep-learning detection system
• Proprietary EHR sepsis model (external validation)
• nH Predict Utilization Review
• Cost-Proxy Care Stratification
• CA-CDS Child Abuse Alerting
• IDx-DR Autonomous Screening
• Viz.ai LVO Stroke Triage
• IBM Watson for Oncology
• Practice Fusion Pain CDS
• UBH Level of Care Guidelines (Wit v. UBH)
• EviCore by Evernorth: the review threshold
• Cigna PxDx