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ZUSDURI Market Access SentinelZUSDURI Access Analytics · Priority KBQs 1–5 · recurrent LG-IR-NMIBC · J9282
Cohort: new enrollments, last 90 days
All payer segments
HUB · BI/PA · claims (example sync)
EXAMPLE DATA
Priority Business Questions (KBQs) 1–5Each card shows example KPIs plus a data availability rating from the KBQ review. All figures are illustrative example data.
Data availability:● Strong existing data● Existing-data candidate◐ Mixed◔ Needs research★ Core dashboard opportunity
EXAMPLE DATA

Access journey funnel: where patients are delayed or lost KBQ 4★ Data availability: Core dashboard opportunity

Where are patients getting delayed or lost across the access journey? Enrollment/PEF → BI → PA if required → approval → scheduling → treatment
1Enrollment / PEFPEF initiated → completed
3,140PEFs received
11% PEFs missing info
median 1.8 d PEF → BI complete · missing insurance card or pathology report
2Benefit investigationcoverage verified · OOP estimated
2,952
−188 (6%)
PA required for 58%
median 2.4 d PA identified → submitted · 5.1 d submitted → decision
3PA, if required1,712 required · 1,240 not required
2,844submitted or not needed
−108 (4%)
awaiting documentation
PA initial approval 84% · denials appealed 41%, 62% overturned
4ApprovalPA approved / benefit confirmed
2,606
−238 (8%)
201 exits cite OOP cost
median 3.2 d approval → scheduled · site capacity, patient availability
5Schedulingfirst instillation booked
2,318
−288 (11%)
no contact / declined
median 6.4 d scheduled → treated · chair time, reschedules
6Treatmentclaim / dispense confirmed
1,984
−334 (14%)
63% conversion · 412 in flight
18.9 dmedian enrollment → 1st instillation ▼ 2.4 d
63%PEF → treated conversion (90-day cohort)
14%largest drop: scheduled → treated
Time between milestones · median days
1.8
2.4
5.1
3.2
6.4
PEF→BI
BI→PA sub.
PA decision
→ scheduled
scheduled → treated
Top reasons for delay / no treatment · patients
PA pending, more documentation
318
OOP concern / declined
201
Site scheduling capacity
176
Incomplete PEF
142
No contact / patient declined
96
Data need: defined funnel + linked HUB milestone dates (PEF, BI, PA, approval, scheduling, treatment) and standard delay / no-treatment reason codes.
EXAMPLE DATA

Access & utilization by payer segment KBQ 1● Existing-data candidate

How do access and utilization differ by payer segment?
Payer segmentMixTreatedCovered livesApprovedCoverage / restrictions
Medicare FFS + supplemental31%712FFS96%Covered · LCD
Medicare FFS, no supplemental9%148FFS97%Covered · 20% coins.
Medicare FFS + LIS / dual6%121FFS95%Covered
Medicare Advantage24%46618.2M86%PA 71% of plans
Commercial22%42141.6M79%PA 83% · step edit
Medicaid / managed Medicaid5%826.3M74%PA 64% · varies by state
1,950treated with payer linked
50%Medicare FFS share of treated
17 ptsapproval gap, FFS vs Commercial
Sources: HUB BI results, payer policies, claims. Gap: confirm payer/benefit data can be linked to utilization; reimbursement confidence by payer is a research/field measure.
EXAMPLE DATA

Affordability limiting treatment KBQ 2◐ Mixed · needs research

Where and how significantly is patient affordability limiting treatment?
6.8%not initiating due to OOP
$640median est. OOP / course (BI)
38%use affordability support
SegmentAvg OOPMedianRange p10–p90Not starting
Medicare FFS + supp.$90$01.4%
FFS, no supplemental$5,420$5,16014.2%
FFS + LIS / dual$30$01.1%
Medicare Advantage$1,540$1,1807.9%
Commercial$1,210$6405.6%
Medicaid$12$42.3%
⚠ Abandonment threshold ≈ $1,000 OOP is a hypothesis from example HUB data. 62% of FFS-no-supplemental patients were never referred to affordability support.
Sources: BI OOP estimates, coverage / LIS status. Gap: true % not initiating due to OOP and the threshold need added analysis and/or research.
EXAMPLE DATA

PA burden & delays KBQ 3● Strong existing data

What is the magnitude of the PA burden and where are the delays?
58%require PA
84%initial approval (16% denied)
41%denials appealed
62%appeals overturned
PA cycle, median days
2.4
5.1
9.6
ID → sub.
sub. → decision
approval → treatment
Top denial reasons
TURBT / recurrence hx missing
37%
LG pathology not confirmed
23%
Step edit: MMC / gem first
17%
Site of care / OON
13%
Commercial BCBS cluster: decision time +3.1 d, ~112 patients waiting (new attestation form).
Gap: define PA timestamps and denominator consistently across HUB records.
EXAMPLE DATA

Claims & reimbursement KBQ 5◐ Mixed

What is actually happening after treatment (claims and reimbursement)?
91.4%paid 1st pass
9,846claims submitted
8.6%denied
27 dmedian to payment ▼ 11 d
72%denials paid on rework
Denial reasons
Units / NDC mismatch
29%
Missing / invalid PA #
22%
Medical necessity
18%
Days to payment by payer: FFS 16 · MA 31 · Comm. 36 · Medicaid 44 · predictability IQR 19–41 d
J9282 billed as 1 unit instead of 75 at 3 accounts · ~$0.4M pending. Recoupments / audits: not captured today.
Gap: claims/EOB completeness and representativeness; RAC/audit/clawback needs new tracking or research.
Next phaseKBQs 6–8 (not in this view)
KBQ 6Accounts moving from setup → repeat use ● Existing / linkage
KBQ 7Where FRM intervention has most impact ◔ Future analytic layer
KBQ 8Financial-risk concerns beyond PA & OOP ◔ Mostly mixed / research